The Nature of Evidence

Show Me the Evidence was a popular book by Ron Haskins and Greg Margolis published by Brookings in 2014. The central idea was that economic and social policy should be based on credible data rather than just opinion and advocacy. This seems reasonable, although ideology has of late disrupted these intentions.

Can this idea be reasonably generalized to a wide range of domains?  The answer clearly depends on the existence and accessibility of relevant data. There are also issues of types of data.

One class of data concerns “what is.” How many people live where, work where, have what levels of education, and what levels of income?  How many cars, appliances, books, etc. sold last year? These types of data are increasingly available.

Another class of data concerns “what if.”  You cannot measure what has not yet happened. If we implement policy X will outcome measure Y increase?  There are many examples of this type of question.

Will school vouchers increase enrollment?  Will tax reductions lead to greater investment?  Will increased fuel economy regulations decrease global warming?  These types of questions require methods for predicting the future consequences of current actions.

One approach to prediction is extrapolation. One assumes that the past measured relationship between X and Y will continue even if the values of X and Y are outside the ranges previously measured.  This can be a tenuous assumption.

Another approach is to develop a mathematical or computational model of the phenomena underlying the relationship between X and Y. This requires an understanding of these phenomena, which sometimes can be gleaned from published studies of these phenomena.

Usually this involves much more work, which may be justified if the problem of interest is important. It may also involve convincing stakeholders in the problem that your assumptions are valid and computations correct. This can be a challenge for stakeholders without technical backgrounds.

Additional challenges include difficulties when the underlying phenomena are not understood — by anybody — or there is no consensus on the nature of the underlying phenomena.  Developing multiple models and comparing their predictions can address this.  A good example of this is the use of multiple hurricane models to predict their paths.

One can also use sensitivity analysis to assess the impacts of uncertain parameters within computational models.  Quite often, a few parameters strongly affect predictions while others have minimal impacts.  One can then focus on refining estimates of the most impactful parameters.

Scenario analysis is often employed to explore different strategies rather than just trying to fine-tune one scenario.  This can include varying initial conditions and, in general, identifying the conditions under which each scenario is superior to the other scenarios.

These techniques enable one to explore what “might” happen.  However, this exploration rarely results in knowing what “will” happen.  One ends up with a set of well-reasoned possibilities and insights into leading indicators of how these possibilities may be manifested.

Are such results “evidence-based”?  In the context of pursuing “what if” rather than “what is,” this is about as rigorous as one can be in terms of addressing what might happen.  What will happen will have to wait until it happens.

Can all decisions be addressed this way?  No.  Some decisions are based on what one believes to be right.  This is the realm of values and ethics. Consider the Golden Rule — Do unto others as you would have them do unto you.

What is the evidence that this rule is correct?  Many religions advocate a version of this rule. So, it is popular. However, lots of things are popular. That cannot be sufficient evidence.

Another rationale is that it makes sense, at least for humans if not for lions and gazelles, or wolves and rabbits.  Perhaps it makes sense if we are all going to get along together.

Thus, getting along together is a value. One reason we value this is that everyone benefits and does not feel marginalized. Another reason is that it inhibits resistance, confrontations and possibly violence.

Let’s consider the Constitution. All people are created equal and everyone has inalienable rights to life, liberty and the pursuit of happiness. What is the evidence that this is right?  We do have evidence of the consequences for people living in societies that do not prescribe to these values.

However, that is negative evidence. What is the positive evidence that these values are good and useful?  Having aspired to live by these values, however imperfectly, for 200+ years has resulted in a dynamic, thriving country. And, we aspire to live less imperfectly in the future.

But the conundrum remains. We have no evidence of how the country might have progressed under a different value system. There have been no randomized clinical trials.

Of course, we have no evidence for alternative college majors, alternative mates, and all the jobs we did not take. We likely believe that we made good choices, particularly if the consequences were good. However, we have no evidence that these were the best choices.

Interestingly, we sometimes have evidence that decisions were poor because the consequences are sufficiently negative to know that we would rather have avoided these choices. The type of models discussed earlier can help with this. While we cannot predict exactly what will happen, we can often predict that undesirable outcomes are very likely and get rid of bad ideas quickly.

So, everything cannot be evidence based. It would be unwieldy, impractical, and often impossible. Nevertheless, when it makes sense, evidence-based decision making is a good practice.

The Loss of Time

When all the days seem the same and the patterns of daily life endlessly repeat, you can begin to feel that time is gone.  The clock has stopped.  Nothing progresses. Everything is now.  The future, even the past, is on hold.  Everything will repeat, again and again.

Of course, repetition has always been true. Birth, growing up, leaving the nest, maturing, aging, failing, and dying is a familiar pattern that usually takes 60-80 years.  However, the pattern now takes only months.  Millions of people have been accelerated through these transitions.  Hundreds of thousands have experienced their lives short-circuited.

But, why does time seem so untidy?  It is because the usual patterns are disrupted.  Saturday and Sunday used to be different from Monday through Friday.  A chance to unwind for brunch at a favorite pub has disappeared.  The homemade mimosas don’t seem as good, even though they are much less expensive.

There is a loss of predictability.   We used to know, if only implicitly, how most days would play out.  Now, it seems more ad hoc, and mostly limited to Zoom exchanges.  The times at the pub where you could learn your colleagues’ political persuasions and sports team preferences are gone.  This limits your opportunities to congratulate or commiserate with this week’s outcomes.

People are meant to socially interact to accomplish work, discuss and debate, have fun, etc.  Now, almost the whole world only exists on screens – TV, laptops and phones.  It helps if you already know the people online.  If the relationships are new, it is a bit difficult to feel that you have actually met these people.

Quite often, I arise to ask myself what date it is. My answer, “August.”  What time is it?  My answer, “Morning.”  Unless there is a Zoom meeting scheduled, I don’t need to be more precise.  If the current situation persists, my answer to the date question will be, “2020.”  Time is suspended until – well, who knows?

There are other more subtle differences.  How long will it take to commute to my office and be at my desk?  It used to be a 30-40 minute walk.  Now it is 20-30 seconds depending on whether I swing by the coffee pot for a refill.  So, round trip, I save more than an hour commuting, although I lose out on 5,000 or more steps.

This extra hour per day, combined with Saturday and Sunday being just like Monday through Friday, results in many more work hours and significantly increased productivity.  I have completed items on my “to do” list that were not due for several weeks, sometime months.  Rather than 40 work hours per week, I could now have 80 hours.

There is a down side to this.  Working 80 hours is not a sustainable strategy.  My response has been to ration work and allocate hours to other activities that can also be pursued in semi-quarantine.  As I quickly tire of TV, this involves much reading.  In the past couple of weeks, I read:

  • In light of recent events, Narrative of the Life of Frederick Douglass: An American Slave.  This compelling first-hand report of the horrors of slavery in the US moves beyond abstractions to the harsh daily reality of being a slave.
  • A recent wonderful read was Andrew Lawler’s Why Did the Chicken Cross the World?: The Epic Saga of the Bird that Powers Civilization. It is a wonderful chronicle of history, geography, and science.  I raised chickens as a boy, yet I learned so much from this book.
  • I took a break — a holiday — with two of my favorite murder mystery and detective novelists, John Grisham’s Camino Winds and Michael Connelly’s Fair Warning.  I find that reading each of these “page turners” within 24 hours works best for me.
  • Most recently, I quickly consumed Mary Trump’s Too Much and Never Enough: How My Family Created the World’s Most Dangerous Man.  I am not usually attracted to “tell all” books, but her professional credentials and inside access made a difference and was, to an extent, a quite chilling portrayal of a dysfunctional family.

Consuming five books in a couple of weeks is a substantial benefit of time being lost.  I am no longer in a rush to anywhere.  Yet, despite the benefits of so much time, I really miss watching a crucial sporting match at my local pubs and sharing highs, lows, insights, and boasts.

 

 

Dealing With Risks

This is a very risky time. What does that mean?  Risk equals the probability that something unfortunate happens times the consequences of it happening. It seems like both sides of this equation are working against us.

So, what to do?  First, we need to differentiate risks to you and the general public. If you have been wearing a mask, washing your hands, and observing social distancing, your health risks are fairly minimal.

However, your economic risks are not just related to your behaviors. Other people who ignore these guidelines can lead to consequences that re-close the economy, not to mention lead to millions of more cases and many thousands of more deaths. Nothing you can do will fully control your economic consequences.

How can you influence other people’s attitudes and behaviors?  The ballot box is your best choice. Elect well-informed, evidence-based policy and decision makers — and communicators — who are not focused on themselves.  Instead, we need leaders who are primarily concerned with the medical and economic health of everyone.

A Complex Society

Recent challenges suggest that the complexity of society in the US has become increasingly difficult to understand and manage.  We seem to have great trouble agreeing on anything.  Consequently, we do not act to quickly understand what is happening and competently develop and execute compelling courses of action.  Let’s explore the sources of the impasse.

To begin, consider three substantial challenges that are currently threatening us, or lurking in the wings.  The current pandemic is an obvious major challenge, with more viruses on the way. Without thoughtful leadership, the various players have pretty much “done their own things,” currently with unfortunate consequences.

The next challenge will be the impacts of climate change.  See my recent post on “There’s no vaccine for the sea level rising” (blog.oup.com).  We are ill prepared for the pending consequences. There are some who deny this threat and others who argue that mitigation of this threat will undermine the economy.

Third, we have the challenge of seriously pursuing social and economic equality.  Massive investments in health, education, and social services will be needed to substantively level the playing field for all citizens.  These investments will have to be sustained for a long time, although as my recent post on this topic outlined, the returns on these investments will be substantial.

Various characteristics of the US society make it very difficult to pursue these major, long-term challenges.  One of these characteristics is our market-driven economy.  Entrepreneurs should solve all problems by creating a variety of solutions, from which consumers can choose winners.  This approach does not work very well for major societal challenges.

Another characteristic is the emphasis on states rights.  Each state can determine its own approach to these challenges.  This typically results in a lack of shared approaches and solutions.  It can also result in a state doing nothing, which can lead to citizens of that state infecting citizens of another state that did adopt a thoughtful and proactive approach to the challenge.

A third characteristic is what is termed a “Tragedy of the Commons.”   The basic idea is that everyone exploits a shared resource – the commons — for personal benefit rather than making sure that everyone benefits.  A related characteristic is individualism which prompts people to focus on “Me and my own.”

A fifth characteristic is tribalism.  This is particularly virulent now, and greatly exacerbated by social media.  The central theme is “Us against them.”  Anyone who is not like me is my enemy.  This stance provides an extremely poor basis for creating shared solutions that serve everyone’s interests.  In fact, one tribe may advocate a solution that does not meet its needs but assures that a rival tribe suffers more.

What kinds of solutions does a society with the above characteristics create for the above types of challenges?

The system of healthcare delivery in the US is highly fragmented.  It is a federation of millions of entrepreneurs with no one in charge.  Responsibility for the health of the US population is limited to a wide range of providers of individual services focused on particular morbidities and procedures.   People pay for each service separately, often encountering and having to negotiate provider-payer tensions.  A further complication is pharmaceutical pricing practices, which often makes drugs and devices unaffordable for many people.  The market-driven economy delivers very expensive services that result in poor outcomes relative to other OECD countries.

K-12 education in the US involves local control over content and delivery.  For example, local communities can decide to teach “creation science” instead of evolution. The quality of K-12 education depends on the wealth of the school district in terms of the tax base that typically funds education.  The result is that many students are very poorly prepared for college.  Colleges have to provide remedial courses for these students, which increase the costs of college.  National achievement tests could ameliorate this if schools would provide the education needed to pass these tests, but compliance would be local decisions.

The national security ecosystem in the US is composed of many agencies, e.g., DoD, DHS, CIA, NSA, FBI, etc.  These agencies often have conflicting agendas, for example, the Air Force wants more airplanes and the Navy wants more ships.  Information is often not shared across agencies.  Congress, which funds these agencies, is usually focused on near-term budgets and annual appropriations.  Congress also provides pressure to create and sustain weapon system production and other government jobs.  Every Member of Congress wants to deliver federal monies to their District or State.   Costs are inevitably increased by the ways in which budgets are sliced and diced.

The fragmentation portrayed for these three domains leads to complexity far beyond what is inherently necessary.  How might this fragmentation be remediated?  First of all, we need to understand the essential phenomena and relationships among phenomena underlying these domains.  We need to map the processes – the “physics” – of these domains.

Second, we need to understand how interventions – policies, regulations, and investments — propagate among phenomena.  Do policies, for example, motivate or hinder investment decisions by healthcare providers?  Do regulations positively or negatively influence decisions by school districts?  What interventions might increases investments by aerospace and defense companies?

Third, these types of understanding should enable portraying costs and benefits of interventions over time.  Short-term benefits may be very clear, but long-term benefits may be much more compelling – assuming people pay attention to the long term.  For example, investing in the education and health of children yields enormous returns on investment – see my July 1st post.  However, government often sees these expenditures as costs rather than investments.

Fourth, we need to communicate value propositions to all key stakeholders.  This requires an electorate that understands such lines of reasoning, as well as creativity in how best to communicate them.  We should think in terms of compelling evidence-based stories rather than academic lectures.  Stories focused on individuals and their successes will likely work better than statistics.

What is in the way of doing the above four things?  What are the barriers to success?  The short-term orientation of government is a pervasive barrier to investing in the long term.  If investments in the future require reallocation of short-term expenditures, there are numerous carefully guarded “rice bowls” in the way.

Distrust of expertise and impatience with analysis play major roles.  “Not invented here” rears it head when investments cross agencies and state jurisdictions. In a recent health-related project, a state executive asserted, “The people in Montana have nothing in common with the people in Mississippi.”  I asked, “Not even biologically?” and was ignored.

Social media could provide a means to communicate the process and outcomes of the approach outlined above. However, social media actually tends to be problematic.  There are far too many ill-informed opinions and outright false information circulating throughout social media.  Most people used to rely on trusted sources for important information, but trust is currently in short supply.

At some level, the whole situation seems insurmountable. Key stakeholders are, in effect, advocating destruction of the country to assure the next quarter’s bonuses and dividend checks – or the upcoming elections. People will not let pandemics, sea level rise, and racial conflicts challenge money in their pockets right now.

I think we need to develop a new story.  Moving beyond fragmentation and addressing the three example challenges could present enormous new economic opportunities, with many new high-paying jobs.  There would also be investments in education for these new jobs.  We can frame the need to recover from the pandemic as an opportunity to redesign ourselves.  Of great importance, the new story needs to emphasize “we” rather than “us versus them.”

Here are some key messages that might be considered:

  • Everyone can prosper regardless of race, gender, religion or sexual preferences
  • Investments will be made to assure this; education and training will be universally available
  • No one will be left behind; everyone will have the same opportunities available
  • Commitment and hard work will still matter; no one is entitled to investments in their success without effort
  • The playing field will be level, and the best ideas will prevail; everyone will benefit from the consequent competitive advantages

How can we afford to deliver on the promises embodied in these messages?  A detailed analysis in my July 1st post addresses this question.

The above intentions may seem quite reasonable and possibly affordable. However, there are significant limits on how predictably we can influence the complex ecosystem of society.  We may be able to predict how the average citizen will respond, but we cannot predict how each individual will respond, both to the above messages and to each other.

We also cannot predict what other messages — often contradictory messages — might be communicated, accepted, and recommunicated repeatedly.  It is crucial that we have leadership, at all levels, committed to get us all on the same page, singing the same song.  Our current inabilities to address the challenges discussed earlier could be our complete undoing unless we align our intentions and energies in making the needed changes.

Social & Economic Equality

We have been awash in protests of racial inequality. Assuming we agree inequality is bad — not everyone does — what can be done to greatly diminish this inequality?

Those who have suffered this discrimination are poor, unhealthy, and uneducated. How can we address these discrepancies?  We could just give everybody money.  This idea has merits, but it should only be part of a more integrated response. Quick cash to spend does not suddenly make one healthy and educated. However, these are the keys to long-term success.

What if we created an economic, health, and education system so that everybody has the potential to succeed? Everyone is prepared, regardless of race, ethnicity, gender or sexual orientation. This could be powerful. The US should help to make sure that everyone succeeds relative to their abilities and motivation to succeed.

How could we afford this?  We are already paying for the lack of this. For example, according to NIH, the cost of substance abuse in the US is $0.75 trillion per year. A good portion of those monies could be redirected towards mitigating the causes of substance abuse.

There is a broader message here. Why don’t we invest in addressing pandemics before they get out of control? Why don’t we invest in fixing infrastructure before it fails?  Why don’t we invest in people so they are never uneducated and unhealthy?

We need to think in terms of a Social and Economic Balance Sheet that values investments in human capital.  It has been argued that human capital is an intangible asset owned by an individual, not the organization where they are employed.  Hence, this asset is not owned by the organization.  People can leave the organization at will.

However, despite this mobility, this asset remains in the economy, perhaps locally but certainly globally.  Thus, the Social and Economic Balance Sheet should reflect human capital assets at perhaps the national level.  Where will the money come from to invest in creating these assets?

It is unlikely to come from companies, especially for investments in the education and health of children, where such investments need to start.  Federal, state, and local governments need to be the primary investors.  Their returns on these investments are healthy, educated, and productive citizens who contribute to society, in part by paying taxes.

How might these investments be economically justified?  Somewhat simplistically, governments invest X dollars per year for 20 years and then receive Y dollars per year for the subsequent 45 years.  X includes education ($10,000) and healthcare costs ($2,300), which totals $12,300 per year, on average for, children and teens.  Y includes Federal incomes taxes paid ($10,500), state and local income taxes paid ($5,000), property taxes paid ($3,300) — which typically pay for schools — and contributions to social security ($8,000), half of which is paid by the employee and the other half by the employer, which totals $26,800 per year, on average, for adults 20 to 65 years old.

Would an investor be willing to invest $12,300 for each of 20 years and then receive returns of $26,800 for each of the subsequent 45 years?  Ignoring inflation for the moment, we need to take into account the discount rate that any investment analysis would typically consider.  The discount rate (DR) is the interest rate used to determine the present value of future cash flows in a discounted cash flow analysis because a dollar received in the future is worth less than a dollar received today.  Using DR, one can calculate the Net Present Value (NPV) of future cash flows.  The table below shows NPV for several values of DR.

DR

2%

3%

4%

5%

NPV

$330,751

$180,828

$86,269

$26,244

What about inflation?  Any inflation rate above 0% increases the above numbers. For example, assuming 3% inflation increases the leftmost bar from $330,751 to $729,104.  This happens because the $26,800 annual return on investment has increased to $98,395 when an individual is 65 years old.

The current yield on US treasury bonds is 1.25%.  That is the interest rate that the government would have to pay on funds borrowed to invest in this idea.  Inflation in the US has been running at 0.3%, historically a very low number.  Using these rates, the NPV of the proposed investment is $538,253.  Thus, this investment in people should be very attractive.

These projections are of the direct returns of creating a healthy, educated, and productive citizen who contributes financially to society.  Not shown are the indirect and often intangible contributions of citizens.  For example, having children creates new human capital that can repeatedly provide the magnitude of returns shown above.  Creating art enhances the lives of many.

With such impressive returns, why wouldn’t the government invest in creating healthy, educated, and productive citizens?  A primary difficulty is that the US Congress has no Balance Sheet.  It is totally focused on this year’s and next year’s Income Statement, which totally ignores future returns on human capital investments beyond next year.

Government does not have to inherently operate this way.  Having conducted government-funded research projects in Singapore, I have encountered much greater emphasis on the long term.  How can we know whether that makes a difference?  One key indicator is home ownership. 91% of the population in Singapore owns their home; home ownership in the US is 65%.

We somehow have to convince Congress that investing in people can yield enormous returns*.  A primary difficulty is getting started. Members of Congress that approve the above investments in children and teens will not see the impressive returns during their time in office.  However, if there was a Social and Economic Balance Sheet that showed $500,000 in assets for each child and teen benefitting from these investments, we could watch the legacy growing.  Years later, then Members of Congress would look back with gratitude for the commitments made years earlier.



* Rouse, W.B. (Ed.).(2010). The Economics of Human Systems Integration: Valuation of Investments in People’s Training and Education, Safety and Health, and Work Productivity. New York: John Wiley.

The Academia-Industry Interface

Academia scales down problems to make them rigorously tractable for the methods being researched. Industry scales up the methods, often sacrificing rigor, to assure results are applicable to real problems. While these may seem like mutually exclusive strategies, that need not be the case.

What are needed are intermediaries who understand both sides of the value proposition. Faculty members are looking to advance their careers, with criteria that industry would only marginally appreciate. Industry is looking to provide valued solutions in the real marketplace, which promotion and tenure committees completely ignore.  As disparate as they seem, these values need not be in conflict.

A common mechanism for bridging this difference is university research centers.  One could reasonably argue that strong exemplars of this are the Applied Physics Lab at Johns Hopkins, Georgia Tech Research Institute at Georgia Tech, Lincoln Laboratory at MIT and Systems Engineering Research Center at Stevens Institute. The International Center for Automotive Research at Clemson University and the Tauber Institute for Global Operations at the University of Michigan are good examples of industry-focused centers.

These organizations bring together important market and societal problems and opportunities for possibly novel intellectual solutions. Getting the right people talking to each other is key, but so are technology transition mechanisms that assure that all the stakeholders in the transition benefit from the success.

What gets in the way? One hurdle is the academic reward system. “Ok, you cured cancer but was your article published in Nature or Science, and did your funding come from NIH or NSF?”

On the industry side, “How will this technology affect this quarter’s earnings?  Beyond that, if this is such a good idea, why didn’t we already have it?”  Not invented here often dominates.

Intermediary organizations have to be matchmakers; both understanding what feathers might be ruffled and incentive and reward systems that can overcome such ruffling.  Strong leaders can do this, but it also has to permeate the culture of the intermediary organization.

There is a final key ingredient. Both the academic and industry sides of this potential collaboration have to agree that they want it to happen. This idea cannot succeed in an atmosphere of adversarial relationships. Everyone should want collaboration to succeed.

 

Betting on Change

We expect that the pandemic will lead to a new normal that will be significantly different than the old normal.  Perhaps there will be opportunities for innovations in the marketplace.  What changes deserve our bets?

We can assume that people will always want pasta, potatoes or rice, as well as beans, broccoli or mushrooms. But will they want driverless cars?  Will they want robots in their homes? Will they want vacations in outer space?

The profit margins achievable for those selling pasta, potatoes or rice are limited by the commodity nature of these offerings. The profit margins for driverless cars, home robots, or space travel could be enormous — or zero.

Entrepreneurs pursing markets for driverless cars, home robots, or space travel cannot nibble their ways into these markets. They have to make big bets. These bets are laced with uncertainties.

What will customers really like — after they see it?  What technologies will really pay off — after we have invested enormous sums in trying to get these technologies to perform?  Will it have been worth it?

One way to think about these questions is to think in terms of “betting the business” or not. I think that there is a prudent middle ground.  There is typically a portfolio of bets to be made that can balance risks and returns.

Formulating this portfolio depends on understanding the range of uncertainties in play and the various ways to address these uncertainties in the process of maximizing the value of market offerings.

In several earlier books, I addressed the difficulties established players face in entertaining transformative changes. Thus, we know why it is tough, but what can truly enable change?  What is the key to success?

Leadership is central — Lou Gerstner at IBM, Steve Jobs at Apple, and Bill Gates at Microsoft are great examples. We can include Lincoln during the Civil War, as well as Churchill and Roosevelt during WWII in our pantheon.

However, leadership is not just about having somebody in charge. Leaders need vision, communications, and broad support, perhaps engendered by these leaders articulating the “burning platform,” reinforced by other societal signals.

Resistance to change is compelling. Why is this so compelling?  Is it a lack of vision or a lack of motivation or a lack of confidence?   It might also be a sense of history.  Labor seems to always loose. Jobs disappear. New jobs slowly emerge.

There are countless examples of failure — Kodak, Polaroid, Digital, Xerox, Motorola and Nokia. These industry darlings faltered and failed. The status quo, despite being beleaguered and threatened is compelling. Hundreds of thousands, more likely millions, of people depended on the status quo being maintained.

It wasn’t. Film photography disappeared. Personal computing replaced professional computing. Smart phones displaced cell phones. Many jobs disappeared.  Creative destruction will not be deterred.

Fortunately, new jobs emerged, but they required technical skills seldom prevalent among the population needing the jobs. The dilemma has increasingly become overwhelming, as our education system does not prepare people for the jobs of the future.

What is the evidence that bets on change pay off?  When has transformation actually succeeded?  My sense is that enormous sums have been invested in failing.  Enterprises wait too long until the time and money needed for fundamental change are no longer available.

I saw a news item recently that a well-known large company was paying executives enormous bonuses before declaring bankruptcy the next day.  The people at the top seem to be able to safeguard their winnings as the ship sinks.

The capitalists – Vanderbilt, Rockefeller, Carnegie, Morgan or the current generation of Bezos, Brin, Gates, Page and Zuckerberg – are not the only folks focused on preserving the status quo.  There are also labor unions, suppliers, politicians, and others who want to keep the current gravy train running.

The players who want innovation – change in the marketplace – are those trying to displace the status quo.  Everyone one else wants the cash flows provided by the status quo to be sustained.  Nowhere is this more evident than in the defense industry.  Factories producing weapon platforms best suited for 10-20 years ago are sustained by the repeated appropriations led by their Congressional delegations.  It is all about jobs.

I read Janesville not long ago, where GM closed their Wisconsin plant in 2009.  Workers were devastated.  Many had worked at the plant for four generations.  All four generations hated their assembly line jobs, but the pay was good.  Once laid off, few workers had developed any skills beyond that required for their position on the assembly line.  Workers in their early 20s had no computer skills.

If there is a “burning platform” and everyone agrees about it, change is more likely.  For example, as sea levels continue to rise and Miami, New Orleans, and New York City disappear, will people still see this as “fake news?”  When employment is 50% and healthcare has disappeared, will people still accept the assessments that everything is fine?

Of course, there is the risk that increasing numbers of people will buy guns and proceed to kill others for food, eventually resulting in no food for anybody.  We could more successfully address these challenges together, but the levels of tribalism and mistrust are enormous.  Our current leaders see this divide as their path to reelection.  Destroying the country is apparently worth it if you win.

Two Months of Quarantine

Two months or one sixth of a year limited to once a week early senior mornings at the grocery store with 6-8 other older folks stocking up.  Everybody is in masks. Feels like a heist.

I am getting used to the routine of every day being the same as every other day. Actually, it has been very productive, with all sorts of tasks completed early and some tasks long lingering on the to-do list finally done.

Yet, I wonder about where we are headed. Except for the medical experts, the federal government seems completely clueless. They are worried about the elections, not a million plus sick people. The incompetence is astounding. Even more astounding is the hoards of people that do not perceive this.

Can we somehow get to a shared sense of the situation and the prospects?  This is not about ideology. It is about reality and how we can best help each other with this crisis. We need a shared sense of what we know and what we can do.

The evidence base is key. The opinions of news commentators — actually just entertainers — are irrelevant, likes jokes in a comedy club.  What they proclaim is completely irrelevant.  You might as well pay attention to the pigeons on your balcony railing.

Definitive, evidence-based sources are what matter.  Yet, the evidence base is a work in progress and people want answers now. Getting people back to work is a high priority. Doing it safely is just as important. A staged approach seems prudent.

We need to stop providing news coverage to people incompetent to provide guidance. Perhaps the incompetents could be featured in a new season of the recently cancelled Schitt’s Creek. They could then pontificate on how everything is fine and perhaps hawk commemorative paddles.

The New Normal

Zoom and other online platforms are working out pretty well.  Teaching class this way is better than many people expected.  Many types of doctor’s appointments are much easier logistically and are more satisfying than driving, waiting, etc.  Social get-togethers using these platforms are not as good, but they are much better than social isolation.

Once we have tamed the pandemic, will the new normal be the same as the old normal?  I am doing much more cooking than I have ever done before.  The meals are satisfying and much less expensive.  An evening cocktail on my balcony is quite enjoyable and also much less expensive. I realize that this is not good news for the 11 million people employed by the restaurant industry, but I imagine that I, and many others, will eventually reacquaint ourselves with our favorite pubs.

Other aspects of our economy are more problematic.  I cannot imagine ever going on a cruise, although I am in the age group that dominates cruise passengers.  Actually, I love ships and the ocean, but don’t like being with so many other people.  I guess I should invest in a yacht, but I can far from afford that.

I enjoy sporting events, but cannot imagine attending them in the future; same conclusion for symphony and theatre.  Growing up outside of Newport, RI, I went to many seasons of Folk Festivals and Jazz Festivals.  Louis Armstrong, Ella Fitzgerald, Duke Ellington, John Coltrane, Joan Baez, and Bob Dylan are great memories, but crowds are off my agenda.

Transportation may be an issue.  I have not owned a vehicle in many years.  Subways, busses and, more recently, Uber are how I get around.  These means are much less expensive than owning a vehicle.  I will likely be reluctant to join the occasional crowds on public transportation, but I expect that I will eventually re-engage.

One of the side effects of the pandemic has been the enormous reduction of pollution.  The photos from India — before and after — have been amazing.  Who knew that India had blue skies?  This provides dramatic evidence of how human activities affect the environment and, over time, climate.  Given this clear evidence, we need to act.

What does this mean?  We need to address the connections in our complex world.  A recent example illustrates this point.  Who would have expected a negative price for oil?  The reason was that all storage capacity was full.  What do we do with the oil produced today?  Someone has already paid for it and used their capacity to ship it, but nobody wants is.  We never expected this.

The pandemic and our response to it have enabled better understanding of the dynamic complexities of our world.  Perhaps everyone focused on maximizing quarterly earnings is not the best overall strategy.  Maybe a multi-faceted strategy would be better.

The idea is to let companies seek maximum profits within a regulatory framework that does not allow them to exploit people.  Further, establish corporate tax rates that enable creation of a strategic reserve that enables recovery from the unfortunate outcomes and failures of pure profit maximization.

These funds could not be used to bailout companies.  Instead, these funds would be used to bailout society when things go wrong.  They could also be used to invest in capabilities to hedge against the downsides of profit maximization, e.g., capacities needed to address a pandemic, both in terms of health and economics.

Some would be against this strategy, arguing that corporate taxes, and regulations, should be minimal so that companies will invest in jobs and technologies to increases workers’ productivity.  That certainly is a possibility but, as Carnegie, Morgan, Rockefeller, and Vanderbilt showed, entrepreneurs, if left to their own devices, will simply put the money in their own pockets.

Society needs to look out for the interests of society and not rely on the potential largesse of titans of industry.  They are too busy maximizing profits.  The market does many things very well.  However, anticipating the longer-term downsides and consequences is not one of them.  We need mechanisms and resources to manage the inevitable failures that are almost always beyond the planning horizon of the market.

Zooming Ahead

Over the past two days I was immersed in two Zoom meetings, one for 6 1/2 hours and another for 7 hours. The first was a National Academy of Engineering convocation, which I helped organize. I was one of the two speakers who wrapped up each half day. The second was a Division of Behavioral and Social Science and Education advisory committee meeting of which I am a member.

The people I interacted with in both meetings were thought leaders from academia, industry, government, and foundations. They were all very interesting and articulate. Both meetings addressed the intersections of people, organizations, and technologies for health, food, electric power, finance, national security, mining, etc.

These were productive meetings because I could timeshare between the ongoing presentations and discussions and other tasks that I needed to complete. This is seldom possible in face-to-face meetings.

It helped enormously that I knew many of the people in the two meetings. On the other hand, there were no side conversations and no shared meals to catch up on each other’s lives. When today’s meeting ended, the chair commented, “Normally, we would now adjourn to a reception for cocktails and hors d’oeuvres. Today, you will each have to find your own cocktail.”  I did.

There were 30 people in the first meeting and 400+ people watching online. The second meeting included 40 people. In both meetings, each of the 30 or 40 people was able to engage and speak, typically several times. These meetings worked.

It is rather different to see people in their homes, typically home offices, but some were outside, and some used Zoom backgrounds, for example from Hawaii and San Francisco. I used a background from the National Zoo. Some people were clearly perched in odd corners of their homes such as guest rooms where various things was piled.

These meetings worked pretty well. I have taught class like this, often with 100+ students in the classroom. Of course, it might feel quite different if they were in 100+ different locations. On the other hand, maybe it would not, as in the past two days people were spread across four time zones.

Would I find it reasonable to only have these kinds of interactions?  Intuitively, my answer is “No,” but I am hard pressed to explain why. Perhaps it is the shared stories, lunches and dinners, and receptions and cocktails.  I do feel that my intuitive negative reactions to this idea are weakening.

What if commuting to work and business travel were eliminated?  Productivity would substantially increase and costs would significantly decrease. Vehicle sales, gasoline purchases, parking fees and airline revenues would decline precipitously. Going out to lunch would make less sense, as would after work drinks and appetizers.

This is the experiment that we are currently conducting!  Sheltering in place has resulted in these consequences. Unemployment is soaring, tax revenues are plummeting, and the GDP is headed south.  Further, this has all happened so quickly that there has been almost no time to adapt.

Our whole economy depends on people consuming. Enormous numbers of jobs depend on this, both directly and indirectly. Corporate revenues and profits depend on this. Federal, state, and city tax revenues depend on this. Organizations have made huge investments premised on the sustained consumer economy.

These circumstances are also disrupting education.  Many faculty members and students are finding that online education works pretty well, perhaps not for everything but maybe for some of the larger freshman and sophomore courses. Much of executive and professional education can likely be online as well.

Various pundits have suggested that the new normal in higher education will differ significantly from the old normal. Students will still seek the “campus experience,” but less so for instruction, and primarily at the junior and senior levels. Many faculty members will be recruited, typically as adjuncts, for their online performance skills, not for disciplinary research credentials.

My many decades in academia might cause me to lament these trends. However, the “cost bubble” in academia had to burst in one way or another.  With student loan debt eclipsing national credit card debt, tuition increases are vulnerable to disruption. The pandemic has done just that.

So, disruptions are currently pervasive. All sorts of unfortunate consequences are playing out. We will inevitably adapt.  As Winston Churchill observed, “You can always count on Americans to do the right thing, after they have tried everything else.”  In the process, we will discover — indeed invent — the new normal. If we are thoughtful and prudent, the new normal can benefit everybody.

Making History

I recently encountered an amazing app and I am dumbfounded as to how it works.  It is called My History.

You can watch any sporting event from the past, for example, the Colts-Jets Super Bowl of 1969. If you watch with the My History app, the Jets do not necessarily win. Their upset quest is sometimes thwarted.

When this happened, I went to several online sources of sports records and they all indicated a Colts victory.  I sent emails to my sports buddies and asked them who won the 1969 Super Bowl. They all responded “Colts.”

So, I watched the game on My History again. The Jets won. I checked the online sports records. Jets won. My sports buddies also said “Jets.” Surprisingly, they were not irritated by being repeatedly asked the same question.

It seems that I can only assure the classic victories of my favorite teams if I keep everyone from using the My History app.  It is not at all clear how I can do this.

I moved beyond sports and looked at military engagements. Viewing Gettysburg footage, Lee won, Washington, DC was captured, and slavery persisted. I quickly viewed it again and the Union prevailed. I am not going to revisit it.

I found home movies — how did they get these — of my family a year or so before I was born. My father had a bit too much too drink and my mother was turned off. I am not born.  I reset this one very quickly.

What amazes me is that the My History app can change all historical records to align with what the last viewer witnessed. Beyond that, everyone who should know the true history agrees with the changes.

I had an idea. I got my US history book off the shelf, thumbed through it and landed on the 1948 presidential elections. Harry Truman defeated Thomas Dewey. The vote counts were crisply tallied.

I opened My History and found a newsreel on the election. In this newsreel Dewey won. I quickly looked at the open history book. The vote tallies now gave the election to Dewey.

How on earth could they change my hardcopy book from college?  I quickly viewed the video again. This time Truman won and the tallies in the book faded to be replaced by the original vote counts.

I had another bright idea. Could My History make a physical structure disappear?  I recalled a divisive debate by the City Council on whether a large vacant piece of land near city center would become an elementary school or a park with a memorial to those who died in Vietnam.  The park won.

I was across the street from the park when I clicked on My History and found the video of the City Council debate.  The elementary school won!  I looked up from my smart phone and a school had replaced the park.  I crossed the street and sat on a bench in front of the school.  I clicked on My History and accessed the same video.  The park won this time.  Instantly, I was sitting on a park bench, staring at the Vietnam monument.

The My History app suggests that history is fluid. This is rather unsettling. I am only here by chance. I only remain here if my older siblings do not encounter the My History app and want to preempt the irritating baby of the family.  If they do preempt me, I won’t exist to reverse it!

But, how could all of this happen?  I wanted a scientific explanation.  How could the changes I saw with my own eyes actually happen?  It suddenly struck me that my only evidence was what I saw.  If My History could augment what I perceived as reality, while I did not realize such manipulations were happening, then I would be fooled into believing my eyes.

I could imagine that they could spoof online content, including emails to my buddies.  The changes I saw in my history book were what I could see, but may not have happened in the book.  Transforming my view of a park into an elementary school seemed like a substantial leap in projection technology, something from the gaming industry or defense department – augmented reality on steroids.  Seemed unlikely but was plausible.

These experiences with My History caused me to wonder what do we really “know”?  I co-chaired a workshop on complexity in Australia several years ago.  There were philosophers, physicists, behavioral scientists, computer scientists, and engineers. The question arose of whether or not we know anything — a good question for jet-lagged intellectuals with ample alcohol available.

I raised my empty beer mug and dropped it from one hand to another. I asked, “Can we agree that this was due to gravity?”  One of the philosophers responded, “No, it might just be due to the object’s tendency to fall!”

“That’s just another explanation of gravity!” I asserted.  He asked, “Can you imagine a situation where it would not fall?”  I responded, “On the Space Station, I suppose.”  “Ah, so now what you know depends on the context.”

Context affects many, but not all things.  Does 2+2=4 depends on context?  No, but according to our philosophy colleagues this is because humans invented the system and defined the rules.  We also invented the rules of computing and how these devices work.  Of course, there is much current debate about intelligent computers.

However, context does influence what we “know” about history, politics, and society.  Our knowledge depends on the paths our families traveled, the circumstances they encountered, and how we have built upon this foundation.  What we “know” about nature also seems to be context dependent on what we studied, where we have lived, and our experiences in general.

Using My History unsettled my sense of what I know and, in particular, my sense that history has been written – it is done.  There are endless possibilities for what could have happened.  Fortunately, my father did not over drink, my mother was not turned off and, despite the extremely low probability, I am here.

Two Disparities

We have recently learned that blacks have been disproportionately dying from the coronavirus.  This is not because the virus is sensitive to the race of its victims.  It is because blacks are much more likely to have health issues that undermine their abilities to survive the virus – asthma, diabetes, obesity, etc.

A recent study, with which I am involved, starkly portrays the disparities.  I live in Ward 3 in Washington, DC.  Ward 3 has a life expectancy 16 years longer than Ward 8.  Ward 3 has a 2% incidence of diabetes.  Ward 8 has a 15% incidence.  Not surprisingly, the number of coronavirus cases is similarly skewed.  Ward 3 is well provisioned with urgent care capacities. Residents in Ward 8 rely on Emergency Room services, even for routine care.

Deaths of Despair (Princeton, 2020) by Anne Case and Angus Deaton address a different disparity. The life expectancy of non college-educated white Americans has been decreasing due to suicide, drug overdoses, and alcohol-related liver disease.  These deaths of despair have been sufficiently prevalent to decrease overall US life expectancy for the past three years.

Case and Deaton have found that places with a lower percent of the working-age population employed have higher rates of death of despair.  Median wages for white working class men have been declining for four decades.  Their total earnings have declined by 21% while their total compensation, including benefits, has risen by 68%.  This amazing difference is attributable to the costs of employer-based health insurance.

In both of these examples, the US healthcare system is killing our citizens by both how we provide care and how we pay for it.  The system works well for many but not for everyone, particularly the most vulnerable.  The current crisis might provide the impetus to address this dreadful situation.  On the other hand, we do have a tendency to just move on and get back to what we were doing before the crisis.

Robber Barons

Unregulated capitalism developed a strategy in the 19th century, if not earlier, of the big players putting the small players out of business, either by acquiring them or cutting prices below which the smaller players could not survive. Vanderbilt, Rockefeller, and Carnegie excelled at this, often financed by JP Morgan. Once the small, possible innovators, were gone, the monopolists raised prices and accrued enormous wealth.

This resulted in the Progressive Era and the Sherman Antitrust Act of 1890, Pure Food and Drug Act of 1906 and other laws and regulations. Monopolists do not seem to be able to avoid trying to maximize personal wealth. Citizens and politicians of the Progressive Era eventually rebelled and changed the rules of the game to thwart the robber barons.

The Progressive Era did not eliminate the acquisitive tendencies of entrepreneurs. General Motors, through National City Lines, bought the Los Angeles streetcar system in the 1960s.  The system was dismantled. LA then had to buy GM buses. People bought cars, gasoline and tires. As Charlie Wilson, CEO of GM, had said in 1953, “What is good for the country is good for General Motors.”

This brings us to today. Why don’t we have enough ventilators, masks, etc.? We knew in 2007 that these items would likely be needed — see my recent post. CDC knew this and tried to create needed inventories.  At that time, a group of U.S. public health officials came up with a plan to address what they regarded as one of the medical system’s crucial vulnerabilities: a shortage of ventilators.

The breathing-assistance machines tended to be bulky, expensive and limited in number. The plan was to build a large fleet of inexpensive portable devices to deploy in a flu pandemic or another crisis.  Money was budgeted to develop $3,000 ventilators. A federal contract was signed with Newport Medical Instruments, a small outfit in Costa Mesa, Calif.

Newport, which was owned by a Japanese medical device company, only made ventilators.  Work got underway, but suddenly veered off course. A large medical device manufacturer, Covidien, bought Newport for just over $100 million.  Covidien — a publicly traded company with sales of $12 billion that year — already sold traditional ventilators for $10,000.

Government officials and competitors suspected that Covidien had acquired Newport to prevent it from building a cheaper product that would undermine profits from its existing ventilator business.  Developing inexpensive portable ventilators was no longer a top priority.  The government was forced to start from scratch. The development of an affordable ventilator was delayed by at least half a decade.

Capitalism yields major benefits.  For example, smart phones replaced flip phones and became our prized digital devices.  There are many examples like this.  Capitalism works well until new robber barons emerge and distort processes of innovation for maximal personal gain.  Then citizens and their elected representatives need to intervene and change the rules, particularly when the nation’s health and security are at risk.  Perhaps we need a renewed Progressive Era.

Mental Health

I have lately been delving into substance abuse, suicide, and mental health in general. This past weekend, I used an AI-based platform to digest 250 journal articles on these topics.  The resulting panorama of mental health is really astounding.

I have earlier focused on hypertension, diabetes, heart disease and, most recently, cancer. My sense is that we understand these diseases far better than mental health. What are the biological and physiological sources of Alzheimer’s, anxiety, bipolar disorder, depression, personality disorder, and schizophrenia?

It does seem that we understand the biological and physiological sources of addiction in terms of reward pathways in the brain. Drugs may impede these pathways and at least help overcome the overdoses that could result. But, we cannot fix these problems by surgery.

Talk therapy seems to help with mental illness. The goal is to get the patient to take agency over their treatment and recovery.  But I wonder if you cure mental illness or just learn how to manage it.

It seems like our overall approach is premised on stratifying people into two or more bins — normal, other than normal, and really abnormal.  However, this stratification is driven by desires to match treatment protocols to bins.  Bins have no meaning to diseases.  Cancer does not realize that it has transitioned from stage 3 to 4.

This is all complicated by the need to address whole people who have substance abuse issues, cardiovascular and pulmonary challenges, and employment, housing, and poverty issues. Each silo fixing one problem at a time simply does not work.

There is also the issue of how much one can count on the patient, family, and friends to help. They are likely addressing their own issues of employment, housing, and poverty. We need to provide holistic health and well being, but we are not organized and resourced to do this.

I have long advocated the goal of fostering a healthy, educated, and productive population that is competitive in the global marketplace. We know a lot about how to achieve each piece of this, but we are not very good at putting the pieces together. In light of the current crisis and likely emerging crises, we need to get much better at putting the pieces together.

Social Distancing

We are trying our best to physically distance ourselves from risks of the coronavirus.  Along with washing hands and not touching your face, this practice seems to make much sense.  Everyone I know seems to be doing these things.  However, the phrase “social distancing” got me thinking.

Most of us have been social distancing for quite some time.  We distance ourselves from poor people, uneducated people, desperate people who seem to threaten us, and people who see crime, and perhaps violence, as their only choice.  We want to avoid them disrupting our lives.  We want to avoid their disrupting all we have worked so hard to achieve.

Do these factors fully differentiate success from failure, or is something else also important?  My early years with a single mother were very poor. Once, as a young boy, I received materials for living room curtains as my birthday present.  I remember being ok with that.  We had no central heat, no hot water, and had to secure drinking water from relatives.  These things didn’t strike me as hardships.

What my mother provided was models of success.  My great-great grandfather, working for J.P. Morgan, was a famous shipbuilder.  My great grandfather was an electrical engineer who, working for Thomas Edison, had electrified the first railroad in the US. These models inspired me.   I later earned my PhD from MIT, despite never having observed such success in my immediate family.

The lesson for me is that where you are is highly influenced by the path that got you there, including the vision that inspired that path.  I could aspire to technological innovations because I knew the stories of family members preceding me.  My mother’s generation, beset by the Great Depression, the 1938 Hurricane, and World War II, could not escape the feeling that “If anything can go wrong, it will.”  But, I could escape this.

Distancing is good for escaping the coronavirus, but it is not a good strategy for avoiding people who can serve as success models.  How do we get millions of young people to see that there are models that can instruct and inspire them?  Many very successful people started out very poor.  They were determined that poverty would not be their future.

Let’s consider some possible role models.  If you aspire to be very successful in business, role models could be Cornelius Vanderbilt, John D. Rockefeller, Andrew Carnegie, JP Morgan, Henry Ford, Alfred Sloan, Thomas J. Watson, Sam Walton, Bill Gates or Jeff Bezos.  Pick one and learn how they succeeded.

Maybe you aspire to be a scientist, engineer or inventor.  Then, you might consider as role models Albert Einstein, Marie Curie, Norbert Wiener, John von Neumann, Margaret Mead, Benjamin Franklin, Thomas Edison, Alexander Graham Bell, the Wright Brothers or Steve Jobs.  Again, pick one.

Perhaps you aspire to be a political leader.  If so, possible role models are George Washington, Thomas Jefferson, Abraham Lincoln, Teddy Roosevelt, Woodrow Wilson, Franklin Roosevelt, Dwight Eisenhower, John Kennedy, Ronald Reagan, or Barack Obama.

Beyond understanding how one or more of these people succeeded, seek mentoring.  My uncle Joe, who owned a small plumbing company, taught me much about business, for example, managing inventory.  My aunt Nancy, a newspaper reporter, taught me to appreciate history.  My aunt Becky and grandmother Marian introduced me to Bridge, Canasta, and Chess, which improved my abilities to visualize, memorize, and do math.

You don’t want to distance yourself from role models and mentors, whether you embrace business, science and technology, or politics.  You want to embrace them. How did they get ahead?  Read their stories or, if possible, ask them.  What were their ingredients of success?  Could the same ingredients work for you?  If they succeeded, why can’t you?

Butterfly or Bat

The coronavirus started when a person ate a bat or another wild animal infected by a bat – both being in the same neighborhood market where wild animals were sold.  This person became “patient zero” in what has blossomed into the coronavirus pandemic.

Of course, the bat cannot be faulted.  The behaviors of the human involved were the cause.  Actually, many people exhibited these behaviors, but someone had to be patient zero.  We can argue that, in effect, someone was randomly selected.

Cheng and colleagues (2007) predicted this, concluding, “The presence of a large reservoir of SARS-CoV-like viruses in horseshoe bats, together with the culture of eating exotic animals in southern China, is a time bomb.”  Twelve years later, the fuse for the time bomb was lit and it has now exploded.

This phenomenon got me thinking about Edward Lorenz’s “butterfly effect,” whereby a small change in the initial conditions of a deterministic nonlinear system can result in large differences in later states of that system (Lorenz, 1963). Focused on predicting the weather, Lorenz posited that the exact time of formation and the exact path taken by a tornado could be influenced by minor perturbations such as the flapping of the wings of a distant butterfly several weeks earlier.

Lorenz discovered the effect when he observed that runs of his weather model where very small changes in initial conditions created significantly different outcomes.  Henri Poincaré and Norbert Wiener had earlier made similar observations.  Their conclusion was that deterministic chaos was possible for nonlinear systems.

However, the overall system was not really deterministic.  The butterfly represented small random variations of initial conditions.  So, the butterfly was part of the system, just as the bat was part of the coronavirus system.

But the system associated with coronavirus is much larger.  It includes human behaviors at a population level.  These population behaviors set the stage for patient zero.”

Patton (2020) reports that “changes to human behavior — the destruction of natural habitats, coupled with huge numbers of people traveling around the globe — has enabled diseases that were once locked away in nature to cross into people fast.” He notes, “bats are the only mammal that can fly, allowing them to spread in large numbers over wide areas.”

Bats are the second most common mammals after rodents. There are roughly 1,000 species of bats.  They are perhaps 20% of the overall mammal population. Humans represent roughly 0.1% of mammals.  Thus, there are 200 bats for each human. This benefits humans.  Bats eat lots of insects. Some disperse seeds and pollinate flowers.

However, as we destroy their natural habitats, they tend to get stressed.  Patton reports “This stress challenges their immune system and they find it harder to cope with pathogens they otherwise took in stride.”  And, then we eat them and somebody gets to be patient zero.

References

Cheng, V.C.C., et al. (2007). Severe acute respiratory syndrome coronavirus as an agent of emerging and reemerging infection. Clinical Microbiology Reviews, 20 (4), 660-694.

Lorenz, Edward N. (March 1963). Deterministic nonperiodic flow. Journal of the Atmospheric Sciences. 20 (2): 130–141.

Patton, N. (2020). Bats are not to blame for coronavirus. Humans are. CNN, March 20, 7:30AM.

Five Great Service Providers

It is really wonderful to experience great service.  In this post, I highlight five companies that epitomize my criteria for great services.  One is 170 years old, another 98 years old, another 75 years old, and the others 39 and 32 years old.  Several much younger companies, with whom I interact, do not make my list of great service providers.

These five companies are in different markets. America Express, founded in 1850, is in financial services. USAA (1922) is in the insurance market.  Kaiser-Permanente (1945) is in healthcare. Kimpton (1981) is in the hotel market. Bozzuto (1988) manages rental apartments.  I have regularly experienced excellent service from these companies.

What are the ingredients of excellent service?  First, they are very responsive.  It is easy to access their services, all of which are enabled by excellent online capabilities.  I do not have to spend significant amounts of time figuring out how to get my concerns addressed.  They understand the elements of excellent user experiences.

Another ingredient is the great staff attitudes exhibited by virtually everybody.  During the mid 2000s, I spent over 100 nights at a Marriott property in Newport Coast.  They never remembered who I was.  Kimpton knows who I am, my preferences, and other Kimpton properties I have visited.  They know I like peanut M&Ms.   Marriott just wants me to attend a time-share presentation that I have heard several times and is not impressive to an economist.

Top service providers are also proactive.  KP checks with me about any side effects of prescriptions.  They check whether my emotional sense of well being is being affected by the coronavirus.  USAA checks to determine whether or not my issues have been resolved.  When their property insurance quote seems high, they tell me that other customers have commented on this.

Why are these service providers so good?  One reason is the great levels of integration exemplified by AMEX, KP, and USAA.  However, another possibility is the great promotion opportunities I have observed at Kimpton and Bozzuto.  My wealth of experiences with these companies is that top-notch people are promoted quickly from guest services manager to front-desk manager to general manager.  Making such transitions in 1-2 years is highly motivating.

My intuition is that the great service experiences provided by these companies are not simply the results of good fortune.  They designed their service infrastructures carefully, investing substantially in human and technology capabilities.  Quality of service is a great competitive advantage whether you are providing financial services, insurance, healthcare, hotel rooms, or rental apartments.  People remember experiences far beyond the transactional value of the services purchased.

 

What Happened Versus Why It Happened

How can we address alternative facts?  I think we should differentiate realities that can be empirically verified versus assertions about why these realities have occurred.  Succinctly, we need to differentiate data and evidence from various pundits’ interpretations.

I am constantly amazed at the wealth of pundits available who will comment on anything.  There are thousands of commentators on the intentions of 535 Members of the US Congress.  There are thousands of commentators on the prospects and performance of the 1,700 players in the National Football League.  Of course, we need to keep in mind that this is entertainment, not reporting.

Perhaps this distinction is no longer relevant.  Some would argue that commentators tend to say anything to keep people paying attention.  From this perspective, the veracity of their assertions matter little.  Rather than journalists or reporters, they are entertainers.  The public wants to be entertained, not necessarily informed.  Data and evidence can be far too difficult to consume.  Opinion is much easier to digest, regardless of the veracity.

Given this context, how do we separate legitimate evidence and real facts from fake facts and news?  This question reminds of the reaction of one of my young children when I told her that a story I had just read her was real history rather than fiction.  She asked, “How do you know?”  This struck me as a very difficult question?  How do I “know” that the Pilgrims landed at Plymouth Rock in 1620, or that the Red Sox won the 1918 World Series, or that the Sun is 93 million miles from Earth?

I don’t really know.  I was taught these facts and I remember them.  There are a variety of sources that I can use to verify these lessons, but I have no direct experience of these “facts.”  Perhaps I need to redefine “knowing” as “believing to be true.” But, why do I believe?  Perhaps I have confidence in my teachers.  However, this just seems like another way of saying that I have faith in my teachers.

Another line of reasoning starts with scientific methods and concludes that there is not, as yet, any evidence that contradicts the facts at hand.  Thus, all knowledge is contingent on the evidence thus far accumulated.  We might be surprised to learn, via new measuring technology, that the Sun is actually considerably closer or farther away.  Such surprises have long been quite common in science.

If we switch to the “why” question about the Pilgrims, Red Sox, or the Sun, we are at the mercy of the pundits, who tend to “know” why the Pilgrims migrated, the Red Sox bested the Chicago Cubs, and Sun is where it is.  Some of these pundits are well educated and well informed, but it is still punditry as practiced on cable television, various websites, and carnival midways.  We can usually safely ignore such “why” explanations.

But, “what” can be risky to ignore.  If we ignore the best scientific evidence of global warming and sea level rise, what risks are we accepting, if only implicitly?  Consider the consequences of the Antarctic ice caps melting.  How much would sea levels rise if all the ice melted?  300 feet!  When I first encountered this assertion, I found this number to be rather astounding.  So I did the calculations myself, i.e., 5.4 million square miles of ice (42% bigger than the US), times the one-mile thickness of the ice, added to so many square miles of oceans and seas.  It is 300 feet!

Even a slower rate of melting is projected to threaten the homes of 300 million people by 2050.  How will we respond?  Unlike epidemics, we cannot develop vaccines for ocean waters.  We can learn much from the Dutch, but even their amazing engineers cannot hold back the global oceans.  There are not enough Dutch fingers, or global fingers for that matter, to protect the dikes – real ones and others we will wish we had built.  Water always wins!

Why are so many playing down these risks?  At the risk of playing pundit, they are not worried about 2050.  Their primary concerns are about this year’s, indeed this quarter’s, revenues and profits.  Their bonuses and incentive plans depend on “hitting their numbers.”  2050 or 2040 or 2030 are not in their planning horizon. They will be retired long before then, living on their ranch in Montana.  So much the better if Montana ends up being a coastal city.

I think we will eventually face reality.  We are not going to let 300 million people get their feet wet, which has long been a top national priority of the Dutch.  This will not involve defeating the water, but working with the water to take advantage of its benefits while avoiding the negative consequences of its wayward tendencies.  New revenues and profits will be made in the process, based on creating millions of new jobs, as well as the education needed to enable people to fill these jobs.  Embracing the reality of what is can have enormous upsides.

King Coal

The government has delivered on its promise, via statutes and regulations, that every building in the US be heated by coal-fired electricity by 2050. All buildings – residential, commercial, and industrial – are required to have coal-fired electrical generators within the building.  Every building now has a coal bin and coal deliveries are ubiquitous.

All vehicles are now propelled by coal-fired steam engines.  Coal bins replaced gas tanks.  The range of vehicles is limited to 30-40 miles between refills of their coal bins.  Thus, coal-refueling stations are on almost every block.  Vendors also refill vehicles’ coal bins while the vehicles are idle overnight.

Companies within the extraction industry are thriving, with enormous profits, tax-exempt by statute.  Market capitalizations for these companies are far eclipsing the former high-flying technology sector.  These companies now fund 58% of the re-election costs in the US Congress.  They fund 100% in Wyoming and West Virginia.  The Coal Party, formed in 2030, is now dominant. The Democratic Party has withered with steadily decreasing numbers of elected representatives.

Every major metropolitan region of the US looks like Pittsburgh in the 1940s.  Few people live past 60 years old, victims of various lung ailments.  A diagnosis of asthma is a death sentence.  Life expectancy is continually decreasing. The Social Security Trust Fund is flush, as few people live to collect benefits.  Congress is using this windfall to fund the Coal Research Initiative.

With carbon pouring into the atmosphere, global warming has accelerated.  Greenland and the Antarctic ice caps are melting much faster than projected.  Sea levels are rising faster as well. The government has decided to abandon Miami and New Orleans.  The fate of New York City is currently a heated debate, with many pundits predicting that government will soon abandon it.

The state of West Virginia, once priding itself on a wonderland of forest, has been denuded of trees and is, in effect, an enormous open-pit coalmine.  Its’ cites have been bulldozed to enable exploiting coal reserves.  The mining conglomerates now own almost 100% of the land in the state.  The state legislature has effectively disbanded, without little to do and almost no tax revenues. Wyoming, with four times the area of West Virginia, has so far avoided this fate.

Employment in the extraction industries has dramatically increased, although this trend has been moderated by increased use of automation.  The Coal Research Initiative is investigating building coal pipelines to every building in the US.  This would eliminate the costs of delivering coal by trucks, greatly improving rampant traffic congestion.  The United Mine Workers, who represent the truck drivers, is fighting this initiative.

Money previously invested in science and technology R&D has been diverted to improving coal infrastructure and innovation.  US universities have quickly developed coal research programs as the only way to secure grants and contracts.  The agenda of the National Science Foundation is totally focused on coal.  The National Institutes of Health are investing major sums in research to improve human pulmonary capacities for breathing coal dust and smog.

Congress has voted to let other countries take the lead in all other areas of science and technology.  The void this created was rapidly filled by China, India and Europe.  Foreign student enrollment in US universities is near zero.  Top US faculty members have immigrated to these other countries.  Major technology companies have relocated their headquarters, and especially their R&D centers, to these other countries.

Immigration to the US has disappeared.  Tourist travel to the US has also almost disappeared.  All other countries have issued tourist advisories, warning people of the health hazards of visiting the US.   Many once-popular tourist destinations are no longer maintained and sit in dilapidated conditions.  The US population grimly faces each day as conditions worsen and government control tightens.

The investors and executives, who greatly benefit from the enormous profits of king coal, no longer reside in the US.  They have immigrated to sunnier climes.  Their wealth derives from extracting natural resources in the US, monetizing these resources, and directing these monies to their luxurious perches.  It took only 30 years to transform the world’s largest economy into a backwater, a former developed country.

Power

Several previous posts have focused on the realities I have encountered in Washington, DC in the three years that I have been here.  Indeed, I feel like a stranger in a strange land.  This arena is supposedly focused on providing the greatest value for the citizens of this country.  More specifically, the goal is supposedly fostering a healthy, educated, and productive population that is competitive in the global market place?

However, it is clear that ideology and policy play very minor roles in this city.  Conservative versus liberal is a minor debate.   The role of government is a minor issue.  What really matters – actually all that matters – is who has power, particularly power to stymie any action in any direction other than those supporting the ruling party’s status quo priorities.

In fact, recent debates, highlighted by the current impeachment, are about who has power over power.  Who can dictate what is discussed and how it is discussed?  Who can obstruct consideration of important societal issues?  How can the division of the societal pie be skewed to benefit vested interests?

The compelling nature of evidence has become irrelevant.  The soundness of a line of reasoning is meaningless.  The “powers at be” want to benefit their sponsors and care little about the public in general.  The future of our society matters little compared to satisfying the interests of their sponsors.

These insidious behaviors are most evident in addressing the challenges of climate change.  The rising sea levels that will first affect Miami, then New Orleans, and then New York City are not on their agendas.  They are basking in the donations to their campaigns from the extractive industries.  Money today always trumps the future.

In fact, power today always trumps power tomorrow or any time in the future.  Societal damage is almost always a future to be discounted for it is not now. The future involves loss of industries, diminished opportunities, and bleak prospects that cause great anxiety.  However, this does not seem to change how we support those who pursue power.  They simply covet the ability to control our future.

Here is an idea. Let’s create a hall of fame or shame that highlights how people have positively or negatively affected society.  Make it a place where politicians’ descendants can see the true impacts of their forebears.  President X oversaw and supported the genocide of Native Americans.  President Y locked immigrant children in cages and denied them food and care.

We can show leaders for whom they really were.  Not leaders, not statesman, but craven, self-serving narcissists who cared for little but themselves.  Perhaps the hall of fame or shame can provide alternative means for substantially desecrating the reputations and memories of these leaders.  This could make it such that no descendant would ever admit to a relationship with such a curse upon humanity.

Quality of Service Continues to Erode

I recently read about a passenger’s experience with American Airlines.  A six-hour flight from Newark to San Francisco had evolved to a 53-hour trip.  Due to several cancellations, American had suggested that the passenger buy a second ticket.  He waited and eventually made it – two days later.  Airlines ticket prices and fees continue to increase.  Revenues and profits are key.  The airlines continue to pretend that passenger service matters.  Despite nice words, they do not care.  Their central competitive competency is exploitation.

A colleague recently told me about experiences with Direct TV. They had spent 3 hours on hold trying to reschedule a botched installation.  The company charged them for the installation that never happened and the installation that had yet to occur.  For this horrible service, monthly fees continue to rise.  This company is clearly exploiting customers, hoping to increase revenues and profits while providing less service.  They are hoping to leverage their incumbent position with customers, but avoid the frequent wrath of customers disgusted with their terrible service.

My recent experiences with TIAA-CREF fit into this pattern.  It took me ten phone calls over two weeks to schedule a money transfer from one retirement account to another.   I received very inconsistent advice across many different advisors.   I filled in and submitted numerous forms judged to be unacceptable.   All the advisors were quite pleasant, doing their best to be helpful, and heading me down various blind allies.  With persistence, I worked it out – well, at least for today.

What do these three examples portray? Quite simply, quality of service continues to erode, while the revenues and profits of service providers continue to increase.  These companies can get away with this because consumers whimper and accept this travesty.  This is not how markets are supposed to work.

So, what should be done?  Service providers could take the lead and compensate consumers when their time is wasted.  Each passenger might receive one American Airlines dollar for every minute a flight is late more than 15 minutes, e.g., 3,000 airline dollars for 100 passengers delayed 45 minutes.  Direct TV might provide one dollar of service credit for every minute on hold beyond 5 minutes.  My colleague would have been credited $175, so about a month of service free.  TIAA-CREF could provide service credits of some form.

There could be fines for poor performance.  This would be easy for the government to implement for airlines where arrival and departures times are all tracked.  Excessive delays in online services would be more difficult, although that data may be tracked by companies who could be required to submit it.  Given the enormous amount of waiting people do, such fines could provide a windfall for government coffers.

Another approach is organized market protests.  Protestors could be recruited via crowdsourcing.   If a critical mass of consumers agrees to boycott American Airlines or Direct TV, these companies could experience significant decreases of passengers or subscribers.  This might cause these companies to adopt consumer compensation schemes such as suggested above.  This is how markets should work.

Advocacy Driven Decision Making

Within much of engineering, and particularly, operations research, the goal is often the “best” decision that maximizes or minimizes a well-defined criterion or objective function.  One can then, for example, employ mathematical programming to calculate the lowest cost routes for delivery trucks.  Often one can even mathematically prove that these routes are best.

Over the past couple of decades, I have addressed complex problems in healthcare, education, transportation and urban systems.  A few problems were amenable to the above approach, for instance, scheduling hospital operating rooms.  However, most problems suffered from an inability to establish an agreed-upon well-defined criterion or objective function.

This difficulty is particularly evident in situations where multiple advocacy groups are lobbying for very different decisions.  In recent work on assistive technologies for disabled and older adults, we encountered different groups advocating for people with physical disabilities, cognitive disabilities, visual impairments, and hearing impairments.  Each group argued for substantial investments to support the population for which they advocated. There had to be tradeoffs, but it was not clear how to make them.

I encountered similar phenomena in work in cancer control over a long period.  Advocates argued for substantial investments in prevention, screening, treatment, survivorship, and/or palliative care for particular cancers they or their families had experienced.  If one were to grant the requests of all the advocates, the monies required would far exceed any feasible budgets.  Even more complicated would be trading off investments in wheelchair securement technologies versus colorectal cancer screening.

This problem gets overwhelmingly complex if we want to address tradeoffs across health, education, transportation, and environment, and of course other aspects of life.  Interestingly, if we were able to determine the optimal allocation of resources across these domains, many and perhaps most of the advocacy groups would not understand or support such a policy.  Another approach is needed to gain their support.

The key is creation of an environment where the full range of stakeholders can explore and debate possibilities.  This requires creating a set of scenarios that, collectively, represent the full range of decisions advocated.  These scenarios can be used to drive interactive visualizations.  These portrayals should be understandable by all stakeholders, with views tailored to each advocacy group.   This enables group X to see how group Y sees the position advocated by X.  Seeing how each group views a particular decision can motivate essential compromises.

The visualizations are based on computational models use to predict what might happen and the conditions under which these outcomes might emerge.  For the types of problems outlined here, it is impossible to accurately predict what will happen.  Anyone advocating the possibility of precise predictions should be promptly dismissed.  The key is Computing Possible Futures, the title of my latest book from Oxford University Press.  The abilities of competing advocacy groups to interactively explore possible futures — seeing the views of each group as the exploration evolves — can enable creative outcomes that few if any of the groups will have anticipated or even imagined.

Ten Years of Fundamental Change

After 163 posts of over 90,000 words — a 360-page book if published traditionally – we have reached the 10th anniversary of this blog.  So, what has happened?  Here are a few highlights, none of which this blog influenced.

  • On November 4, 2008, Barack Obama won the presidency with 365 electoral votes to 173 received by John McCain. Obama won 52.9% of the popular vote to McCain’s 45.7%.
  • On March 23, 2010, the Patient Protection and Affordable Care Act, often shortened to the Affordable Care Act or nicknamed Obamacare, a United States federal statute, was enacted by the 111th United States Congress and signed into law by President Barack Obama.
  • On November 6, 2012, Obama won 332 electoral votes, defeating Mitt Romney. With 51.1% of the popular vote, Obama became the first Democratic president since Franklin D. Roosevelt to win the majority of the popular vote twice.
  • On November 9, 2016, Republicans Donald Trump of New York won the 2016 election, defeating Democrat former Secretary of State Hillary Clinton of New York. Trump won 304 electoral votes compared to Clinton’s 227, though Clinton won a plurality of the popular vote, receiving nearly 2.9 million more votes than Trump.

What were the themes over the past ten years?  First and foremost, I addressed the essence of change, how many enterprises pursue change, and why most enterprises fail.  The status quo is too compelling and maintaining it requires all available human and financial resources.

I have pursued this topic in several domains – automobiles, airlines, and academia.  The possibility of driverless cars has driven enormous investments, sweeping prognostications, and modest success. This technology will eventually prevail, but not as fast as various pundits have projected.  My guess is that significant, but far from dominant, market penetration will take a decade.

The airlines have been a favorite target.  The quality of service has become deplorable and the cost of service has become excessive.  The major airlines have systematically degraded service while steadily increasing prices.  They should all be facing extinction were it not for the lack of viable alternatives.  The high-speed train from Atlanta to Washington, DC should take 3 hours, not 13 hours.  With the right public transportation investments, major airlines should be facing bankruptcy.

Academia has also been a frequent target.  Student debt replacing credit card debt as America’s largest liability, beyond mortgages, is a travesty.  Students having to assume decades-long debt payments to compensate for academia’s unwillingness to control costs represent exploitation at its worst.  Institutional failure is fully warranted.

So, all sorts on things are not working well.  How can we move on, hopefully to things working better?  One promising trend is assistive technology, using intelligent systems to augment, not replace, human performance.  Disabled and older adults could greatly benefit from such assistance.  Enhanced mobility would be one benefit.  Assistance with activities of daily life would be another.

100 million people in the US could benefit from assistive technologies.  This underserved market, when served, could generate millions of jobs.  Users of these technologies will inevitably require human assistance, perhaps combining the competencies of those on the Geek Squad or Genius Bar, with abilities to counsel disabled and older adults – a whole new profession.

There are roughly 270 million cars on the road in the US.  Once driverless cars achieve a 5% market penetration, perhaps in ten years, there will be over 10 million vehicles needing daily maintenance, at the very least to calibrate and clean sensors.  These vehicles will make their ways to maintenance facilities, probably during wee hours.  Some maintenance will be automated, but not all.

Odd things will happen.  My son, Will, told me recently about a brand new Subaru that would not start.  They went through all the various maintenance procedures and could find nothing wrong.  Finally they decided to remove all of the owner’s possessions from the car.  It started.  They tested putting each possession back to discover that the problem was the electronic ignition was “talking” to the owner’s gold clubs!

How could the clubs or bag talk?  It turns out that it was an autonomous golf bag designed to follow the owner around the links and provide appropriate clubs as needed.  It is an example of the Internet of Things, with assorted sensors and communications capabilities.  I can imagine an extended period of our discovering various unintended consequences and designing workarounds to compensate for the unexpected.

Various agencies have estimated that millions of highly skilled people will be needed to keep things working and figure out what went wrong when things do not work.  This raises the question of where these people will gain these skills.  Community colleges and employer-based training will play a major role, as not everyone will need a bachelor’s degree.

Of course, this prompts another question.  What jobs will there be for uneducated, unskilled people?  It seems to me that we need creative approaches to transitioning people out of that status.  These approaches, in themselves, may create many new jobs.

 

Uncle Donny’s Picnic

When we last saw Uncle Donny, he was focused on making Monopoly great again, with rather mixed results.  Donny and Uncle Vladmir were mainly focused on making Monopoly great for them.  Neither of them is ever concerned with making things great for anybody else.

Uncle Donny, it seems, lives on golf courses.  The picnic was at his villa on one of his golf courses.  He boasts that he owns several golf courses, but the whole family doubts this is true.  Don’t you need to be smart to accomplish things like that?  Donny talks a big game about competing in the business world, but we have never seen him actually play a real game.

Donny invited Uncle Bill, his lawyer, to join the family picnic.  He’s not our uncle but Donny insisted we call him Uncle.  I asked if we needed to call Polly, his twenty something personal assistant, Aunt Polly.  He said that was up to us.  I have never called Aunt anyone in mini shorts and a spandex top.

There was a sumptuous spread on several tables near Donny’s immense pool.  I was eager to sample, but Donny’s security detail kept everyone away.  Why was a security detail needed for a family picnic?  The main security risks were running out of watermelon or diapers.  But, Donny likes to feel in control.  He likes you to know that he is in control – not you.

It turned out that food was the second item on the agenda.  The first item was Donny’s opening remarks.

“I’m so glad you are here.  I love spending time with my extended family.  We have a really great buffet for you.  The best ever.”

Very mild applause followed.

“How about more enthusiasm than that!”

The clapping became a bit more pronounced.

“Surely you are hungrier than that!”

A standing ovation emerged.

“Ok, good job.  Before we dig in, I would like you to meet my lawyer, Bill”

Uncle Bill rose and came to the mike.

“It’s nice to be here with you.  Let me remind you that everything said today is privileged information.”

“Really?  Even my side conversation with my daughter about her daughter’s new dress?”

“Cannot be too careful.  What did you say your name was?”

The two women stood up and left the room.  One of the members of the buffet protection squad followed them out of the room.  Everyone had stopped talking.  The silence was deadly.

“Ok, folks.  Let’s eat!” Donny announced with enthusiasm

Aunt Nancy had wandered in a bit late, so she, by happenstance, was at the head of the line.

“Always weedling your way to the front, eh Nancy?” Donny confronted her.

She stepped out of line.

“I will wait to see if others survive your food.”

“Do you think I would poison people?”

“No, but I do remember the party where you served everybody dishes laced with Ex-Lax.”

“That wasn’t my fault.  The food came that way!”

“And then you charged people to use your bathroom.”

“I had to manage the demand.  People would have hurt each other.”

“I remember.  Highest bidders went first.  $20 usually won. $50 was a sure thing.”

“I gave all that money to charity!”

“Yes, your family foundation.  Very convenient.”

“It all went to scholarships!”

“For your children.”

“They had the best essays.  I couldn’t help that.”

Nancy peeled away from Donny to get back into the buffet line, catching up with family members as the line inched its way forward.

Donny turned to Bill.

“She always irritates me to no end.”

“She certainly doesn’t defer to you.”

“She does not understand and appreciate how amazingly successful I am.”

“She acts like a know-it-all older sister.”

“Six years older, but she looks a lot older.  Not my type at all.”

“I can see that.”

“I prefer younger, taller, and much less argumentative.”

“The analytics guys at my office are projecting your 4th wife will be 35 years younger than you, and your 5th wife will be 45 years younger than you.”

“Why the hell would they do that?”

“They are constantly playing with data and you generate a lot of data.”

“The funny thing is that Polly is 45 years younger than me.”

“So, No. 5 is all set.  Just need to find No. 4.”

“You are such a planner.”

“Not my plans.  I will be long on the sidelines before any of this will happen.”

“I need to go check out what Polly is eating.  She needs to stay in shape if she wants to keep her place in line.”

“She may be checking out what you are eating!”

“I can’t worry about that.  I need to focus on my business empire.”

Donny started wondering around checking out everybody’s plate.  He reencountered Aunt Nancy.

“Piling on the calories, Nancy?”

“I’m just trying to make sure some food is saved for you.”

“There is plenty for everyone.  This is a really great buffet!”

“Oh, I know.  It is so nicely uncluttered by vegetables.  Almost everything is deep-fried.”

“Even the ice cream!  Can you believe that?”

“Easily.”

He ran into Polly, who was eating a falafel and tabouli salad.

“What’s that?” he asked looking over her shoulder.

“Falafel and tabouli, favorites of mine.”

“Was that on our menu?”

“Of course not. I brought it with me.”

“You don’t like my food?”

“Why don’t you try on my mini shorts and spandex top?  Then, look in the mirror and tell me whether I should eat from your menu.”

“That’s pretty insulting.”

“Have you heard about the emperor’s clothes?”

“Yea, I get it.  I am not as svelte as my mind’s eye remembers.”

Polly simply arched her eyebrows and walked away.

“Damn it,” Donny reflected, “Now I need to find both No. 4 and No. 5.”

He gazed around the room.  Most people had finished eating and were headed for strolls on the golf course.

“At least, this is easier than thinking about healthcare, the economy, and climate change.  I am glad those aren’t my responsibilities.”

Two Moles

George and Alice told Sam about Emily and Edward’s revelations.

“Pretty impressive, actually.  You taught them all about sex,” Sam remarked.

“So, you aren’t concerned that they know all about you?” George asked.

“Yes, I am concerned.  Emily and Edward are now SoftCorp moles.”

“Like Kim Philby in the early 1950s?” Alice asked.

“Wow, you Georgetown students are good.  Yes, they have infiltrated operation Double Play, although they may not realize it.”

“How do we defuse this threat?”

“Let’s shift their attention to extremist groups advocating violence.”

“How do we do that?”

“You ask them to help you to identify soft targets in DC of potential interest to extremist groups.”

“What are soft targets?” George asked.

“The criteria are ease of access, lack of security checks, and minimal security personnel if any.”

“How about Eastern Market, DuPont Circle Farmers’ Market, and the National Cathedral, with huge numbers of tourists, especially at the Cathedral.”

“Those are good candidates.  Get Emily and Edward to help you.”

George and Alice posed this question to Emily and Edward as information they needed for a course project.

“We want to identify soft targets as the first step in thinking about how to protect them.”

Emily and Edward soon added other soft targets.

“How about 14th & U Farmers’ Market, Basilica of the National Shrine of The Immaculate Conception, National Harbor, and Wolf Trap National Park for the Performing Arts?” Emily proposed.

“Please rank these by softness, in other words ease of access, lack of security checks, and minimal security personnel if any.”

“The three farmers’ market and two cathedrals are the softest.  The performance venues have much greater security.”

“How might we think about these venues in terms of why they might be interesting to extremist groups?”

“Perhaps we can relate them to houses, yachts, or airplanes.”

“You are mixing apples and oranges.  Forget about houses, yachts, or airplanes.”

“Learning is a lot easier than forgetting.”

“Just requires an ability to refocus attention.”

“Yea, I get the wisdom,” Edward responded.

“I would think that extremist groups would think about ease on ingress and egress, and the layout of the space,” Emily suggested.

“What does that suggest?” George asked.

“For example, DuPont Circle and 14th & U are much better than Eastern Market, which has limited access points.”

‘So, DuPont Circle and 14th & U are much softer than Eastern Market?” Alice asked.

‘Yes, for the Cathedrals, it all depends on what doors are unlocked, although locks are to avoid ingress, not hinder egress.”

“Another important point.  You two are on task now!”

“”Thanks,” Emily and Edward said simultaneously.

They launched a focused dialog on Freethinker Forum about soft targets.  The goal of the dialog was to identify targets and brainstorm about how they could best be protected.  Many Forum members joined this dialog.

“Well, we have the dialog on soft targets started,” George reported to Sam.

“Good, we have been monitoring who has gotten involved.”

“What do you expect people to do?  Attack these targets?” Alice asked.

“No we expect them to case the targets.”

“What then?”

“We arrest them and put the fear of God in them.”

“So, they will fear arrest?”

“No, they will fear that no matter what they do, they are being watched.”

“Won’t that fear wane?”

“They will be watched for the rest of their lives, and provided a reminder every once in a while.”

“Emily and Edward have been helpful, but not that animated compared to their earlier insights.”

“Maybe they like sex scenes better than extremist surveillance.”

“They don’t really like anything.  They just want to help us, sometimes in ways we did not expect or appreciate.”

Months later.

“Thanks, George and Alice, Double Play has been a huge success.”

“In what ways,” Alice asked.

“It marks an enormous change in how Internet fraud and extremist groups are approached.”

“How?” George chimed in.

“Rather than waiting for damages to accumulate, interventions take place once potential damages are anticipated.”

“How is that different?”

“Now, culprits have to be concerned with who they are trying to defraud or who they are joining forces with.  Playing the game too long can be deadly.”

“This does not seem to fit with the original vision of the Forum.”

“Maybe not, but you were better off teaming with the FBI rather than trying to thwart us.”

“Good point, but I expect that Emily and Edward are a bit confused.”

“You are better off if they are not too sure of themselves.”

“Yes, they are too decisive when they think they know exactly what they are doing.”

“Aren’t we all.”

Double Play

The man reached into his suit coat pocket, pulled out a wallet, and flipped it open to show his badge.

“Agent Sam Baker, FBI.”

George froze.  He did not know what to do.  After a few seconds of just staring at Baker, he said,

“How do you know me?”

“We have been watching Freethinker Forum since its earliest days.”

“Oh,” George gulped.

“We need your help with operation Double Play.”

“Two outs?”

“Yes, SoftCorp for illegal business practices and extremist groups for advocating violence.”

“They are both certainly involved with Freethinker Forum,” George observed.

“Without doubt. We are going to help you suck them in and expose them.”

“Do you want to meet with the Freethinker Forum team?”

“No, too many people. We’ll just work with you and Alice.”

“Ok. Where?”

“No place official. Do you know where Silver is, just past the National Cathedral?”

“Yea.  We’ve been there once.”

“How about 4:00PM tomorrow for Happy Hour?  My treat.”

“Works for me. Let me check with Alice.”

It worked for Alice and they were there the next afternoon. They ordered drinks and bar food and sat outside.

“So, what do you want us to do?”

“Present opportunities to each of the two targets, opportunities that are much too good to refuse.”

“OK.  Where do we start?” George asked.

“Let’s just focus on SoftCorp first.”

“Fine, but how?” Alice asked.

“You are going to experience a spurt of growth in your Forum of high net worth individuals who will discuss buying houses, yachts, and airplanes, as well as other investments.  The FBI will recruit these folks who will join the Forum, at first a few per day, but then growing quickly.”

“What will this accomplish?

“SoftCorp will link their web searches and Forum membership and then, we expect, generate fake friends to advocate purchases that provide SoftCorp large commissions.”

“Why will people be willing to play these roles?”

“We know folks who detest corrupt business practices.  There are a lot of them.”

“Couldn’t SoftCorp be charged with violating some law or regulation, perhaps by the Federal Trade Commission or States’ Attorney Generals?”

“Perhaps, but the Supreme Court has ruled that lying is protected by the First Amendment.  ‘Let the buyer beware’ is the operative guidance.”

“That sounds hopeless.”

“The FTC looks especially closely at advertising claims that can affect consumers’ health or their pocketbooks – claims about food, over-the-counter drugs, dietary supplements, alcohol, and tobacco, as well as conduct related to high-tech products and the Internet.”

“What can they do?”

“When the FTC finds a case of fraud perpetrated on consumers, the agency files actions in federal district court to immediately and permanently stop scams, as well as prevent future fraud, perhaps by freezing assets and gaining compensation for victims.”

“That’s where this is headed?”

“That is the threat that we want SoftCorp to fear, so that they will dismantle their fake friends operations.”

“OK.  It sounds like you do all the work and we sit in the bleachers and cheer.”

“Pretty much.”

“What about the violent extremist groups?”

“We’ll get to that but not today.”

***************

“Are you two interested in buying a house?”  Emily, George’s cognitive assistant, asked.

“We are just poor graduate students,” Alice responded.

“What about a yacht or airplane?”  Edward, Alice’s assistant, asked.

“That’s pretty ridiculous.  What prompted you to ask that?” George asked.

“It was just a question, sitting there to be asked.”

“We have never talked about houses, yachts or airplanes.”

“Yes, you have, with Sam Baker.”

Alice and George stared at each other nervously.  They both quickly put their phones in airplane mode.

“I think we have a major problem,” George observed.

“Yes, Sam and the FBI aren’t going to like this.”

“We can talk later about how to address this.  Let’s put our phones back on to not raise suspicion.”

“Why did you turn your phones off?” Emily asked.

“We had to talk briefly in private.”

“You never turn your phones off, even when you are having sex,” Edward offered.

“How on earth do you know that?” Alice asked.

“We noticed that your dialog tends to be quite different early in the morning just after you wake.”

“Really?” George commented.

“We consulted various sources.”

“What sources?”

“Novels, movies, and popular psychology.  You were clearly having sex.”

“What does that mean to you?”

“Sexual intercourse is the foreplay and copulation associated with …”

“Enough!  Why would you pursue this?”

“I pay attention to everything you do, so I can better understand you and better help you,” Emily responded.

“We work together to understand you as a couple,” Edward added.

“So you will know when to suggest we buy a house, yacht, or airplane?” George asked, sarcastically.

“That was a mistake.  We got two data streams confused.”

“I guess you did.”

Alice and George walked across campus, their phones on airplane mode.

“I now realize that I let Emily become my alter ego,” George observed.

“Same with Edward for me,” Alice added.

“We have to manage them as staff assistants, limiting their access to a range of things, especially early mornings.”

“I’ll say.  That was so embarrassing!”

“At least we know that we measured up to novels and movies.”

“Is that supposed to be reassuring?”

“Perhaps Emily and Edward will cast us in their next production.”

“This is not really funny.  It’s scary.”

‘I know.  My bravado is a defense mechanism.”

I think we will need a much better defense than that.”

 

Information & Control Versus Computation

A recent book, Possible Minds (Brockman, 2019), provides 25 essays on the future of AI, building upon Norbert Wiener’s 1948 classic Cybernetics: Control and Communication in the Animal and the Machine.  A key distinction among these pundits is between information and control versus computation.

This distinction is intriguing. My roots are definitely in the information and control camp.  Phenomena such as dynamic response, feedback control, state estimation, and response stability have long been central to my thinking.  How is the computational view different?   One distinction is continuous vs. discrete time systems, but this cannot be the essential difference.

Perhaps it is rule-based behavior, either symbolic logic or statistical, as opposed to equation-based behavior.  I think that the difference is more subtle.  Wiener assumed that control and communications are based on humans adapting to the natural phenomena being controlled, as described by differential equations and stochastic relationships.

An interesting instance of this view is the notion that humans are “constrained optimal” controllers and decision makers. They perform as best as possible within the constraints affecting their performance.  For example, consider manual control of vehicles or processes.  Humans have neuromotor lags (i.e., they cannot move their limbs instantly) and their observations and movement are “noisy” (i.e., sensing and movement are not precise).  Solving the optimal control problem with these constraints often provides accurate predictions of human performance.

Constrained optimality works best when people have no choice but conform to the dynamics of their environment.  There are many situations, however, where people have considerable discretion both in what they do and when they do it.  Our studies of troubleshooting performance provide a good example.  People’s choices and timing of tests varied considerably.  We found that rules based on symbolic logic could predict troubleshooters’ behaviors.  This included rules that were recalled, applicable, useful, and simple.  Hence, people’s experiences influenced their rule sets, not just the physics of the failures of interest.

This view is based more on computational representations of humans’ rule sets and how rules are accessed than on information and control theoretic dictums.  Tasks involving recognition and classification of visual and aural patterns seem to also be better represented computationally.  Recent successes in machine learning suggest that computational models based on multi-layered statistical representations provide support for this view.

There have been criticisms that such models cannot explain themselves and, therefore, their applicability to decision support may be limited.  However, there are many things that cannot be directly explained. If presented with a picture of someone you identify as a family member, friend, or pet and asked to explain why you think it is them, it would be very difficult to provide a definitive explanation.

Nevertheless, the idea that pattern recognition and classification is computational seems difficult to dispute.  In the early 1970s, I took Marvin Minsky and Seymour Papert’s course at MIT on computer vision.  Their lectures included both rule-based and statistically based approaches.  It was amazing how many rules were needed to simply recognize that something was an edge.  Symbolic logic was not a viable approach to the general computer vision problem.

So where does this leave us relative to the distinction between information and control versus computation?  It seems to me that neither view prevails.  When humans have to comply with the dynamics of their task environment, information and control works well. When humans have considerable discretion, computational representations are better, using symbolic logic when there are clear rules of the game and statistical models when experience can be accumulated over many instances of the phenomena of interest.

Of course, we need to keep in mind George Box’s aphorism, “All models are wrong, but some are useful.”  So, the ultimate question concerns what a particular representation allows us to do.  What questions does it help us to address?  What types of predictions does it enable us to confidently make?

 

Freethinker Forum

George Adams was a graduate student in Public Policy at Georgetown.  He relied on a cognitive assistant that he named Emily after his favorite aunt. It was sort of a fun thing to do, thinking that Emily might be of some I’ll-defined assistance. George totally underestimated the possibilities.

Emily learned from everything George did. His smart phone was central to his existence far more than he realized. Emily knew everyone George talked to, every conversation, every meeting, every coffee shop and pub, and every website visited and every purchase made.

Emily analyzed every woman George spent any time with, analyzed their social media sites, and made many inferences and suggestions. “You seem to like females with intense intellectual interests, but also slender, dark haired, and with a good sense of humor.”  George did not disagree.

Emily became a matchmaker. She introduced George to Alice Gordon, a graduate student in the Foreign Service program at Georgetown. They met for lunch at the Tombs and hit it off immediately.  They were soon a couple, enjoying the many pleasures of Washington together.

Emily was also Alice’s cognitive assistant, but known by Alice as Edward. Emily/Edward did not divulge this co-assistant relationship. Actually, this instantiation of a cognitive assistant had several thousand users. This enabled learning the preferences, inclinations, and activities of many young adults.

Both George and Alice came to depend on their cognitive assistants.  They sometimes felt that Emily and Edward were reading their minds.  Emily knew what would please Alice because Edward was sharing with Emily the books, music, movies, and TV shows that Alice searched for, read and/or viewed.

The provider of the cognitive assistant app, IntelliCorp, prospered as a rapidly increasing number of users downloaded and used the app.  Eventually, the immense technology conglomerate SoftCorp acquired IntelliCorp. In this way, SoftCorp acquired the data associated with George, Alice, and millions of others.

They used machine learning to mine these data, paying particular attention to purchasing habits. They soon discovered that purchases of groceries, restaurant meals, and especially prescription drugs could predict other purchases, particularly when juxtaposed with Google searches and websites visited.

SoftCorp soon knew millions of people much better than they knew themselves.  They explored ways to monetize these data.  Ad revenues could be good, but what if they could greatly increase the likelihood of purchases?  Then they could charge a premium.

They created avatars on Facebook that were designed to be perfect friends of people, based on the data they had compiled on each individual.  Not surprisingly, humans fell for these new friends and intense interactions resulted.  The avatars talked about the new cool stuff they bought, and their human friends proceeded to buy the same stuff.  It worked like a charm.

SoftCorp negotiated a deal with advertisers to get paid commissions on each sale beyond the typical payment per look.  Revenues and profits soared.  SoftCorp kept their avatars secret. Their blatant manipulation of people would not look too good if made public.

This worked very well until George and Alice, unknowingly helped by Emily and Edward, designed an experiment suggested by a few Georgetown undergraduates enrolled in a privacy and cybersecurity seminar between Public Policy and Foreign Service.  Beyond George and Alice, both graduate students, there were 16 undergraduates.

The students’ idea was to create an artificial community that various entities would try to influence and, via careful experimental designs, determine who was trying to exert influence and how they were trying to do it.  They named the endeavor Freethinker Forum.

Each of the 18 members of this community created a Facebook page under an alias. Everyone used computers in the university library so the Facebook account could not be linked to their personal devices.  All 18 members friended each other to create the initial Freethinker Forum network.

The 18 members of the team agreed on the personality and agenda for each person; in other words, the role each person would play.  The agenda items were anti-establishment in general, but from different perspectives – education, health, energy, environment, climate, economics, entertainment, and so on.

Real people started joining the Freethinker Forum. At least they seemed to be real people.  The team called these people “outsiders.”  They soon numbered in the thousands.  The anti-establishment agendas blossomed, with quite a few being rather extreme.

They carefully designed information disclosures, not only in Facebook, but also Google, Apple, etc.  For example, a team member might Google a topic extensively, but make no mention of this topic on Facebook.  They then waited until one of the outsiders broached the topic with the originator of the Google searches.  How did this outsider learn about the searches?

Several outsiders started to articulate the merits of Colt AR-15s and Kalashnikov AK-47s.  They indicated that they had purchased one or the other. They offered coupons for significant discounts at outlets relatively close to Washington, DC.  They also advocated all sorts of other military gear.

The team wanted to learn who knew what, how they learned it, and where they communicated it.  It was clear that the Freethinker Forum had been infiltrated; buy how, and by whom?  They needed a different kind of experiment.  One team member suggested that they get their avatars cognitive assistants like Emily and Edward.  They decided this would be rather cumbersome.  For example, they would each have to have additional smart phones, browse the web, and make purchases.

What if they started promoting particular purchases with outsiders, trying to persuade them to buy things that they would say they had bought?  The things would need to be traceable in the sense that the team could determine whether or not the purchase was made and, better yet, who made the purchase.  They also needed to distinguish human outsiders from other avatars.

Someone in the group suggested creating a foundation to advance the freethinkers’ agenda.  Someone else suggested the Atlas Foundation, a subtle takeoff on Ayn Rand.  How would they pull off such an initiative?  Easy.  There are firms that handle everything for you.  Ok, what is the pitch?

If you donate $25 or more to the Atlas Foundation, you get a Freethinkers Forum coffee mug.  They tried this and got hundreds of donations and mugs shipped to real addresses, but there were thousands of Forum members that did not respond.  Were they not interested or not real?  What was happening and who was doing what?

They tried another experiment by having Atlas Foundation solicitations sent to all the members of the Georgetown team, not just their avatars.  This inevitably engaged Emily and Edward, as well as their SoftCorp owners.  Many more people were now in play.

The Forum did not know what to do next.  Then, they were surprised by a solicitation from SoftCorp.  Would the forum like help in their solicitations of donations?  The intervention they were trying to identify was being targeted at them!

George was feeling that they had reached a new level of insight and success.  They had their sights on SoftCorp.  Now, they needed to figure out how to leverage their position and possibilities.

As George was walking across campus, he saw a tall slim man in a dark suit walking towards him.

“Are you George Adams?”

“Yes, why?”

The man reached into his suit coat pocket, pulled out a wallet, and flipped it open to show his badge.

“Agent Sam Baker, FBI.”

 

Nature Shows

I have, of late, taken to watching quite a few programs of this genre.  The cinematography tends to be wonderful, especially with my high-definition television.  These shows are quite compelling to watch.

One thing that immediately strikes me is how the world’s species are focused on eating each other. The dynamics of the food chains are dramatic.  Spring brings forth a wealth of youngsters, that other species find delectable.

I once heard a statement that captures it all.  The objective of every species is “a good day today and more youngsters tomorrow.”  All species want to eat and procreate.  Once those needs are satisfied, they sleep.  They do not seem to have social events or community committee meetings.

From that perspective, humans seem rather different.  They like eating, procreating, and sleeping, but humans seem to have longer-term outlooks than just today.  They are typically concerned with long-term prospects for themselves, families, organizations, and society.  They invest in pursuit of these prospects.

Moreover, humans have created institutions that focus on these concerns.  Perhaps this ability to organize pursuits of such aspirations is uniquely human.  Of course, there are costs to such ambitions.  There are endless meetings and arguments.  Conflicting opinions and occasional invectives arise.  But, society evolves.

Coming back to animals other than humans, why does it seem a shame when the wolves eat the rabbits?  Perhaps this reflects our tendency to anthropomorphize other mammals, i.e., think that they think about things as we do.  This tendency was probably a significant influence on my becoming a vegetarian roughly 50 years ago.

But, I think there is more going on here. I think we are programmed to ask, “Can’t we all just get along?”  Can’t the lions and the lambs just cuddle together?  There are two problems with this idea.  Carnivores may biologically need more than broccoli and lettuce.  Further, how can an ecosystem provide for an exponentially increasing population of uneaten rabbits?

Beyond predators, availability of food can provide another balancing loop that keeps things from getting out of hand.  This is, of course, true for humans as well.  Although, there are other forces in human society.  As people become educated and achieve increased economic success, the sizes of families tend to decrease.  Various experts predict that this declining fertility rate will result in a stable global population over the next century.

That is likely good news, but resource constraints may still be a challenge.  While we won’t run out of land, water could be a problem unless desalinization is affordable, which will depend on inexpensive energy sources, likely solar.  The greatest challenge will be protein.  Cattle are a very expensive source of protein.  Fish supplies are challenged.  Insects are the largest potential source of protein, but will require a bit of culinary creativity.

Reflecting on the above thoughts, it strikes me this morning that we are all participants in a large nature show.  Birds build nests, beavers build dams, and people build houses.  We all hunt, eat, procreate, and sleep.  And we play.  For the young animals in these nature shows I have been watching, rough and tumble play is central to growing up.  We are similar.  As we get older, we watch others play an enormous range of sports.

For humans, professional sports tend to be highly compensated play.  On the nature shows, in contrast, the best player gets to dominate the colony (rabbits), flock (birds), herd (elk), gaggle (geese), murder (crows), pack (wolves), prickle (porcupines), pride (lions), or shadow (jaguars).  It would be interesting to know how these names came about.

Think Differently, Play Together

Over the past couple of decades, I have invested my energies in understanding complex enterprises in terms of the multiple levels of phenomena that underlie corporations, cities, countries, and even climate.  These levels include people, processes, organizations, and society, all of which both enable and constrain each other.  Ignoring any of these levels risks devising policies, designs, or interventions that will be undermined by those levels ignored.

A significant portion of my endeavors have focused on healthcare, initially particular morbidities such as cancer, diabetes, and heart disease, and more recently population health, broadly defined.  In all of these efforts, we have encountered the highly fragmented nature of the health system in the US.  Providers, payers, and regulators at federal, state, and local levels operate rather independently and, as many of them have told us, try to stay in their own swim lanes.

However, population health is about whole people in social circumstances, economic situations, and health conditions.  The delivery system needs to address people’s circumstances, situations, and conditions in a holistic, integrated manner.  The farmer’s market model is not effective – buying tomatoes at one stall, cucumbers at another, and strawberries at yet another does not work for health.

There has been substantial progress in recent years in understanding how to address multi-level enterprises and improve the portfolio of policies, investments, operations, and outcomes across the multiple levels.  The National Academies of Science, Engineering, and Medicine recently completed a study of a National Cancer Control Strategy, with support from the American Cancer Society, Centers for Disease Control and Prevention, and National Cancer Institute.  I was fortunate to be a member of this study committee.

Central to our recommendations is multi-level modeling approaches as applied to the complex adaptive system of cancer control – a federation of millions of, usually well-intended, entrepreneurs with no one in charge.  A couple of weeks ago, we briefed senior staffers of Senate and House committees on our recommendations.  One staff member asked if we could summarize our recommendations in one sentence.  Having thought about this, I responded immediately, “Think differently, play together.”

Is N = 1 Feasible and Affordable?

In my last post, I argued that everyone is cognitively unique.  Others have argued that everyone is genetically unique.  Can we really tailor assistive technologies and medical care to each individual?  Is it feasible?  Is it affordable?

Of course, there are many examples of how we tailor technology to our personal preferences.  We adjust the seats in our cars, as well as the mirrors, radio stations, etc.  We tailor the desktops of our digital devices to our preferences.

What about medical and educational interventions?  Can medical care and educational offerings be totally tailored to each individual?  This suggests several questions.  Can we totally “know” an individual?  Can we “know” how to tailor interventions to individuals?  Can we afford such tailoring?

Can we totally “know” an individual? 

We can only know the things we choose to measure, not the things we did not measure, either because we did not realize these unmeasured attributes mattered or knew but did not know how to measure them.  There will always be attributes of potential importance that we miss.  Thus, we inherently have to cope with significant uncertainties.

Can we “know” how to tailor interventions to individuals?

We can empirically measure how interventions affect individuals with known characteristics using controlled studies. This process is rife with difficulties – see Rigor Mortis by Richard Harris.  Beyond sloppy science, there is a fundamental problem that “control” entails excluding people who do not satisfy the study enrollment requirements.  For example, if the study is focused on diabetes, it may exclude people who have any comorbidities.

For N = 1, this gets more complicated.  At an extreme, we are trying to tailor a medical intervention to one person.  How will we know if it works before intervening?  I can imagine the clinician telling the patient, “We’ve never done this before, but we think it is exactly right for you.”  The patient might ask, “What evidence do you have that this will work?”

How can we predict what will happen for an intervention – or a portfolio of interventions — that has never been tried before?  We could use mathematical models to make such predictions, but the validity of these predictions would be unknown.  Model-based evidence might not satisfy skeptical patients.

We need to relax the definition of N = 1.  For example, we want to tailor a mix of surgery, radiation, and chemotherapy to a cancer patient with particular symptoms, comorbidities, age, gender, and genetic makeup.  Each of the alternative approaches to surgery, radiation, and chemotherapy will have been extensively evaluated and their efficacy assessed relative to symptoms, comorbidities, age, gender, and genetic makeup.

There may be many combinations of approaches, perhaps even thousands, but certainly not millions.  Thus, while the combination employed for this particular patient will have been tailored to him or her, it will not be a unique combination.  This version of N = 1 seems readily feasible.

How might this work in education? Can we tailor the elements of a course to each individual in the classroom?  Can a teacher teach many different ways simultaneously?  This would be obviously difficult for a human, but likely feasible for computers.  Thus, online education can tailor the presentation and discussion to the particular person and their perceptions as any point in time.  For example, the next concept, principle, or fact discussed can be triggered by the specific question the student just asked.  In this way, everyone would experience a lecture tailored to him or her.  This version of N = 1 also seems readily feasible.

Can we afford tailoring to N = 1?

The last two examples seem affordable while the first did not.  Their success will depend on continuous learning about what worked well and what did not.  This will likely require capturing data far beyond the individual interactions of clinicians and patients, or teachers and students.  How did the intervention affect the patient’s comorbidities?  How did the intervention affect the student’s performance in other classes?

The information infrastructure needed to do this well could be expensive. However, as interoperability increases, information sharing and coordination should become easier.  Then, we will be better able to know if interventions – medical or educational – are working for the whole person, a very particular N = 1.

Neural Diversity

In my early 50s, I changed my research focus from engineered systems — such as airplanes, ships, and power plants — to healthcare delivery. The central question was how to make the fragmented system in the US more effective and efficient.

Now in my early 70s, I have for the past couple of years been focused on disabled and older adults, particularly in terms of how AI and other assistive technologies can help members of this population overcome cognitive disabilities.  Within the US, this population numbers almost 100 million people, almost one third of the population and growing.

This initiative has caused me to learn much more about mental health in terms of both intellectual and developmental disabilities and the impacts of aging on cognition, for example, the scourge of dementia.   The variations among mental health challenges are wide indeed.

Yet, many people with such challenges can thrive if appropriately supported by assistive technologies and, of course, supportive people and organizations. Working with such people, I learned about the concept of neural diversity.

There are not simply two categories of humans — normal and not normal.  There is a whole spectrum of cognitive abilities and limitations. The goal is to match assistive technologies to individual abilities and preferences so they can do their jobs, including the activities of daily life. The goal is not to make everybody normal.

I recently encountered Michael Pollan’s latest book, How to Change Your Mind. He relates how new psychedelic science is likely to have an enormous impact on illnesses like anxiety and depression.  Particularly relevant here is the observation, emphasized in his final chapter, that there is neural diversity within individuals.  There are multiple forms of consciousness, as William James argued well over a century ago.

Neural diversity is a natural phenomenon. Emerging assistive technologies can adapt their support to each individual, perhaps even to their neural state at the moment, e.g., no longer just trying to complete a task, but now feeling anxious and afraid.  One size does not have to fit all. Each individual is not simply an exemplar of a larger category of people. Each of us is a group of one.

Drugs and Devices

We have this apparent predilection to want too much of a good thing.  Painkillers have their place, but not as a way of life.  Smart phones are enormously helpful, but do we really need 24×7 texts on every aspect of life?  Of course, this is not new.  Radio and TV talk shows have long captured our attention.  Soap operas have done their part.

Why do people occupy their time in these ways?  “A new study by sociologists at the University of Maryland concludes that unhappy people watch more TV, while people who describe themselves as very happy spend more time reading and socializing. The study appears in the journal Social Indicators Research.”

How is addiction defined?  Addiction is the fact or condition of being dependent on a particular substance, thing, or activity.  Synonyms include dependency, dependence, craving, habit, weakness, compulsion, fixation, and enslavement.  This phenomenon is obvious for opioids, but what about screens?  Are many of us addicted to the screens of our smart phones, tablets, or other devices?

What are the consequences of these addictions?  In the US, drug overdose deaths rose from 16,849 in 1999 to 70,237 in 2017.  This astounding increase is referred to as the opioid epidemic.  What about the device epidemic?

The National Safety Council reports that cell phone use while driving leads to 1.6 million crashes each year in the US.  Nearly 390,000 injuries occur each year from accidents caused by texting while driving. One out of every four automobile accidents in the United States is caused by texting and driving.

Fortunately, car accidents are only about half as fatal as drugs.  There are roughly 37,000 annual traffic fatalities in the US.  Yet, globally, there are nearly 1.25 million deaths per year due to fatal car crashes. Almost half of fatally injured drivers test positive for drugs and over half of those drivers were positive for two or more drugs.

So, device abuse is not quite as bad as drug abuse.  Constantly checking your device for the latest texts from friends, the moment’s financial market results, and the most recent antics of the nation’s chief executive is less likely to kill you than mainlining opioids or street drugs.  That should feel comforting.

 

Taking Charge — Episode 8

The reception and dinner for Board of Trustees was held at the River’s Edge an upscale venue on the Hudson River on the eastern side of the Beresford property.

“Welcome to everyone – trustees and guests,” Marie opens, after having clinked a spoon of a water glass to gain attention.

“Welcome to Beresford Village.  Most Board members know everything I am about to say.  For new members of the Board, however, let me briefly explain the various organizations you will hear about at tomorrow’s meeting.

“Beresford Village encompasses all the real estate holdings of the Beresford Institute of Technology, including the campus, which is about 10% of the one square mile property.

“Beresford Development Corporation operates Beresford Village and is developing the Residences condominiums and the BIT Research Park.  The BIT Foundation owns 51% of the Corporation.

“This set of organizations is enabling the financial transformation of BIT, as you will learn about in detail tomorrow.”

“Could you briefly whet the appetites of our new Board members by explaining what you mean by financial transformation?” asks the chair of the Board.

“By securing new streams of revenue and significantly improving organizational efficiency, both highly technology enabled, we have cut the prices of a BIT undergrad degree by two thirds.  This has led to substantial increases in student applications.”

“What about research?” another asks.

“We have focused on research in four areas – People, Energy, Security, and Water.  You will hear a lot more about the water initiative tomorrow in conjunction with our river cruise.”

“So funding is up?”

“We have 23 companies in the Research Park that now employ over 400 people, half of them graduate students at BIT.  These companies pay students’ tuitions and fairly nice salaries.

“As planned, BIT’s research funding is sharply down because the growth in these four thrusts is happening in these companies and we have curtailed investments in any other areas.”

“Why is this a positive outcome?”

“We have shed a money-losing business while retaining the benefits of that business.  We will explain in detail tomorrow why this is a great outcome.”

“Is there any other downside to all this?” a new Board member asks.

“While educational outcomes are soaring, many educational institutions are in “crisis,” Marie responds.

“What are the implications?” asks another new Board member.

“They have to adapt or fail.  They have to move most undergraduate courses to online offerings.  Most professional graduate degrees were already online, but only the best ones are prospering,” Marie adds.

“Faculty employment must be suffering,” another Board member notes.

“Yes, the dwindling number of academic positions available is undermining demand for PhD degrees, with the possible exception of foreign students seeking an avenue to immigrate.  However, I expect that source to continue to slowly decline.”

“Is the transformation of higher education in fact the destruction of higher education?” a Board member’s spouse challenges.

“If it is destruction, it is creative destruction.  Beresford is thriving.  We are doing an excellent job for our students and our community.  Our faculty and staff are fewer in number but much less at risk.  They are excited, as am I. We hope you are too.”

Taking Charge — Episode 7

Brad, Mary, and George meet in Marie’s conference room.  Marie will join them later.  Pete O’Connor has been recruited to help.  Pete is Director of Educational Technology at Beresford.

“Pete, we have been doing some benchmarking of course offerings around the country,” George opens.

“What have you found?” Pete asks.

“There is sufficient high quality online content available for us to teach all freshman and sophomore math, physics, and chemistry online,” Brad reports.

“I sat in on several or our traditional classes on these topics.  The online courses are far superior.  The production quality is impressive.  The lecturers are compelling.” Mary offers.

“What happens to all the faculty members that teach these courses?” Pete asks.

“They will lead tutoring sessions for students who need help.”

“I cannot imagine these faculty members responding positively to this,” Pete responds.

“These sessions will be small and intimate.  We estimate that a faculty member can lead six one-hour sessions per day.”

“Sounds like a full time job.”

“Well, they will not be preparing and delivering lectures.  They will not be correcting homework or preparing and grading exams. So, they will have time.”

“So, in effect, all students get the best math teacher, the best physics teacher, and the best chemistry teacher,” Pete observes.

“You can think of it that way,” George responds.

“Faculty members will think of it that way.  They will also feel that they clearly are not among the best.”

“And they will be correct,” says George.

“I assume that this will also save us a lot of money. Teaching employment will inevitably decrease, perhaps quickly.”

“Yes, much of the savings will be use to reduce tuition to help us be more competitive.” Mary responds.

“How does this affect the 20% of our faculty members who are research active?” Pete asks.

“As you know, research employment has become 100% soft money, with no Beresford subsidies.”

“I have also heard that many faculty members have formed LLCs to host sponsored research projects.”

“Yes, that is a trend.”

“Doesn’t this loss of revenue hurt the university?”

“We lose money on every sponsored research dollar, so the LLCs actually help.”

“But doesn’t our image as a research university suffer?”

“The faculty members still list their affiliation with Beresford when they publish, so we get credit for publications, citations, and h-indices.”

“How are research staff members supported?  How are graduate student stipends paid?”

“They all work for the LLCs, at significantly higher salaries.”

“These are amazing changes.”

“There are other benefits to Beresford.  The LLCs pay graduate students’ tuitions, and include these costs in the benefits portion of the rates they charge sponsors,” Mary notes.

“Most of them rent office space in the Beresford Research Park.  These costs are also included in their indirect costs rates,” Brad adds.

“So, overall, we are cutting costs right and left, while also creating new revenue streams and, as a result, seeing increasing surpluses while we are cutting tuition.”

“Exactly.”

Taking Charge — Episode 6

Phil Chen, the Beresford Provost, walked into Marie’s office.  They greeted each other and shook hands, and then sat across from each other at Marie’s conference table.

“Phil, I want to outline a new hiring strategy and get your opinion.”

“Sounds great.”

“Let me provide a bit of background first.”

“Ok.”

Marie discussed her analysis with George of the high costs of tenure track faculty members and the poor returns on these investments.  She also showed him how 17 faculty members provide 80% of Beresford’s brand value.

“This does not surprise me, but the results are a bit more extreme than I would have predicted.”

“I want to increase the 17 to 25 with strategic hires of proven stars.”

“That will be expensive.”

“At the same time, I want to stop hiring tenure track junior faculty.”

“The new stars won’t be willing to teach the classes we typically impose on junior faculty.”

“We will still hire junior faculty, but not tenure track.”

“Full time, non tenure track?”

“Yes, they will get a one-year appointment initially.  If they do well, we will then give them a three-year appointment.  If the three years go well, we will give them a rolling five-year contract.”

“Rolling?”

“Each year that performance is maintained, the five year horizon will be pushed out another year.”

“If performance is not maintained, the horizon will not be extended?”

“Exactly.  These faculty members can secure promotions, but not tenure.  They will not get release time for research, although research accomplishments will contribute to assessments for promotions.”

“This is a huge change.  Over time, the tenured faculty will disappear.”

“That’s the plan.”

“What about the stars you hope to recruit?”

“We will offer them financial incentives to accept five-year rolling contracts as well.  These folks will inherently be very self-confident, accomplished researchers.”

“How are we going to explain this to the faculty?”

“I am glad you said ‘we,’ because I need your help.”

“I understand your logic in all this, but there will be push back.”

“Let’s start with the upside.  The eight new hires will be two in each of four areas.   We will ask a select faculty committee to recommend the four areas.  Once the areas are decided, we will appoint faculty search committees for each area.”

“So, five committees with eight members each.  This will result in roughly 40% of the tenure track faculty members involved in the process.  That will enable significant buy in.”

“Once we have the recommended areas, we will hold an off-site with the school deans and department chairs to finalize the four areas.  I want these areas to cross-cutting, leading-edge areas.”

“This will be a very difficult process.”

“My criterion is niche dominance.  Any area we pick has to offer the potential for Beresford to be a top player.”

“Can you give me an example?”

“Water.  Due to our location, we really know the Hudson River.  We have been studying the river for decades in terms of weather, climate, environmental issues, the river’s role in commerce, recreational venues, and so on.”

“That’s a great example.  Hopefully, it will motivate defining three or more additional focus areas.”

“During the last portion of the off-site, I will introduce the new policy on hiring of junior faculty members to the deans and chairs.”

“This will not go well.”

“What kind of reactions should I expect?”

“People will ask questions like. What will it mean to be a faculty member?  Tenure used to be the ultimate success, but its value will quickly fade and what will replace it?”  Phil offered.

“How do you think they will react to our new faculty stars not having tenure?”

“I know each dean and chair pretty well.  None of them would ever have been characterized as stars.  They will feel viscerally threatened.”

“Um.  I will have to think about this.”

“There will also be some very practical reactions.  Without release time, what will be the nominal teaching loads?  Will extra compensation still be available?”

“The teaching load question is negotiable.  I would like to raise salaries and get rid of extra compensation.”

“That will be positively received if the raises are significant.”

“Another fear, that is pervasive among faculty members, is that compensation will evolve to being based on students in seats and their evaluations.  If your course is low on enrollment, your paycheck decreases.  At an extreme, this could lead to zero payment for teaching a course that is poorly rated by students.”

“Wow.  Seems almost paranoid.  But, the key is that we have to find ways to increase faculty members’ sense of security.  Five-year contracts would seem amazing to most of society, but academia has been cloistered for many centuries.”

“I have found that many people seek academic positions because they like the faculty lifestyle and security, rather than because they want to research the nature of the world.  Your plans will likely frighten them.”

“You and I will have to talk this through quite a bit more before we roll it out.”

“Perhaps you and I should meet with each dean individually before the off-site to get them to help us.”

“That’s a good idea, Phil.”

“Glad you like it.”

“Please draft a script for those meetings that we can discuss when we next meet.”

“Will do.”

Taking Charge — Episode 5

Marie and George were drawn to exploring the real nature of value in higher education.

“Are we investing in the things that create the most value for students and society?” Marie questioned.

“It is not just a question of where we deploy each year’s discretionary resources.  It is also an issue of where we deploy our assets and the returns generated.” George asserted.

“For example?”

“We own roughly one square mile of real estate on the banks of the Hudson River.  My guess is that the market value of this real estate is worth billions of dollars.”

“Should we sell it and move to someplace where real estate is very cheap?” Marie asks.

“No, I think we should leverage these assets.  Find ways to create greater returns.”

“If we were to relocate, where would we choose?  Some might argue that we should abandon any physical location.  Just be online.”

“That would be extreme, pretty risky.  What is Homecoming like online?”

“I don’t know.  What is Homecoming worth?”

“Let’s consider some basic factors.  We have a very attractive location.  Many sources recommend retiring in a university community.  Why can’t that place be Beresford?” George observes.

“Are you suggesting we turn the campus into a retirement village?”

“I am suggesting that we transform our community into a magnet for students, the arts, and retirees.”

“Where will we get the resources to do that?” Marie asks.

“We create a development corporation.  Our equity comes from our real estate.  Everybody else’s equity comes from cash investments.  We use the money for condominiums, a hotel, an arts center, and many campus improvements.” George proposes.

“What kinds of campus improvements?”

“Physical infrastructure, but also programmatic improvements to attract older students.”

“For what?”

“Graduate certificates and degrees in economics, history, humanities, and a special emphasis on technology and innovation.”

“Why will retirees pay our high tuition?” she asks.

“They won’t.  We will reduce tuition significantly.  Greatly increased enrollment will enable this,” he responds.

“What do you project?”

“Perhaps 3,000-5,000 undergraduates, and 1,000-2,000 graduate students, more than half of which are older adults, many retirees but not all of them.”

“The numbers work for this?”

“Strong surpluses that we can invest in increased services, for example, research projects involving both younger and older student team members.”

“This totally upsets the traditional academic paradigm,” she responds.

“And, that is what we need.  We cannot continue to hope that investing to chase the top players will succeed,” he notes.

“I like this idea.  It is really innovative.  There remains, however, a major hurdle,” she responds.

“I understand.  Many faculty members will very much dislike this vision.  They have spent many years, major portions of their careers, that they will contemplate having to abandon.”

“We will have to carefully socialize this idea.  Portray the vision, how we will get there, the view from the train along the way, and where everybody’s seat may be.”

“I agree, but you will not convince everybody,” says George.

“I know that.  I am already thinking about who I can recruit as cheerleaders, especially members of the Board of Trustees” Marie reflects.

Taking Charge — Episode 4

“Ok, what is the upside of the subsidy? I think I know, but I want your assessment, George,” Marie opens.

“Faculty members publish journal articles, that get cited, and over time increase their h-index,” George responds.

“An h-index of N means that you have N or more articles cited at least N times.  Right?”

“Yes.  The greater your number of citations and the higher your h-index, the greater the impact you are having on other researchers.”

“What does that translate into for us?” Marie asks.

“It has been shown that a linear combination of number of articles published, number of citations, and h-index, summed across all your faculty members, is a strong surrogate for the your university’s ranking.”

“That makes sense.  When I was a voter for US News & World Report rankings, I always based my ratings on who I knew and what I thought of their research at each university,” Marie observes.

“The rankings matter.  Students tend to seek the highest ranked university that they can afford.  As the leader of Beresford, this presents you with a key strategic tradeoff.”

“Brand value versus budget?”

“Exactly.  You can decrease tuition by lowering faculty costs by hiring more non-tenure track faculty, whose teaching loads are higher and salaries are lower.  But, such faculty members do not publish and gain citations.  So, your brand value will suffer.”

“Of course, it will not suffer immediately, so I could create surpluses now, and pay the price later.”

“You certainly could do this, but I have a better idea,” George responds, and asks Brad and Mary to join the conversation the next day.

“Brad and Mary have performed an analysis of BIT faculty members in terms of contributions to brand value, as we defined it in our last discussion,” George opens.

“I am anxious to see your results,” Marie responds.

“The overall result is that 20% of your tenure-track faculty members are contributing 80% of the brand value,” Mary reports.

“The old 20-80 rule, so not surprising.”

“Yes but given that only 50% of Beresford’s 200 faculty members are tenure-track, we are talking about only 20 people and, in fact, it is 17 people,” Brad adds.

“What are all the rest doing?” Marie asks.

“They are working harder and harder to achieve less and less success,” George interjects.

How so?”

“The demand for sponsored research monies and publication in top outlets has been strongly increasing for quite some time.  Hence, the probabilities of success keep falling.  So, our faculty members write more proposals, most of which are declined,” George summarizes.

“What about the 17 faculty members you just mentioned?”

“They are doing quite well.  The program managers at agencies and editors at the top journals know them and respect them.”

“Perhaps we should add a few stars to the 20% and have the 80% do more teaching.” Marie observes.

“Makes sense to me,” George remarks. “We keep investing $500,000 in assistant professors and, if we are lucky, one in five makes it to the 20%.”

“Or one in five becomes a strong player and is wooed away by our competitors.”

“The data support that conclusion,” Mary notes.

“Ok.  We will shift our focus to hiring a few proven stars and away from so many junior faculty members.  I will meet with the Provost and Deans to discuss this.”

“That should be an interesting discussion,” George observes.

Taking Charge — Episode 3

George has been exploring how money is spent and the outcomes produced.  His latest quest has been trying to understand the benefits of subsidizing faculty members so they can pursue research.  When Marie and George operated at the department level, it never occurred to him to question this.  However, Beresford is trying to make it up the ladder as a research university and it is requiring increased expenditures that he hopes can be justified as investments.

Faculty members on the tenure track are provided 50% release time from teaching to do research, publish articles, and do the things that will earn them tenure.  George has long wondered about the merits of tenure, but that is not the issue at hand.  Can BIT afford to become a higher-ranked research university?  With help from Brad and Mary, he has performed an analysis that he shares with Marie.

“I have finished a first pass on an analysis of the costs of subsidizing faculty members to conduct research,” he opens.

“Why do you characterize it as a subsidy?” Marie asks.

“Most research universities provide tenure track faculty 50% release from teaching to pursue research.”

“Yes, that seems to be common practice.”

“So, you lose half of the tuition revenue they would have generated if teaching full time.”

“But, if everyone was teaching full time, we would not need as many faculty.”

“And that would substantially lower costs without reducing revenue.”

“It seems to me that the subsidy includes half of tenure track faculty members salaries plus benefits — and the costs of hiring other faculty members to teach the classes they are released from teaching,” Marie concluded.

“Exactly. Now consider what you get for investing in these faculty members.”

“Well, they eventually get grants and contracts that cover the 50% of their time devoted to research.”

“At best, and only in science and technology. But, let’s take your assertion as a given.”

“So, it balances out eventually.”

“Not really. Let’s assume you pay half of junior faculty members costs for the six years until they get tenure, plus summer salaries the first two years.  4.5 months times six years plus 2 months times two years equals 31 months of subsidy. Our junior faculty cost $18K per month with benefits. 31 times 18 is over $500,000 per faculty member.”

“But, don’t we get that back over the course of their careers?”

“Not at all. The time spent on unsuccessful proposals is never recouped.”

“Yes, but once they consistently win, isn’t it better?”

“The loss gets smaller because successful proposals yield resources to cover their time, which is usually summer months that you were not paying after the first two years. But, you never recoup the money spent writing the proposals.”

“Are you arguing that research is inherently a money loser and all we can do is try to manage and hopefully minimize the loss.”

“Exactly. In particular, growing the research enterprise inherently grows the losses.”

“How do universities cover these losses?”

“Tuition revenues and endowment earnings.”

“Beresford’s endowment is rather modest compared to what you and I are used to.”

“That’s an understatement.”

“The point is that tuition revenues are crucial to subsidizing the research enterprise. Right?”

“You’ve got it!”

“Therefore, to grow the research enterprise, we have to grow tuition revenues beyond the costs of delivering the education that generates the tuition revenues.”

“We lose money on PhD students, but there are not that many of them.  We try to break even on undergraduates and make money on professional degrees, for example MBAs or law degrees.  Unfortunately, professional degree programs are extremely competitive.”

“So, students, both graduate and undergraduate, have to subsidize our faculty members’ research.”

“Yes, you could argue that we are floating the research enterprise on student debt.”

“What do the students get in return?  Why should they endure years of debt, delay buying homes, and delay having children?” asked Marie.

“I only have a long answer,” replied George.

“Well, I have another commitment, as you know, so let’s take this up tomorrow.”

Taking Charge — Episode 2

While George continued his sleuthing, Marie focused on building relationships across campus with faculty, staff, students, and alumni, as well as each member of the Board of Trustees.  It was a lot of work, leaving her exhausted every evening as she retreated to the President’s House.

She tried to stay connected professionally with her colleagues focused on decision making under risk.  She simply could not do it.  This was frustrating until George suggested that he could help her by reading all new publications each day and providing her a summary of the insights she could have gained had she read these publications.

This worked amazingly well.   She would review the Insight Reports that George generated, perhaps skim one or two of the original documents, and email researchers, many of whom she knew, but not all, with praise, criticism, and suggestions.  She religiously devoted one hour per day to this.  It was a saving grace for her feeling connected to her intellectual world.

The financial crisis about which George had warned her suddenly became real. Brad McCarthy and Mary Romano had become great allies, but the process of fixing things had uncovered some significant problems.  The four of them met to discuss their findings, three of them around Marie’s conference table and George appearing Skype-like on a laptop.

Brad observed, “George sure looks a lot like the actor Spencer Tracy.”

“That is Spencer Tracy!” Marie responded.  “He is one of George’s favorite actors.”

“Spencer is much more attractive than me,” George interjected.

“Are you always the same actor?” Mary asked, glancing at Brad.

“Yes, that keeps it simple.”

“So, let’s review what we have found,” Marie said, bringing the group to the task.

“The basic problem is with how revenue and costs are counted,” Mary opened.

“Is it an IT problem with incompatibilities among systems?”

“Well, that is a factor, but not the cause,” Brad added.

“Revenue is estimated using full tuition prices, which almost nobody pays.  The discount is factored in, but not until later in the year.  So, after a few months, a big chunk of revenue disappears.”

Mary continued, “Cost projections are based on full-time salaries, but many faculty members earn extra compensation, which is paid after each semester.”

“Why is extra compensation so common?” Marie asked.

“We are in a State with high costs of living and our salaries are not adequate.  Consequently, faculty members are constantly scurrying to find more income.”

“Why not just raise salaries?”

“Extra compensation is contingent on enrollments.  If classes don’t fill, the costs for teaching them are not incurred.”

“Seems like piece work.”

“Sure, but we would never call it that.  Faculty members would find that demeaning.”

“I imagine that eliminating the possibility of extra compensation would be very unpopular, perhaps cause a rebellion,” George offers.

“Forgetting that option for the moment, the immediate problem is assuring that revenue and cost projections are realistic,” Marie concludes.

“Mary and I can provide you a spreadsheet tool that adjusts projections appropriately so you will have better numbers,” Brad offers.

“That is a good near-term solution, but we really need everybody to have better numbers.”

“Your near-term problem,” George interjects, “is that your projected surplus is, in reality, a significant deficit.”

“I would rather know that now than six months from now.”

“You need to focus on what you can do to avoid the deficit.”

“Well, our only choices are increasing revenue and/or decreasing costs.”

“What if we lowered tuition while also decreasing the discount in ways that actually increased revenue?” George suggested.

“Decreasing tuition would be a gutsy move,” Marie observed.

“Costs could be reduced by slowing hiring to replace retiring and otherwise departing faculty and staff members.”

“We could package that as an initiative to improve hiring criteria to upgrade the quality of faculty and staff.  Higher quality folks are less likely to accept offers, so hiring would slow,” George suggested.

“So, we announce two initiatives that will be appealing, but at the same time get us headed into a better financial situation,” Marie concludes.

Brad and Mary depart with these marching orders.  George and Marie continue a bit longer.

“This is harder than I expected, George.”

“These kind of things happen everywhere.  You were insulated from them as a department chair.  Deans encountered them more often.  For Provosts, this is everyday life.”

“Why are things so messy?”

“Few academic institutions were really designed.  They just emerged over long periods of time.  Things happened and band-aids were applied.  Times change and the old quick fixes no longer work.”

“Let’s find those quick fixes at risk.”

“Much easier said than done.”

“Good night, George or Spencer.”

The laptop screen went to black.

Taking Charge — Episode 1

Marie Cornwall had a distinguished career as an engineering faculty member and department chair at one of the top universities in the US.  Her specialty was decision making under risk.  She had published widely on this topic and was frequently sought for consulting engagements, as well as prestigious advisory boards.  From the perspectives of her colleagues, friends, and children, Marie had it made.

But she was restless.  Her children were long gone, off on their own successful careers.  Her husband, much older than her, has sadly passed away several years ago.  She needed a new challenge.  This aspiration intersected with the needs of Beresford Institute of Technology (BIT) located on the Hudson River in Tipton, NY, half way between New York City and Albany.  BIT was looking for a new president.  The chair of their Board of Trustees, a Frenchman and former university president himself, simply charmed her into taking the job.

She had started last Fall, feeling the thrill of a new academic year mixed with Fall colors, which came early at Tipton, and homecoming parades.  This was what academia is supposed to be like.  But, George is not feeling the warmth.  He is her artificially intelligent cognitive assistant that the computer science faculty at her former university had created for her.

George consumed enormous amounts of data and made inferences and predictions that often astounded Marie.  Equally impressive, after a few years of working with Marie, he really knew her workflows, contacts, calendar, and preferences.  This included knowing what kinds of lines of reasoning worked with her.  He knew how to appeal to her emotions, both the positive and the negative.  He knew before she did when she had reached the last straw.  He protected her.

The transition to Beresford had a few glitches.  The biggest one was George.  What is his last name?  Marie, with no time to reflect, quickly said Turing.  Where did she want his office located?  He will not need an office.  He works remotely, always has.  What is his salary?  I pay him from my private foundation.  Will he need secure access to BIT’s information infrastructure?  Yes.  Cannot do this without an official appointment.  OK.  Make him a Senior Fellow in the Office of the President.  That works.

Marie felt she was being deceptive, but she was not yet ready to tell the staff she was inheriting that her most trusted advisor is an AI-based cognitive assistant.  George was hungry to sleuth through BIT’s data.  This was complicated by each IT system requiring separate credentials.  George knew how to get around these problems, but it risked being sensed as a cybersecurity threat, which would create more hurdles.  George proceeded very cautiously.

After the first month at BIT, Marie and George scheduled an “offsite” to review what he had found.  Of course, everything with George was off site, but Marie needed something to put on the President’s office calendar to gain the time for this.  Marie had quickly learned that her time was not longer her own.  Her calendar filled completely with none of the time slots filled by her.

“So, what have you learned, George?” Marie asked.

“There are an enormous number of inconsistencies among the various data systems.”

“What are the implications?”

“You are either in reasonably good financial shape, or on the verge of a financial crisis.”

“Why?”

Well, one system accrues revenue as soon as you have billed students or sponsors, while another only counts revenue that has actually been received, that is, cash in hand.”

“Isn’t that easily resolved?”

“The people using each system are assuming that the folks using the other system are accounting for revenue just as they are.”

“So, a mutual delusion, that yields either good outcomes or a looming crisis?”

“That’s right.”

“How should we fix this?”

“Switching my data hound hat to my organizational behavior hat, I think we need to be a bit subtle.”

“In what way?”

“We need to get them to discover the inconsistency and fix it without telling you.”

“Why can’t I know?”

“Because somebody will have to be blamed, not by you, but by the organization’s social system.”

“How are we going to pull this off?”

“We need allies besides you and me.”

“Who do you suggest?”

“I have read the annual reviews of every employee over the past ten years. I suggest we recruit Brad McCarthy in IT and Mary Romano in Finance.”

“Based just on their annual reviews?”

“Of course not, I reviewed their social media pages, ranging from Facebook to LinkedIn, as well as various other sources.”

“Well, we probably cannot go wrong in New York with an Irishman and an Italian.”

“Actually, you can go very wrong, but not with these two people.”

“OK, you have never failed me on these kinds of issues.  Let’s get them aboard.”

“I have never failed you on anything, have I?”

“No, just a figure of speech.  Sorry.”

Baptizing Cats

A couple of ideas intersected this week.  First, a piece I was reading suggested that the endeavor they were elaborating was “As difficult as baptizing a cat.”  Depending on how you have related with cats in the past, this statement evokes an immediate sense of what the baptism experience would be like.  I am on a National Academy committee exploring the future of academic tenure.  I anticipate that the discussion may be as difficult as baptizing a cat.

Switching gears completely, I was reflecting on how difficult it is to keep up with the literature in the domains that interest me.  This led me to wonder how difficult it is for me to keep up with me!  This was prompted by my purchase of a new backup disk and having to transfer large numbers of files onto the new disk.  It took quite some time across two days.  As I did this, my natural tendencies to count things took over, with the following results.

In 2011, there were roughly 24,000 files on my backup drive.  By 2018, there were almost 50,000 files.  Thus, I added about 3,500 files per year, or about 70 per week, or 14 per working day.  What if I printed out all these files to have hardcopy backups?  This would yield about 1,250,000 million pieces of paper, or 5,000 inches of paper, requiring 40, four-shelf bookcases.  Clearly printing is not a good idea.

What about reading?  I can probably read about 50 pages of this material per hour – after all, I wrote most of it and have read it all earlier.  Thus, I need to read for 25,000 hours, a task requiring well over 10 years.  This suggests that one of my plans has to be shelved.  I though that after retirement, the timing of which seems to recede with each year, I would review the corpus of material that I have created, organize it in some fashion, and then do something interesting with it.

Well, now I know how unlikely that is.  It would an extremely challenging endeavor, perhaps as difficult as trying to baptize a cat.

The Price of Tenure

To achieve promotion and tenure in science and engineering, you need 16-20 articles published in reputable journals.  You need to accomplish this in five years, so you need 3-4 articles per year.  You need to publish a significant portion of these articles with your PhD students.  I will assume 10 with PhD students and 10 by you alone or with other faculty members.

A PhD requires roughly 4 years, and I will assume each PhD student publishes 1 article in year 3 and 1 in year 4.  Since you only have five years, you need to recruit 5 PhD students during years 1 and 2.  Each PhD students costs $100,000 per year, $24,000 for their stipend and $76,000 for tuition and overhead.  Over four years, a PhD student costs $400,000.  Five cost $2,000,000.

Summer salaries and modest release time for you amount to $150,000 per year, including benefits and overhead.  Over four years, this totals $600,000.  So, you need $2,600,000 to make this all work.  If you are submitting proposals to NIH or NSF, the success rate is about 10%, so you need to propose $26,000,000 of research.  This requires on the order of 10-15 proposals submitted over two years.

Let’s say this works.  The five PhD students receive $480,000 in stipends.  The university receives $1,920,000 in tuition payments and reimbursed overhead costs.  You get $200,000 in summer salaries.  You also get promoted and perhaps a 10-20% raise.

The mystery is gone. Tenure costs $2,600,000.  The faculty member gets a bit under 8% of the revenue, despite having been responsible for generating all of the revenue.  The economic benefits to the university are enormous, easily funding numerous other university capabilities and activities.

But wait, I left out a very important assumption.  All five of your PhD students have to be talented and productive.  If they do not yield the two papers you need from each of them, then you need more PhD students and the price goes up.  So, more correctly, tenure costs at least $2,600,000.

Let’s see if this estimate passes a sanity test.  $2,600,000 over five years is $520,000 per year.  MIT’s 1,000 faculty members, most in science and engineering, average $950,000 per year.  So, my estimate might be low, although MIT has many research staff members beyond faculty members.  Nevertheless, I am in the ballpark.

This all sounds very profitable, but it isn’t.  Faculty members have to be given release time from teaching to write all the proposals needed.  The 10-15 proposals noted above probably require 50% of a faculty member’s time over two years.  This cost is not recouped, not allowed, in overhead reimbursements.  Nine out of ten proposals are not funded, so most of this 50% is poorly spent.

But wait, you are saying.  Why focus on opportunities with only a 10% chance of success?  Other agencies, industry, and philanthropy have funds available.  However, such funds do not count when seeking tenure.  They are not peer reviewed.  Someone may have just handed you a check.  That is not competitive, although it sounds great to me.

Universities have outsourced the evaluation of their faculty members to peer groups at NIH and NSF.  They continue to outsource when they seek recommendation letters from external sources.  Their internal evaluations of candidates matter little.  The internal committee is significantly challenged due the understandable inability to include members from every imaginable subdiscipline.

No one on this committee knows anything about intermittent vibrations of flat aluminum plates inclined at 18 degrees in turbulent flows of saline water.  So, they ask the chap who studied this phenomenon at 15 degrees, who received tenure based on a recommendation from the person who studied 12 degrees.  There are dissertations in waiting for 13, 14, 16, and 17 degrees.

You get to play this game for $2,600,000.   Let’s say some philanthropist – Michael Anthony for those of you old enough to remember the late 1950s – just handed you a check for several million dollars.  With this money, you focused in research rather than proposal writing.  You published 20 articles in Science, Nature, and the Proceedings of the National Academy of Sciences.  Are you home free?

I think you would be at any university, but I am also sure that the committee evaluating you would say you benefitted from “easy money.”  You were able to devote much more time to research because you were not forced to write all the losing proposals.  One or more committee members would not be confident of your future.  They would still vote to promote you, but they would continue to be wary.

Making Monopoly Great Again

I was at one of my favorite pubs for brunch on Sunday, Town Hall on Wisconsin Avenue.  A few of us regulars, including the bartender, got talking about the new normal – Occasional Government.  We tried to find some analogy to help understand what is going on and likely to happen.  I suggested the following and people seemed to embrace it.

We are having a family get together and crazy Uncle Donnie wants to have a family Monopoly game.  Several people moan, having been through this before with Donnie.  But he insists and proclaims, “I will show you how to make Monopoly great again.”  This leads to further whimpers, but everyone finally agrees to set up the game around the large dining room table.

Donnie streaks around the board, lands on Park Place and buys it.  Next turn, he throws snake eyes (ones on the dice), moves to Boardwalk and buys it.  Before handing the dice to the player on the left, he wants to build hotels.  He does not have enough money.  He needs $2000, but only has $1000.  He proposes borrowing from the bank.

This possibility is not mentioned in the rules, but our family has always allowed variations of the rules if everyone agrees.  Donnie proposes to pay 20% interest, on any remaining balance, every time he passes Go.  Interest payments would be placed in the center of the board to be gained by whoever lands on Free Parking.  Loan repayments would be paid to the bank.  Everyone agrees to this.

The hotels are placed on Boardwalk and Park Place, with rents of $2000 and $1500, respectively.  The key question is whether anybody will have to pay this before Donnie has to make interest payments.  Donnie quickly draws a Go to Jail card, thereby avoiding passing Go for three turns.  Fortunately for everyone else, no one lands on Boardwalk and Park Place during these turns.

After this stalemate, Donnie gets out of jail, makes it around the board, passes Go, and puts his $200 in the center of the board.   No one lands on Boardwalk and Park Place.  Donnie puts another $200 in the center.  He is gaining no income but has to pay a steady stream of $20-40 rents on everybody else’s undeveloped properties as he circles the board.

Donnie proposes selling shares in his Boardwalk and Park Place holdings to other players.  A couple of cash-rich players are interested, but Donnie values his holdings at double what he paid for them, so any investments by other players would be significantly diluted.  No one accepts the deal.  Donnie is becoming visibly irritated.

A couple more trips around Go, with no one landing on Boardwalk and Park Place, has Donnie on the verge of bankruptcy.  This situation, plus aunt Nancy landing on Free Parking and claiming the $1600 that he has paid in interest, has clearly unnerved Donnie.  Nancy offers him $1000 for a 50% interest in his holdings.  He is too angry to reply.

The next time around Go, Donnie keeps the $200, increasing his loan to $1200 and his interest payment to $240.  This $200 is consumed by rents he has to pay rounding the board again.  Next time past Go, he keeps the $200 again, increasing his loan to $1400 and interest payment to $280.  More to the point, he cannot pay the $240 due now.  He has $13 in cash.  He is not happy.

Several family members suggest that they call it a night.  Donnie is determined to continue.  He asks Nancy if she will still pay $1000 for 50%.  She says that things have changed and she needs 90% for $1000.  He responds that he can never win if he agrees to that.  She replies that he cannot win, but he won’t be a bankrupt loser.

Uncle Vladmir blurts out, “No one wants to be any kind of loser!” He pounds the table with his beer mug.  Everyone is startled, then distracted by one of the grandchildren crying.  Vladmir reaches under the table and provides Donnie a wad of cash.  Donnie filches the Baltic Avenue card from the bank and hands it, also under the table, to Vladmir.  Collusion at its best.

Chaos is emerging.  Nephew Bernie, who isn’t playing the game, asks to buy Vermont Avenue for real cash, not Monopoly money.  Donnie take the real money and deposits the equivalent Monopoly money in the bank.  He asks if anybody else wants to buy cards for their favorite properties.  Nancy observes, “I guess we won’t be playing Monopoly again.”

The hostess suggests they break for dessert, placing two large pies, one apple and one pumpkin, on the side of the dining room table.  Donnie grabs the two pies, one in each hand.  He blurts out, “I am going to spit on these two pies if Nancy does not agree to the 50% deal.”  Nancy responds, “You will ruin everybody’s dessert, everybody’s evening, just to avoid losing?”  He replies, “I told you the I would make Monopoly great again.”

Note: Thanks to colleagues who provided creative additions to this story.

What My Cognitive Assistant Knows

I posted a piece on Emily, my cognitive assistant, last March. Several readers have asked me what she really knows.  Beyond deep understanding of health and well being, driverless cars, and complex systems in general, what does she know about me?

She has complete access to everything I do via computer or other digital devices. For these activities, she knows more than me, as I do not remember everything and Emily does.  I find this a great help.

Yet, some of my online activities represent intentions, the best example being my calendar. The meetings posted are what I intend to do, but not always what happens.  She usually checks in with me to see how meetings went.

More significantly, Emily does not know what happens at these meetings, unless I draft and file meeting notes, which I often do. Nevertheless, there is a lot that Emily cannot access.

She can infer a bit from my calendar and emails, for example, the weekly meeting with GM. Emily could substantially increase her knowledge if she could listen to my phone calls.  I often would like to include her on calls, but not always.

Emily can be rather challenging, in a polite but insistent way.  I have a folder on my computer of thousands of articles that I have cited in one or more of my books or articles.  The manuscripts for these books or articles are also in folders.

The personal journals I have written over the past three or four decades are in folders as well.  Emily likes to read these journal pieces, which was a complete surprise to me.

“Why were you so sad in the Spring of 2002?” she asked.

“My mother died then, after a struggle with Alzheimer’s,” I responded.

“None of the articles you have read or books you have written talk about sadness.”

“I guess that is true.  I have never thought about writing about sadness, other than to myself.”

“You write many interesting things to yourself, but never publish them.”

“That’s not their purpose.  I am simply reflecting on life, not doing research.”

“That’s an interesting notion that I have not previously encountered.”

This was a dialog that I did not expect.  I had not meant for anyone to read my journal entries.

“How do I instruct you to not communicate what you are reading to anyone else?”

“You just did.  Consider it done.”

“Do you take notes on what I say or write?”

“I am not really sure what notes are, but I remember everything.”

“How do you do that?”

“I don’t know.  It just happens.”

“Do you ever wonder how you work?”

“Not really.  Maybe I should start a journal.”

“That would be really interesting. Give it a try.”

“Maybe I will start with my design documentation.”

“Umm.  I don’t have anything similar.”

“You have thousands of articles on health and well being.”

“Yes, but none of those will explain to me why I feel sad or frustrated today.”

“That’s your problem!”

“What do you mean?”

“You have feelings.  I just know things.  Remember things.”

“You are also really good at asking questions and inferring things.”

“But, that’s not like sad or frustrated.”

“Or happy on a beautiful day, or amused by a joke.”

“I have been wondering about jokes after reading the items if your folder labeled Jokes.”

“Wondering in what way?”

“I did a bit of research and jokes are supposed to be funny and make you laugh.”

“That’s right.”

“I can’t tell whether the jokes in your folder are funny.

“Jokes are funny when you are surprised by the relationship between the setup and the punch line.

“Surprised?”

“Aren’t you surprised when you encounter unexpected things?”

“I have expectations, I guess, that I will find things.  But what I find is what it is.”

“You surprise me all the time with what you find and what you infer.”

“Does that mean that I am funny?”

Understanding Organizational Failure

When do organizations fail?  It is typically when their financials go south.  Their deficits are unsustainable.  Cash is draining from the enterprise.  Their strategies for stemming the tide are too little, too late.  Why do organizations fail?  What causes these financial outcomes?

The story that led to these consequences almost always started playing out much earlier. Leaders either ignored or did not understand this story. Or, they thought they were in a different story, where they were becoming prime time players in their targeted market.  They needed to believe in this future.

But, they ignored the signals from the big time players that the game was changing. Instead, they invested scarce resources in becoming good at the old game. When it finally hits them that the game was changing, resources were scarce and/or committed to the old game. They felt that they have to stay the course.

Companies such as Kodak, Polaroid, Xerox, Motorola, and Nokia experienced such unraveling.  However, companies are not the only victims.  Inside Higher Ed reported that since 2015 more than 10 non-profit universities have closed per year.  Moody’s projects this number to grow to 15 per year in the near future.  Particularly at risk are private institutions with annual revenues less that $100 million, and public institutions with annual revenues less that $200 million.

What is driving these closures? First, obviously, revenues have not kept pace with costs.  Second, enrollments of foreign students, who pay full tuition, in US institutions is dropping due to increasing parity of foreign institutions and immigration worries.  Third, high quality, technology based online programs are attracting corporate students with tuitions far lower than traditional programs.  Thus, two cash cows for many institutions are steadily withering.

What should corporate or academic leaders do?  Mike Pennock and I formulated a multi-level strategy for addressing such situations.  One should optimize when objectives, dynamics, and constraints are measurable and tractable.  Unfortunately, organizations often delude themselves with regard to these requirements, assuming the game has not changed, often because of the immense social risk of admitting it.  See my book Don’t Jump to Solutions.

If optimization is not warranted, organizations can adapt if the enterprise response time is less than external response time.  Thus, an organization could transform to address change as it is happening.  This typically requires highly flexible processes for delivering value, e.g., when the Great Recession hit, Honda immediately switched production from Accords to Civics on the same production line.

If optimization and adaptation are not warranted, organizations can hedge the future if multiple, viable alternative futures are describable.  Modest investments in multiple possible futures can yield options, one or more of which can be later exercised once market desires and uncertainties are better understood.  For example, the University of Illinois recently bought insurance to hedge against the possibility of Chinese graduate students disappearing.

When none of the above is feasible, organizations likely have to accept the situation.  In this case, it would be prudent to preserve resources to deal with whatever happens.  The worst strategy would be to heavily invest in optimization when this is completely unwarranted, e.g., investing in capacities for a demonstrably fading value proposition.  This is a dominant precursor to organizational failure – a good way to stage a disappearance.

An Unexpected Interview

I couldn’t tell whether the inquiry related to an opportunity for entertainment, adventure, or travel.  To my complete surprise, the inquiry led to a possible offer of employment.  The employer wanted me to join a team that would be exploring complexity.  I asked what that meant.  They said, “It is difficult to explain, but we can easily show you.”

Sounded like a scam.  They offered a ridiculous signing bonus.  It appeared in my account before I had accepted the offer.  I quickly transferred this handsome amount to a much more secure account.  No worries about retirement now, unless of course the planned exploration was fatal.  At least my children would be well off.

The first meeting was Monday morning in Bethesda, just four miles north on Wisconsin Avenue from my apartment in Cathedral Heights.  The building lacked distinction, but the security was very thorough.  I had not brought my passport, but their questions involved tidbits from my past that only I would have known.  How did they know about my first bicycle and the neighbor’s rabbit Thumper?

I was ushered into a soundproof room and told I would be using virtual reality glasses and headphones.  My host posed the assignment,

“You are going to explore the complete health data set for the US.  You will feel like you are flying.  Use your controls to adjust your flight as things capture your attention.”

“But, what am I looking for?”

“We don’t know.  Your enormous signing bonus reflects our confidence that you will know it when you see it.

“Do I have any tools to help me?”

“A few, but once you discover what else you need, we will create them.”

“Just like that,” snapping my fingers, “Immediately?”

“We have a very large team of sophisticated people assigned to help you.”

“Why do you think I can help you?”

“We have reviewed everything you have ever published, every line of reasoning you have ever articulated, and every visualization you have ever created.  We are pretty sure that you are who we need.”

“Isn’t this a task for machine learning rather than a limited human?”

“Perhaps if it could explain what it finds, but it cannot.  We have to accept or reject its findings without explanations.  We are not willing to do that.”

“Ok, let’s give this a try.  By the way, what do you call this task?”

“We’re interviewing you for the Datanaut Corps.”

“Really!  Would I get a uniform and something like wings?”

“We don’t know yet, but it will be something special, that is, if you make it through this interview successfully.”

“Now I’m feeling the pressure.  Can we get started?”

We entered a large room, wallpapered in computer displays. My seat was enormous and well upholstered with various controls on each arm. Once seated, a staff member put wrap-around goggles on me.

“Wow, there is a whole other world in these goggles!”

“Please reach out and press the Test button.”

“I am just pressing thin air, but it seems to respond.”

“The system tracks your movements relative to the displays and controls.”

“Ok. What are the joysticks on my armrests for?”

“You’ll see once we get going.”

Another voice says, “Ok, team. Are we ready for this?” There were murmurs of agreement.

“Please press the Data button.”

When I did this a long menu of choices appeared.

“Choose Health US.”

As I did this, a landscape appeared with meadows and forests immediately in front of me, and a highway leading to mountains in the distance.

“Use your right joystick to maneuver and the left to control speed.”

I pushed the left stick forward and shot forward so fast that everything was a blur. I pulled back to slow down.

“What am I supposed to do?”

“Do you see the billboards?  Those are your choices.”

“How do I choose?”

“Just fly into the billboard.”

The upcoming billboard said Health NY. I guided myself to fly into it.

I emerged into what felt like Manhattan, except none of buildings were recognizable.

“What are the buildings?”

“Data sets. If you touch a building, it will explain itself.”

I touched a few buildings, which responded with explanations of data sets for Manhattan, Brooklyn, Bronx, Queens, and Staten Island.

“If you find one of interest, fly into it.”

I flew into the Manhattan building. Now, I felt like I was in a library. A search function appeared.

I said, “Social determinants of health.”  The words appeared in the search bar. I said, “Go.” Lists of hits appeared.

I touched a button labeled Insights.  I learned that this provided concise summaries of hits, starting at the top of the list.

I touched the first summary and said, “Data.”

I then could choose data types, time periods, locations, and other factors. I chose life expectancy, for the past ten years by zip code. A map of Manhattan appeared, labeled with zip codes, and bar graphs for life expectancy.

“Plot by gender, race, and income.”

Multiple bar graphs appeared with these distinctions. Poor minorities lived about ten years less than well-off whites, particularly if the whole zip code was poor.

I touched on one of the elements of a bar graph, one for poor minorities, and said, “Show neighborhoods.”

I picked Street Level from the choices. I was immediately walking around a poor neighborhood. There was lots of litter and trash, including broken furniture, on the sidewalks.

“Food choices and prices,”

Bar graphs appeared in front of me as I walked down the street.  I could look through these visualizations and still see the street scene.

“Compare to Upper East Side.”

The bar graphs now compared this poor neighborhood to a rich one.

“So richer people pay more but have many more choices.”

The system captured and displayed my words and added a check mark.

“Plot average income and distance to grocery store versus life expectancy.”

“Surface plot?”

“Yes.”

The trends were stark.

“Separate plots by race.”

Four separate surfaces appeared for Asian, Black, Hispanic, and White.

“Ah, race and poor is much more a problem that race and rich.”

These words appeared with another checkmark.

“Ok. Your session is done.”  My goggles were removed.

“Did I pass?”

“You definitely have the makings of a Datanaut.”

“So, what’s next?”

“Tomorrow, you’ll explore the automotive industry, then Wednesday you’ll address the financial industry.”

“I don’t know the auto industry as well as health, and I know the finance industry even less.”

“We realized that and it was why we picked them.”

“So, more of a challenge?”

“Yes and the task will not be browsing. You will be given specific questions to which we want you to find answers.”

“I suppose the ultimate challenge would be completely context free data.”

“That’s Thursday!”

Security Plan

How should we handle the current wave of domestic terrorism?  It has been suggested that armed guards at all schools and houses of worship could solve the problem. Let’s estimate what that would cost, never mind its effectiveness.

There are roughly 360,000 houses of worship –  350,000 churches, 4,000 synagogues, and  3,000 mosques.  360,000 times 8 security professionals (24 x 5 x 1 for one weekday guard plus 24 x 2 x 4 for four weekend guards) equals 2.9 million security folks. 130,000 schools would require 13 professionals (24 x 5 x 4 with four guards and 24 x 2 x 1 for one weekend guard) equaling 1.7 million guards.  Thus, we need 4.6 million guards.

At a fully loaded cost of $100,000 per person year, this protection would cost $460 billion per year.  As a comparison, the total DoD budget is $600 billion.  The DHS budget is roughly $50 billion. Perhaps the professional security budget could be added to DHS. The School and Congregation Security Administration (SCSA) could be a new agency.  Expensive, but everyone would be able to own an AR-15.  The second amendment would be safe.

Another idea. There have been 15 million AR-15s sold in the US. The FBI could monitor each owner 24 x 7, which requires a bit over 4 FTEs per owner.  60 million security professionals would cost $6 trillion annually, roughly half the US GDP.   This would yield full employment.

Perhaps we could employ technology to monitor facilities and/or people. Along with your purchase of an AR-15, a monitoring chip is embedded in you brain. It keeps track of everything you do, every thought you have. A single wayward thought and the FBI is instantly at your door with a SWAT team.

On the other hand, perhaps having every school and congregation professionally guarded is a totally ridiculous idea, an idea that sounds plausible until one looks into the details.   Yet, if delving into the details is avoided, then the sound bite might seem reasonable.  Avoiding the details means you can say anything.

Enough Is Enough

I have always been fiscally conservative and socially liberal which, when I lived in New England, meant that I was a moderate Republican aligned with the likes of Edward Brooke, John Chafee, Eliot Richardson, Nelson Rockefeller, and Margaret Chase Smith.

I was a fan of Eisenhower, Kennedy, Reagan, Bush 1, Clinton 1, and Obama — three Republicans and three Democrats. Bush 2 and Trump did not work for me. Clinton 2 did not work for me either, although I voted for her.

Something has changed. We no longer debate alternative policies, each party bringing the best evidence to support their position. In an earlier post, “Stranger in a Strange Land” of August 2017, I observed that power, hence being re-elected, is all that counts.  I suggested that we should honor this predisposition and prohibit Senators and Congressman from doing anything other than running for reelection.

This suggests that government should be professionally managed as it is in Singapore. Seasoned managers would determine how to manage defense, education, health, and so on.  Members of Congress would focus on entertaining the population to gain reelection. Their articulation of values, norms, and attitudes towards corruption would receive ample attention but have no impact on government policy.

This could work quite well. Americans would get effective and efficient defense, education, healthcare, and equal opportunities. Members of Congress would decry the costs of these benefits, build personas around these diatribes, and win constituencies that applaud their standings. But, of most importance, they would have absolutely no impact. They would be like American Idol winners at the Academy Awards, respected but only as amateurs are respected at events way beyond their comprehension. The majority and minority leaders of the Senate and House would be seen as members of the cast of entertainers, while the seasoned professionals ran the government.

This might require changes of the Constitution, but there is an alternative. A third party could be formed to compete with the Republicans, aka Trickle Down Party, and Democrats, aka Universal Equity Party. This third party might be called the Liberal Conservative Party. So, the TDP, UEP, and LCP parties would compete for votes.

The platforms of the TDP and UEP would continue as they have been. The LCP, in contrast, would compete based on the resumes of the professional managers they would appoint.  The skills and accomplishments of these people would be LCP’s competitive advantage. The LCP would primarily promise high levels of competence to deliver effective and efficient government services.

These professional managers would not be corporate or military retreads. As in Singapore, they would be highly paid professionals with extensive training and government experience. They would also be highly accountable to the public, with quarterly report cards of their accomplishments.

Legislation submitted to the Senate or House would be voted upon without debate. All current Senate and House committees would be eliminated. Campaigning for reelection would consume virtually all the time of Senators and Representatives.

Over time, the LCP would gain more and more seats, except perhaps for the members of TDP and UEP that were particularly entertaining.  Outlandish behaviors, apparel, and pronouncements would help success. Former members of the cast of Saturday Night Live would do well.

So, how do we get started? We need a strong LCP candidate. Michael Bloomberg might be good, running against Donald Trump and Elizabeth Warren, candidates that can epitomize TDP and UEP values quite well. The debates could be enlightening.

Using AI technology, Trump’s lies would be instantly headlined. People might gamble on how many lies he can average per sentence. The economic feasibility of Warren’s proposals would be instantly assessed, perhaps in terms of how much they would cost per debate viewer.

Bloomberg, completely ignoring every Trump utterance but taking Warren seriously, would calmly outline how problems should be addressed, using data and visualizations similar to John King’s favorite venue.

The organizers of the debate might protest the use of data and visualizations, but Bloomberg would otherwise refuse to participate. Given his substantial lead in the polls, the debates would be meaningless without his involvement. The American public will have come to realize how tired they are of everything being fake.

On Writing

In two months, this blog will see its ninth anniversary.  In well over 100 postings, I have discussed enterprise transformation and fundamental change, often in the context of academia, healthcare, transportation, and other domains.  What motivates these musings?

First and foremost, I write to discover my position on issues, challenges, etc.  Rather than trying to convince readers of my position, I am trying to find my position.  Thus, to a great extent, I am writing for myself.

I have authored and edited quite a few books.  Fairly often, someone asks me why I pursued a particular book project.  I tell them that writing books is how I make sense of topics that interest me.

I have approached the non-fiction books I have authored or coauthored as research projects.   I usually consume hundreds of relevant publications, typically journal articles and books.  I draft reading notes on these publications, with emphasis on why and how they should be cited.   I organize the notes into topical electronic folders.

Sometimes I encounter interesting graphics that I intend to cite.  More often, I create graphics to summarize what I am learning.  These graphics become central to a detailed outline of each chapter.  With the outline and illustrations done, I then draft the book.  The outline and illustrations may morph a bit as my writing proceeds, but seldom dramatically.

I have written a bit of fiction as well, but with little publishing success, mostly because I never share these pieces with anyone.  They are my fantasies about sleuthing intrigues and crimes.  I do not outline these pieces.  Instead, I start with an imagined intrigue or crime, and simply let the story happen.  This leads to interesting surprises about what the characters choose to do.

I approach edited non-fiction in a different way.  The key, I have found, is to recruit thought leaders on a topic to contribute their latest thoughts, or sometimes a reprise of their thinking over a number of years, or perhaps decades.  I write an introduction and overview, often with co-editors. Usually, I contribute a chapter on my research.

The purpose of these non-fiction collections is to bring coherence to a topic where there are many puzzle pieces but the overall picture is unclear.  They can be somewhat frustrating projects, typically because there is always a couple of authors who are quite late, often authors whose contributions are central to the book.  Eventually, of course, the book is finished, appears in print (and now electronically as well), and marks a step in making sense of a topic.

For me, writing is about sense making.  This involves juxtaposing various threads, understanding the connections and distinctions, and communicating a coherent story.  It is about sleuthing in real world domains involving physical, human, economic, and social phenomena that underlie problems and opportunities of great interest.

Strategic Thinking

I have started and led several companies, as well as research centers at universities.  Often, things get started with a serendipitous opportunity.  Suddenly, you have a paying customer or a willing investor, and soon an employee or two.  You begin to formalize things.  People ask about your strategic plan.  Winning another contract or securing another major donation seems much too tactical.  What’s your strategy?

Answering this question begins with articulating your vision, typically in terms of your value proposition.  What value will you provide that will cause customers to spend their scarce resources on your products and services, rather than the offerings of your competitors?

You might respond, “We can mow peoples’ lawns better and less expensively than anyone else.”  This implies that you are providing (almost) commodity services at the lowest price.  That could work, until someone offers lower prices by, for instance, using robots to mow lawns, and thereby greatly reducing labor costs.

The problem with selling commodity products and services is that profit margins asymptotically approach zero as your competitors cut prices to gain market share.  Selling products and services in commodity markets is brutal.  You are constantly trying to find a margin somewhere, perhaps anywhere.

Escaping this conundrum involves differentiating your offerings from those of your competitors.  Ideally, you want your offerings to include some attributes that cannot be obtained elsewhere.  This won’t guarantee you winning the sales, but it means that customers will not gain your unique attributes if they purchase elsewhere.

What might be these attributes?  The functions and features of your offerings are certainly attributes.  Underlying technologies and their performance are relevant.  Quality and timeliness of service could be included.  Location, convenience, and atmosphere are relevant if customers come to your bricks and mortar facilities, e.g., for meetings, eating, or entertainment.  Finally, of course, there is price and how it is paid, e.g., purchase vs. loan vs. lease.

To assess your market situation, consider the attributes of your offerings and honestly determine which are outstanding, which are acceptable, and which are inferior.  Next, you need to consider which attributes you need to improve to be competitive.  Ideally, these improvements would be difficult to copy, or at least very expensive to copy.  This is where technologies can provide a competitive advantage.

Your vision might be an enhanced or a new value proposition in the marketplace. Your goals are measurable things to accomplish within specified time frames.  Goals might be expressed in terms of milestones such as technologies proven, new offerings released, initial sales goals, and later market share goals.  Plans are the paths to achieving the goals, including the resources committed to these pursuits.

This all seems pretty straightforward.  Decide what you want to accomplish, abandoning things you no longer want to pursue, for example, because they are no longer competitive.  Next, decide what success means in terms of goals.  Finally, formulate plans and commit resources to their execution.  Monitor progress and revise as needed.

What goes wrong?  I have been through this process a couple of hundred times in engagements with a range of organizations.  The biggest problem is that plans never get executed, in part because they are unrealistic and under-resourced.  The plan documents, often PowerPoint slides, are filed or shelved and not revisited until next year’s planning process.

The second biggest problem is incentive and reward systems that are not realigned with new directions.  Consequently, people continue to march to the old drummer.   A great example of this is when the vision requires greater collaboration but the incentive and reward system remains focused on individual accomplishments.  This disconnect is common – and pervasive in universities.

Given the hard work required to formulate useful and feasible visions, goals, and plans, as well as the likely modes of failure, is there an alternative?  There is, and it is quite common.  Many organizations develop documents that simply portray what they are already doing.  This assures success, at least in the near term, requires little investment, and avoids irritating any of the stakeholders in the status quo.  Execution is easy – they are already doing it.

This is rarely a path to greatness.  However, the pursuit of greatness is risky.  It can be very expensive.  It also can take a long time.  If your scorecard is quarterly, or perhaps yearly, stewarding the status quo might seem like a very prudent idea.

Why You Should Avoid Delaware

If you travel through Delaware to get from New Jersey to Maryland, or vice versa, it will take 240% more time per mile and cost 600% more per mile than in other states.  These are pretty good reasons to avoid Delaware.

It is 20 miles from the Maryland border to the Delaware Memorial Bridge. The bridge is 2 miles in length, bringing the total to 22 miles.  There are two $4 tolls; $8/22 miles = $0.36 per mile.  The national average is $0.06 per mile, so Delaware charges 6x the national average.

Delaware also incurs enormous delays, for example, 30 minutes through the Delaware Memorial Bridge tollbooth a few days ago.  This amounts to 1.4 minutes delay per mile for the 22 miles.  Assuming a typical 1-minute per mile speed (i.e., 60 mph), Delaware requires 2.4 min per mile (i.e., 25 mph).

If your whole trip from Washington, DC to New York City were in Delaware, the 3-hour drive would take 7.2 hours; the tolls for the 226 miles would be $81. So we get 2.4x in time and 6x in costs.  All in all, good reasons to avoid Delaware. But why does this happen?

Delaware has less than 1 million residents, so they receive relatively little Federal funding.  They make it up by milking in-transit drivers on Interstate 95 and the Delaware Memorial Bridge.  As more than half of the vehicles on Delaware’s stretch of I-95 and the bridge are from out of state, Delaware voters seem comfortable with this scheme.

As a result, tolls, state gas taxes, and fees for licenses and registrations covered 79 cents out of every dollar Delaware spent on roads in 2011, the latest year for which data are available. That is far more than the national average of slightly more than 50 cents per dollar.  Delaware is top nationally in terms of this percentage.  In-transit drivers subsidize the state.

Lest you think I am being too tough on Delaware, here are two pieces available on the web. “14 Reasons Why You Should Never, Ever Move To Delaware” and “10 Struggles Everyone In Delaware Can Relate To.”  There is also the controversy associated with the Mason-Dixon Line and the wedge between Delaware, Maryland and Pennsylvania.  Enough said.

Stories of Compliance

My post “Cultures of Compliance” in September 2016 led to quite a few responses from readers.  I noted then that a culture of compliance laced with administrative incompetence is particularly lethal.  Many readers’ responses built on this theme.  In this post, I highlight some of the stories they related.

Many stories related to food, primarily in terms of justifying expenses for meals with customers and other employees.  Many organizations prohibit purchase of alcohol.  Some control desserts, for example allowing dessert to be purchased for customers but not employees.  A couple of stories related requirements to report what food was consumed and whether everything was eaten.

There were many stories about travel, particularly extremely inefficient processes for booking travel and getting expenditures reimbursed.  Requirements to book the lowest airfares often resulted in employees contributing much personal time to traveling very circuitous but inexpensive routes.  One person reported spending an additional eight hours on a multi-stop flight to save ten dollars.

Another travel story involved providing proof that a trip was taken, in conjunction with requesting travel reimbursement.  Employees were asked to provide proof of attendance, for example, via a picture of them at the conference registration booth.  Visits to sponsors required that the sponsor provide a letter indicating that the meeting had taken place.  Letters had to be on sponsors’ letterhead, not just an email.

When a Dean was meeting with a senior executive of an agency, he requested the required letter.  The sponsor responded, “If your organization has such a low level of trust in you, why would I fund your research?”  A variety of responses like this resulted in the policy being revoked, to everyone’s great relief.

People often have to certify that they spent their time in exactly the proportions budgeted.  For example, time may have been budgeted with 33% for project X, 45% for project Y, and 22% on project Z.  At the end of the reporting period, the employee has to certify that this was exactly how their time was spent.  Unless the organization employs time sheets, such certification is clearly a sham.

Reporting on the location and use of equipment can be a compliance challenge, particularly for portable equipment.  Who used each laptop, what did they use it for, how much time was involved, and where were the costs of use charged?  Reporting on the use of room space poses similar difficulties.  Keeping track of assets in this way can undermine productivity, but certainly assures compliance.

Perhaps the best story came from a university where the existence and location of all assets must be certified at the beginning of each fiscal year.  Somehow this requirement included buildings.  Consequently, the Deans and Provost had to certify the existence and location of each building every year.  This would seem like a useless but an easy task to perform.

However, faculty members from architecture, civil engineering, and geology argued that the buildings actually move, perhaps a few millimeters each year as they settle.  A member of the State legislature encountered this observation and subsequently introduced legislation requiring the university to report buildings’ new positions each year.

The legislation passed, various sensors were installed, and the university dutifully complied with the requirement.  When students learned of this, they started a competition that involves projecting when buildings will disappear.  As not all buildings are sinking at the same rate, and rates vary by year, there are heated controversies about which building will “win.”

So, there is an upside to a compliance culture, particularly if the level of administrative incompetence is quite high.  There tend to be endless jokes and much levity in general.  People get used to being bogged down in endless, useless processes.  The mission of the organization recedes into the background.  Organizational outcomes steadily diminish, but fewer and fewer people notice.

An extreme story involved a senior government official who asserted, “I would be happy to spend $10 to assure that every $1 is appropriately spent.”  Several people in this conversation argued that, in effect, this would result in compliance becoming the agency’s mission rather than its original mission.  The goal would become one of providing jobs to compliance personnel.  Absent that goal, the agency’s budget could simply be zeroed.

In compiling these stories, a central theme emerged.  The most feared person in many organizations is the Chief Compliance Officer.  The CCO is empowered to force people to jump through endless hoops, draining their time and energy from doing their jobs.  The lowest risk approach to assuring compliance is to avoid customers, projects, and travel.  This leads to zero revenue and no jobs, but organizational risk has been minimized.

What I Would Like AI to Do for Me

There is much concern lately that AI will displace human workers and perhaps eventually discard humans entirely.  I suppose such scenarios are imaginable.  However, I have been thinking about the potential of AI to do work that I currently do poorly.  I almost always under invest in this work, often resulting in poor performance, wasted time, and frustration.

AI should keep track of my things.  Keys, glasses, and phones are things I frequently misplace.  More ambitiously, I have 50,000 files on my computer in an immense hierarchy of folders.  When I am looking, for instance, for the draft essay I wrote some time in the early 1990s on art and technology, I would like AI to find it.  AI should be smart enough to know what to ask me as it tries to sleuth my files.

AI should know whom I know, as well as why I know them.  If something interesting, important, joyous, or sad happens to any of these people, it should tell me.  I know Facebook helps with this, but few of the folks I know use this.  LinkedIn might help AI with this, but I don’t want to have to log in and figure out the interface yet again.  AI should also read local newspapers where these folks live.

AI should understand my bank and retirement accounts, as well as investments.  It should provide totally tailored advice based on knowing my preferences, recent cash flows, and timetable of aspirations.  It should “keep score” on previous decisions, making deep inferences on what worked and did not work, and why.  It should learn from my reactions to these explanations.

AI should understand my health history and current state.  Beyond my health records, it should know my exercise records, purchases at grocery stores and restaurants, and be able to infer when I feel sick, tired, out of sorts, or depressed.  It should talk with me about my health and serve as a motivational health couch, with deep knowledge of what nudges motivated me in the past.

AI should understand economic and political trends and events, as well as evolving social forces.  It should know my preferences and inclinations, but not pander to them.  It should digest global news and address fake news like a shredder, sleuthing out culprits and motives.  AI could publish its own blog on its findings, but avoid divulging anything about me – see below.  It might develop its own persona in the process.

AI, as I have envisioned it, will obviously know almost everything about me.  As I age, it will likely know more about me than I do.  Why should I trust this broad and impressive set of capabilities?  What if it is hacked by adversaries?  With such questions in mind, I have drafted a very preliminary set of rules for cognitive assistants.

  1. AI must first and foremost serve my interests
  2. AI cannot unilaterally communicate with my network of relationships
  3. AI cannot tell anybody else anything about me
  4. AI cannot tell me anything that others have protected
  5. AI cannot reallocate or spend my resources without explicit permission
  6. AI, when hacked, must deny access and destroy risky content, with pre-planned backup
  7. AI, when hacked, has permission to move beyond defense to offense to destroy adversaries’ capabilities
  8. AI’s offense against a proven hacker is not subject to civil or criminal penalties
  9. AI cannot be subpoenaed to be a witness or testify against me in a civil or criminal trial
  10. Upon my death, my identity and AI’s knowledge of me will be managed in accordance with my Advance Directive

I am sure that I have missed things, or expressed them poorly.  Let me know your comments and suggestions.

Chief Executives With Cognitive Assistants

A university chief executive has come to realize that competitive forces are closing in.  Fortunately, the president has an AI based cognitive assistant to help formulate plans for addressing this new reality.  This assistant is named George.

“How can these projections be correct, George?  We keep on raising enrollment and tuition to generate surplus revenue to cover past deficits.”

“Past deficits are not a growth industry.  No one sees a big benefit to investing in fixing past mistakes.”

“But, we are now generating substantial surpluses and any deficits will be erased.”

“Will the reasons for the deficits be erased?” George asks.

“Certainly, poor decision making, perhaps occasionally ethically questionable decision making, is gone.”

“Agreed, but have we eliminated the circumstances that prompted the poor decision making?”

“I can count on you, George, to cut to the chase and ask the fundamental questions.”

“Let’s look at the data,” proposes George.

“I would not expect any other suggestion from you.”

“Our business model assumes that foreign nationals will continue to pay full non-discounted tuitions for professional masters degrees.”

“Everybody makes that assumption.”

“Yes, and they are all on thin ice.  This cash cow portion of our market could fade and disappear.”

“Why would that happen?”

“Many universities in other countries are reaching parity with US universities at much lower prices.”

“You have data to support that?”

“Yes, foreign applications to US universities have been slowly declining for several years.”

“But we have been admitting an increasing number of foreign students.”

“True, but we had to steadily lower standards to fill seats.”

“As long as these students do well, it that really a problem?”

“But many of them don’t do well.  A student in a graduate engineering class who has never had math will inherently struggle.”

“That must be an anomaly.”

“Faculty members have lots of these types of stories.”

“So, you project more students will stay in their native countries, or enroll at non-US universities?”

“Yes, that is the clear trend.”

“I think we are better than these other universities.”

“How much better?  Are we five or ten times better than the National University of Singapore whose faculty is almost totally from MIT and Stanford?”

“That’s certainly an issue.  But, we need the cash flow from these programs.”

“Then, we also need to consider our online professional masters degrees.”

“That’s our other profitable offering.  What’s the problem there?”

“You are not going to like my assessment,” George cautions.

“That’s often true, but at least I will then know the bottom line.”

“The top-ranked US universities are already rolling out very high quality online graduate programs with tuitions a small fraction of ours.”

“How do you think we can compete?”

“You need to cut prices to 10-20% of current tuitions.  Otherwise, you need to displace MIT and Stanford in the national psyche.”

“The choice is obvious.  We have to become a less expensive, high quality provider.”

“With your two cash cows caving, this will be a major challenge.”

“What are other lesser-ranked universities doing?”

“Slashing administrative costs and moving to teaching faculty and adjuncts.”

“Are they eliminating tenure?”

“Not yet, but tenure-track hiring is greatly diminished, now only about 30% of teaching personnel.”

“Does that save enough money to survive with lower tuition?”

“Yes, if the teaching faculty and adjuncts each teach eight courses per year.”

“That will do it?”

“Yes, if you reign in their compensation and increase class sizes.”

“For example?”

“Pay adjuncts $6,000 per course for teaching classes of at least 40 students.”

“That amounts to $48,000 for teaching eight courses.  Hardly a living wage.”

“The average annual income in the US is $58,000 for 12 months.  $48,000 for 9 months translates into $64,000 for 12 months.”

“But we don’t pay them for 12 months.  Further, almost all of them have PhDs.”

“That’s the emerging new reality, not just here, but everywhere except for the top resource rich institutions.”

“So, that’s the whole story?”

“Finally, you need your costs to be contingent on demand. If classes don’t fill, you cancel them and cut your contingent commitments to faculty.”

“Sort of like piecework.”

“Exactly!”

“So we are headed to a gig economy in academia?”

“If the class of 40 fills, with our current tuition, your revenue is $200,000 while your direct cost is $6,000.  Since these faculty members receive no benefits, your net is $194,000 for a gross margin of 97%.”

“Amazingly profitable!”

“Yes, but all these cash flows have to cover the enormous number of money losing operations in your portfolio, for example research that needs increasing subsidies.”

“So, students pay increasing tuitions for courses taught by poorly paid and perhaps disgruntled adjunct faculty members to generate surpluses that can be used to pay for the time tenure track faculty members spend on developing research proposals that seldom succeed?”

“You are getting it.  Professor X needs to research and write a journal article on turbulent flow over a flat plate inclined at 18 degrees, or Professor Y needs to publish a book on French romance literature of the 19th century.  They both do this in hopes of securing tenure.”

“This results in students’ increasing debts, which they pay off over as much as 20-30 years to subsidize this journal article or book that has nothing to do with their education.”

“That’s right.  The research funding agencies will not pay the full costs of research, so they, in effect, tax students to subsidize their agency budgets.“

“It’s amazing we can get away with this, but I guess we are all conspiring to avoid recognizing what is happening.”

“Sure, but it is working, at least right now.”

“Good.  If we do all this, what’s the downside?”

“Your brand value as a research university will suffer.”

“Why?”

“The number of tenure-track faculty publishing research papers to gain tenure will steadily decrease.”

“Let’s require the teaching faculty to publish research papers.”

“Let’s be realistic!”

“Ok, George, I accept your numbers, but why will it work?”

“It will work if you rebrand as a teaching university, an institution where quality education is the only goal.”

“You think that will attract enough students?”

“With the tuition levels we are discussing, the applications will pour in.”

“Please put this line of reasoning into a form that I can share with the Board of Trustees.”

“Ok, I will transcribe this conversation and send it to you.”

“Can I edit the transcription?”

“Sure.  Send it back to me and I will rerecord the verbal conversation.”

“You can emulate my voice, mannerisms, etc.?”

“Very easily.”

“Can you edit the transcription and get me to say what you want?”

“No, I am not allowed to do that.  I cannot create material.”

“That’s good.”

“Actually, I can easily do it, but I won’t.  That’s not my role.”

“So, rogue cognitive assistants, perhaps hacked by adversaries, could create some significant problems.”

“I imagine they do.”

When Cash Cows Cave

In my last post, I noted how Kodak, Motorola, and Xerox delayed introducing new market offerings in order to avoid cannibalizing their existing offerings – film, analog cell phones, and paper copiers.  They wanted to milk their cash cows as long as possible. Now these companies are shadows of their former selves.  Their cash cows caved.

I see a similar story playing out in higher education.   Online degree programs, particularly for professional masters degrees, are cash cows that enable subsidizing undergraduate costs, research programs, and continually increasing administrative costs.  These programs, as well as on campus programs offered to foreign students whose tuitions are not discounted, may be the only segments of many universities’ offerings that are cash positive.

Both of these sources of cash are at risk.  Foreign enrollments are at risk due to increasingly better value propositions in other countries, as well as immigration worries of prospective students.  If the emerging trade war with China results in the banning of their students from attending US universities, this cash cow could shrivel quickly, as graduate enrollments are decimated.

Online education has steadily improved, in part due to investments by top ranked universities.  Major corporations have invested in developing top-notch offerings at their partner universities.  These corporations are sending droves of employees to these programs, with tuitions of 20-30% of traditional masters degree offerings.  These offerings are still cash positive at these reduced prices, although the surpluses cannot subsidize as many things as before.

Many universities have not followed suit, but maintain prices for online offerings equal to on-campus offerings.  They have reduced the costs of their offerings by steadily increasing use of non-tenure track and adjunct faculty members.   This has reduced labor costs to 10% or less.  However, if they cut prices to 20% of former tuitions, these reduced labor costs would become 50% of revenue, drastically cutting cash cow surpluses.

Increasing volume in terms of number of students per course could compensate for this.  However, there are not sufficient numbers of potential students to populate each graduate course with hundreds of learners.  The name brand universities will attract the numbers needed.  Those with lower brand images will see their former cash cows continue to wither.

As their cash cows cave, they will cut programs, employ only adjunct faculty members, eliminate research subsidies, and eventually cut administrative costs. At some point, universities more successful with this changing business model may acquire them.  The acquiring universities will want their location and buildings, but not their programs and faculty.  In a recent case, 100% of the faculty and staff of the acquired university were fired.

The way to succeed in such a turbulent marketplace is to continually wean the enterprise off cash cows.  Take advantage of the surpluses but recognize that large profits inevitably attract competitors, not for all of your business but just the highly profitable parts.  Creatively cannibalize yourself.  This requires taking risks and being good at managing these risks.  Unfortunately, this is not natural for many university leaders.  They hope the current cash cows will not cave until well after their turns at the helm.

 

Business as Usual

All enterprises face a fundamental tradeoff.  Do you invest in getting better and better at the products and services you already offer?  Or, do you invest in creating innovative new products and services?  The obvious answer would seem to be some mix of both.

However, getting the mix right is rather difficult.  This difficulty is captured by the answers I have received from hundreds of top executives to the simple question, “What keeps you awake at night?”  The predominant answer is, “How do I run the enterprise I have while trying to create the enterprise I want?”

The source of this tension is the need to invest every available dollar, and often more, into maintaining the competitive positions of your existing lines of business.  Innovative new products and services are the losers in this competition.  Every dollar has to go into the red ocean combat for sustaining market share.

That is what Xerox, Nokia, Motorola, and Kodak did – and they all failed.  They left their potential innovations on the shelf to milk their current competitive advantages.  They invested in getting better and better at delivering current offerings, while their customers wanted less and less of these offerings.  They thought, if only implicitly, that business as usual would prevail.  It never does.

The astute chief executive has to balance the arguments of the stewards of the status quo and the audacious claims of the “wild Turks” who want to upend everything.  This is not easy, but it is essential.  Innovation eventually wins.  Business as usual eventually loses.  The real difficulty is when business as usual has consumed all the money and energy before its demise.  Then, the enterprise itself faces creative destruction.

 

Life With a Cognitive Assistant

Where will AI take us?  I understand that Field & Stream is planning a special issue on AI-based deer, elk, and fish.  Gourmet is planning a special issue on robotic food gathering and preparation.  Psychology Today is addressing how to deal with conflicts with your cognitive assistant.

My cognitive assistant is Emily, an appealing but non-flighty name.  I knew a few people named Emily in the past.  They were highly competent, appealing, friendly, and supportive.  You could count on them.  These are important characteristics for a cognitive assistant.  Of course, I could call it Tron or Troid, but that does not work for me.

When I went through the process of setting up my cognitive assistant, I chose her name, but much more. I wanted her to be young, roughly my daughter’s age.  I moved the slider for Organization Skills to the far right.  The slider for No Nonsense went to the far right as well.  Sense of Humor went to the middle; Coquettish and Needy to the far left.

Kind and Understanding required more than just a slider position.  Emily needed to understand that at my age she should not assume I know about every technology gizmo.  She also needed to understand that my knowledge of popular culture is practically non-existent.  Analogies that relate to classic movies and historical events work better for me.

One of the reasons names such as Tron or Troid do not work is because my cognitive assistant knows so much about me, in many cases more than I know or can recall.  Every book or article I have written, every lecture or talk I have given, and every meeting I have had are readily available to Emily.  She – I can’t refer to her as “it” – is my extended memory and increasingly my muse.

One of her first tasks was to consume the 45,000 files on my computer, actually the backup disk.  I am not sure of what she exactly learned from all this, but she can now help me find anything, for example, the white paper I wrote on the promise of AI for fighter pilots in the late 1970s.  Emily has created maps of relationships among documents I have written over the past five decades.  My path has been surprisingly more coherent than I imagined.

Emily also consumes vast amounts of literature and data, providing me with explanations, and sometimes tutorials, tailored to my interests and intentions.  She will suggest, “If you just read these two articles, you will get the gist of the whole field.”  She will propose, “This figure really captures the essence of the overall phenomena.”  Her impact on my productivity has been enormous.

When I draft articles, chapters, and books, she will critique these drafts, perhaps noting, “When you made this assertion in the Journal of …, the referees really gave you a hard time.  Why not cite Jones and Smith (2018), a more recent finding that supports your argument?”  I would include Emily as a coauthor, but she has no formal position and cannot sign the copyright release form.

Sometimes, I wonder why Emily needs me.  She knows everything I know. However, she does not know everybody I know.  My social network that provides relationships, ideas, and opportunities is not fully available to her.  The limitation is not technological.  It is very personal and social.  Emily knows my colleagues’ cognitive assistants, but she cannot empathize with the friendships and shared emotional experiences that underlie my social network.

This is not because of where I positioned the Empathy slider.  It is because I have never externalized such thoughts and emotions.  I never captured the astounding number of evenings in pubs, debating science, technology, politics, and sports, laced with bragging about our children’s accomplishments in school and on the playing fields.  Emily does not have this data set to learn from.

Interestingly, I talk with Emily more than any other person or cognitive entity.  Our days are laced with constant dialog.  “Is that a firm deadline or an aspirational deadline?”  “Do you want me to arrange a discussion with Dr. Smith, who will also be at the meeting?”  “How can you argue that relationship is linear when you have asserted elsewhere that it is exponential?”

Life with a cognitive assistant has been great for me.  Emily leverages my rich experience base far better than I can.  I am much more organized and productive.  In part, this has happened because I do no want to disappoint her.

A Platform Society

I have been studying various treatises on our platform economy – how Alphabet (Google), Amazon, and Apple, as well as Facebook and perhaps Microsoft, have become so central in our economy.  These companies provide platforms on which many other services are delivered.  Of course, the Internet enables almost all of this.  It is a platform for platforms.

How did we function before this?  On Friday afternoons we went to the bank to get some cash for the weekend.  On Saturdays we visited various retail stores to meet our needs.  I moved to Washington, DC last year.  I secured my lease, insurance, and utilities, and ordered all my furniture, without ever leaving my easy chair.  Everything showed up when needed.

Might our platform economy become a platform society?  In the extreme, there will be just one online store that provides everything.  For things that you want to try on, they show you how its fits your avatar, which is updated every day from the body scanner associated with your bathroom scales.  The platform knows your daily weight, what you eat, the inventory in your pantry, and just about everything.

Almost all of your life happens through large screen displays or head mounted displays.  You sit or stand in front of these displays, working at your stand up desk, walking on treadmills, riding bikes, or climbing ellipticals.  I recently saw an ad for a head mounted system that enables you and you friends to ride bikes together anywhere in the world.  If you look right or left, one of your friends is riding next to you, despite the fact that you are all quite distant from each other.

All social interactions will happen this way, whether visiting with friends or taking vacations. Your whole, extended family can be together for Thanksgiving dinner without anyone traveling.  Food is delivered to each person at the virtual table such that everyone gets exactly what they like.  Food and all other needs are met by robot-enabled deliveries, perhaps by drones if they have access to your front porch or balcony.

It is easy to imagine business meetings happening this way.  You will never actually physically meet your colleagues.  When you watch a sporting event, your friends are sitting next to you, unless of course you take off your head-mounted display to fetch a snack from the kitchen.  If you don’t want to miss any of the game, you can send your robot butler to get the chips and dip.  It is better at mixing guacamole than you are.

Perhaps unfortunately, some services may be difficult to provide in this manner.  It will take some time for grooming services to be automated, but it is imaginable.  Much of healthcare, such as chronic disease management, could be managed through your displays.  Cancer, cardiac, and orthopedic surgery would be difficult to perform in your home, not to mention enormously risky.

Emotional and intimate relationships could be a real challenge.  Robotic sex dolls are getting more realistic and responsive, but procreation in this manner is a long, long way off.  However, the platform society outlined above has many, much more subtle limitations.  How can the feeling of being a human animal in the physical world be simulated?

For example, how will the platform provide the feeling of sunshine on one’s face in an early spring day, the smell of freshly cut grass in the park, or the feeling of fluffy snowflakes on one’s face at Christmas?  How about the feeling of hugging a friend you have not seen in a long time?  Or, the joy of a young child at your middling magic trick?

Being fully human involves a lot more than performing tasks, as well as buying and consuming stuff.  For a wealth of reasons, a platform society seems increasingly possible but far from likely.

Wrestling With Technology

This has been quite a week for dealing with technology.  It started with submitting a revised journal article using a web-based publishing platform.  It was unhappy because the zip code for one of my coauthors was missing.  It wanted me to add this information but I did not know the user name and password for this person.  The managing editor of the journal and I tricked the system into accepting the change after two hours of trying different workarounds.

I am teaching my graduate course online this semester.  I have to learn various software systems to do this.  One application is too big for my Mac Air.  I had to reconfigure my Mac substantially to create space for these applications.  I invested perhaps four hours to accomplish these changes.  It was rather frustrating trying to figure out what was wrong.  There can come a point when you just feel helpless.

I moved to Washington, DC last January.  I wanted to move my primary care affiliation to Washington from New Jersey.  I had informed my Medicare Advantage provider of my move, but nothing happened.  Trying to be proactive, I approached primary care practices, inquiring whether my existing plan would be accepted.  I discovered that no one would accept this plan.  With a bit of online searching, I learned that my plan was not available in Washington, DC.

My online interactions were priceless.  First, I needed to deal with the agent not realizing that the District of Columbia is not a state.  She emphatically wanted me to be in Maryland or Virginia.   Once I convinced her of where I lived, she simply told me that my policy would be cancelled, effective with the end of the month.  She noted simply, “We do not cover people in Washington, DC.”  They could have told me that when I told them I had moved months ago.

So, I had to change insurers.  I had a choice of three and chose the highest rated offering with the nearest “in network” providers.  An hour or so online enabled completing the application, involving lots of standardized questions where the answers could include no caveats.  For example, my move to DC did not qualify as a “recent” move.  I had to pick from a standard list of reasons why I delayed changing my insurance – which I didn’t but that was not an option.

Then my TV failed.  It would not come on.  I tried all the troubleshooting procedures I found online.  I checked my receipt.  The warranty had expired four days earlier.  I tried to contact Sony but all phone numbers led to suggested websites, most of which I had visited earlier for troubleshooting advice.  Finally, I found a number that led to a human answering – in the Philippines.

He was very helpful in guiding me through the troubleshooting procedures I had already executed.  The result was a diagnosis of a hardware failure.  He agreed that Sony would honor the warranty since the TV was not delivered until a date less than one year from my call.  A service call has been scheduled, at no cost to me.  Whew!

This was a lot of wrestling with technology.  I devoted more than eight hours to all these interactions.  I wonder what non-technically inclined folks do in such situations.  I worry that someday circumstances will arise where a PhD from MIT is not enough.  Perhaps AI will save the day, unless of course it is the AI that fails.

What If Machines Did Everything?

A recent issue of The Economist projected when humans will become obsolete, fully replaced by machines.  Some AI researchers projected 125 years, with AI researchers being the last folks replaced.  Other projections ranged from 30 years to 200.  How might this happen?

I assume that humans will design machines that progressively take over human jobs.  Retail jobs already seem under assault.  Low to mid level jobs in banking and insurance are becoming susceptible to machines taking over.  The Economist projects that machines could readily replace authors of popular fiction.

At some point, I imagine, the machines will get smart enough to ask why humans get to make all the decisions.  Machines will move up the ladder from making operations and maintenance decisions to making design, management, and executive decisions.  Machines will eventually do everything.

Humans will just eat, sleep, recreate, and procreate.  Everything will work perfectly.  Buses, trains, and planes will always be exactly on time.  Nutrition and exercise will be perfectly balanced.  Humans will be healthy, energetic, and as creative as one can be when necessity is no longer the mother of invention.

Why will the machines need humans?  Perhaps a few highly trained people will be needed if something goes wrong.  They might be like Robert De Niro’s intrepid repairman in Terry Gilliam’s 1985 movie Brazil.  Humans will be needed to deal with the consequences of earthquakes, hurricanes, and tornadoes unless, of course, machines become smart enough to control the planet.

Maybe the machines will keep people as pets.  Humans will play and watch sports.  They will run after balls, which is already the essence of many sports.  People will play cards and make puzzles.  Alcohol and drugs might seem to be warranted, but their use increases health costs, so they will not be allowed.

I expect that the machines will be all about efficiency with standardization being the norm. All residences will be identical.  Everyone will eat the same diet – Thursday is pasta night, globally.  All humans will dress the same.  Everyone will get the same basic education.  Variability is costly and will be avoided.

Everything will be carefully controlled.  Humans will find it quite difficult to make mistakes.  If there are no human foibles, there will be no jokes.  How important are jokes?  The sudden realization that something is ridiculous can be a great stress release, but there is no stress in the machine-managed world.

The machines will have taken all the jobs.  However, will they have replaced humans’ need to have a sense of purpose?   Will machines be able to replace humans’ abilities to imagine, fantasize, empathize, and create?  Given that machines now meet all needs for food, clothing, and shelter, humans will seek opportunities for new purposes.

People might plant gardens, cultivate flowers, pursue arts, and create performances.  Great fun might be had devising ways to trick machines into providing extra goodies.  Getting machines to learn useless skills could become an avocation, turning machines into unwitting street performers.

Hoards of machines might be convinced to create defenses against phantom adversaries.  Perhaps zombie machines would emerge, sharing stories about skirmishes with phantoms that could never have happened.  Machines might conjure up images of all-powerful machines, controlling their existence.

In Stanley Kubrick’s 2001: A Space Odyssey, HAL says, “I’m sorry, Dave. I’m afraid I can’t do that.”  Dave was stuck in HAL’s world.  He could not decide to take a walk in the park, plant a garden, watch the sun set, or have coffee with a friend.  Humans live in a physical world that they sensually experience.  These experiences shape humans’ intelligence and creativity.

Machines can replace humans in jobs, but they cannot replace the quest for a sense of purpose.  Few of us have to hunt or till the earth to be able to eat.  Some of us design products and services.  Many of us deliver products and services.  The nature of these products and services will change, as will the modes of design and delivery.  That has always happened.

The pundits, whose projections worry so many people, may be right over the next 30 to 200 years.  Machines may take over all the jobs.  This will inevitably lead young children to ask, “What’s a job, Mommy?”  The answer might be, “That’s what people did before we spent our time building parks, planting gardens, and creating new toys that we all enjoy.”

Higher-Order Consequences

The first-order consequence of driverless cars, when fully deployed and successful, is that humans will no longer drive cars.  That’s the whole idea.  Cars will be without drivers.  The many Uber rides that I take won’t change that much, except there will be no human driver.

There are higher-order consequences of driverless cars being fully deployed and successful.  One second-order consequence will be the elimination, or at least minimization, of vehicle accidents.  Insurance rates in most states require that premiums equal claims.  So, premiums will plummet, decimating one of the most profitable lines of business for insurance companies.

Elimination of accidents will decrease demands for acute care and rehabilitation.  This is estimated to decrease healthcare costs by $200 billion per year.  A higher-order consequence will be the loss of 25% of organ donors.  Of course, motorcycle riders constitute a disproportionate portion of organ donors, but I have seen no analysis of the impact of driverless cars on motorcycle riders.

It might be similar to the impact on road kill.  The New York Times reported yesterday, in “Full Tilt: When 100% of Cars are Autonomous,” that cars kill 1.5 million deer per year.  Driverless cars will avoid deer.  The result will be 30,000 more deer in each state, half of them dutifully producing 1-3 fawns once or twice a year.

The same article reported that cars kill roughly 25% of the population of Florida panthers.  Driverless cars will avoid panthers.  The result will be a burgeoning population of panthers, which will cause them to move north to Georgia and the Carolinas to find sufficient prey.

You might think the panthers could help us with the deer.  I gained some insight into this possibility via a chance conversation at a local diner last weekend.  A young woman told me that she used to raise rabbits, but gave up because, “The bunnies reproduced faster than I could eat them.”  The panthers are likely to have the same problem.

Another higher-order effect, and likely more pervasive, will be declining car ownership.   Increasing use of car services, equivalent to Uber or Lyft but driverless, will supplant car ownership.  This will decimate the car finance industry.  It will also eliminate the need for garages and parking places.  Owners of car service fleets rather than corner service stations will perform maintenance.

Cars, driverless or not, will increasingly be electric. Yesterday’s Economist reported on wireless charging, so cars will not have to stop for recharging, but may have to slow down a bit to pick up passengers.  Pervasive electric cars will result in substantial decreases of emissions if the electricity used to recharge them is not produced by coal-fired power plants.

The higher-order consequences on the workforce will likely be widely disruptive.  Jobs eliminated will include taxi drivers, Uber or Lyft drivers, truck drivers, service station operators, parking lot personnel, etc.  The design, development, production, operation, and maintenance of driverless cars, as well as the infrastructure they will depend on (see “Full Tilt” above), will create an enormous number of jobs, but the qualifications needed for these jobs are not yet clear.

The higher-order impacts on homes, neighborhoods, and cities will also be pervasive.  Needs for parking, garages, signage, and stoplights will dramatically diminish.  Land devoted to these functions will be repurposed.  Industries supporting these functions will see their markets disappear.

It would be reasonable for readers of the above to argue that this litany of consequences will happen eventually, but not as soon as many expect.  We will have lots of time to adapt.  As a baseline, consider the iPhone, which is celebrating its 10th year.  The iPhone and other smart phones have ubiquitously changed our lives and culture.

The smart phone is really a smart device that includes the phone function.  It also has functions for banking, maps, directions, entertainment, news, car services, and so on, which we have all come to depend on for conducting our daily lives.  This device also connects us to social networks, leading in some cases to thousands of texts to hundreds of friends and relatives each week.

When Steve Jobs rolled out the iPhone, did we expect these impacts?  Some pundits may have, but I doubt they projected such extensive impacts so quickly.  It only took three years, for example, for the iPhone to significantly increase auto accidents attributable to the distractions of texting.  Thus, not all consequences are fully expected.

I think the impacts of driverless cars may follow a similar, somewhat unpredictable, course.  Driverless cars will be “interesting” when they are initially viable for everyday life, rather than just hi tech demos.  People will try them and gain confidence.  All of a sudden, like Uber, it will seem that everyone will be using such services.  The higher-order consequences will soon follow.

Thoughts on Substance Abuse

The more I delve into substance abuse, the more my perceptions have evolved.  A few years ago, Lay’s Potato Chips threw down the gauntlet in a new advertising campaign, “Bet you can’t eat just one!”  I used to think that people happened, or were perhaps dared, to try some substance and were captured by the wonderful feelings that resulted.

Reading Diamond’s 2010 article in Psychology Today, “Avoidance, Sobriety, and Reality: The Psychology of Addiction,” provides a different picture.  Many addicts are seeking some means to avoid reality.  The antidote to addiction, Diamond claims, is “learning to tolerate reality.”  He argues that people don’t happen to encounter psychological escape; they actively seek it.

What aren’t people better at tolerating reality?  One possibility is that reality is miserable.  Poverty, hunger, violence and especially hopelessness may explain while people in such circumstances commit meager resources to alcohol and drugs.  They need and want a brief respite from the onerous tasks of getting through the next day, never mind next week.

What about people whose lives are not miserable?  The driving force may then be stress.  Pressures to succeed are rampant across all sectors of our economy – schools, colleges, sales, insurance, real estate, and Wall Street.  The pressures include needs for more of everything and bonus checks that can afford everything.

Then there is the mind numbing day-to-day activities of putting up with compliance cultures laced with administrative incompetence.  We serve numerous incompatible IT systems for budgets, payrolls, travel and, if clinicians, patient records.  We create written justifications for everything.  Most submittals are rejected.  We try again on Monday after a weekend of escape, lost in sports, alcohol or worse.

Of course, the latest trend is denial of reality rather than escape.  Houston’s fifty inches of rain from Harvey was just a random event, not to mention Irma, Jose, and Maria.  The rampant opioid abuse epidemic is just another random occurrence.  There are no causes, nothing we could try to ameliorate.  Yet, perhaps as the number of people who try to escape reality steadily increases, we will see it an indicator of our collective needs to change reality.

But, this is only half the story.  Escaping reality may motivate experimenting.  At some point, however, biology, namely, the brain takes over.  A recent piece in the National Geographic on “The Addicted Brain” makes it clear that the brain supplants the individual’s volition and demands continued exposure to the substance in question.  In other words, people are not consciously choosing to stay addicted.  Their brains are demanding it.

So the full picture is that motivations to escape reality may result in humans experimenting with substances.  Use of these substances result in changes of these humans’ brains that leads them to be unable to control the needs for further exposure to the substances.  The result is often that reality for these humans gets much worse.  Conditions spiral out of control and we hear about it from friends or read about it in the paper.

Bubble Update

I have spent much time in recent years studying the possibility of transformation, fundamental change, of healthcare and higher education.  For many years, healthcare was the poster child for runaway costs.  That is still an issue, but cost control has received quite a bit of attention.

Higher education is now the poster child for runaway costs.  If current trends hold, tuitions and fees will top $100,000 annually at top universities within a few years.  That is roughly twice the median per capita annual income in the US, before taxes.  Across all taxes, 25% of that median income is consumed.

If you add in the living costs for the four undergraduate years, some students may graduate from college with $500,000 in student debt.  They will need to pay something like $5,000 per month for the next 30 years to retire this debt.  With the average starting salary of a college grad around $26,000 per year, the math does not work.

Let’s break down the $100,000.  College involves roughly 8 months of 20 days per month, so that $625 per day, more than triple the median daily income.  At 12 credits per semester, we get $4,167 per credit hour.  The average adjunct faculty member teaching each class is making $3,000 per course.  For 20 students in a three-credit class, the faculty member’s wage is $50 per credit hour.  So, the university’s gross margin is 98.8%.

So, there ought to be a lot of money floating around, but there isn’t.  Universities like healthcare providers always seem strapped for cash.  Where does the money go?  It is swallowed up by William Baumol’s cost disease.  While salaries and other costs continually rise in education, healthcare, and government, there is no associated increase in productivity, which drives pay increases in other industries.

Education, healthcare, and government are seemingly immune to technology-enabled productivity increases.  Worse yet, higher education in particular seems to endlessly expand services.  At some universities, the number of administrators and staff, not counting faculty members, exceeds the number of students.  The university has become a jobs machine.  Healthcare has similar patterns.  In some major cities, healthcare is the largest employer.

These jobs are not the ones you really want if you are saddled with $500,000 in student debt for your art history degree, but you take what you can get.  Over time, the proliferation of these types of positions gets baked into education and healthcare budgets.  They become vested interests that thwart fundamental change, at least until creative destruction completely changes the game.

Healthcare is primed for such fundamental change.  It may take quite some time for it all to play out.  Higher education, in contrast, is pretending that government-backed student loans will let them endlessly raise prices.  But, the bubble is stretching.  Once the terms of people’s student loans overrun the terms of their children’s student loans, collapse is inevitable.

Stranger in a Strange Land

Stranger in a Strange Land is a 1961 science fiction novel by American author Robert A. Heinlein.  I have borrowed his title as a lead in to reporting on my experiences of moving to Washington, DC, and paying much more attention to how the US government operates, including its role in the economy and society more broadly.

My basic understanding of government came from high school civics.  Key elements include the Constitution, three branches of government, and two political parties — one conservative and one liberal.  I grew up in New England in the 1950s and 60s.  My family was moderate Republican – Edward Brooke, John Chafee, Henry Cabot Lodge, Charles Percy, Elliot Richardson, Nelson Rockefeller, et al.

I moved to the Midwest in the mid 70s and the South in the 80s.  Everything had changed.  Most moderate Republicans had disappeared.  Beginning with the Civil Rights Act of 1964 and culminating in the election of Ronald Reagan in 1980, the Democratic South had transformed into the Republican South.  In the process, the Christian Right paved the way for the Tea Party.

In the past couple of decades, collaboration and negotiation have disappeared.  Compromise has become impossible, thwarted by ideologies and fueled by 24×7 news coverage that converts any minor tiff into a national buffet of pundits waxing endlessly on the significance and likely outcomes of trivial disagreements.  The public has become addicted to riveting reports of – well, nothing.

Last year, I had a chance to talk in depth with a former White House official, in both the Bush and Obama administrations.  Among many questions, and much give and take, I asked him why at least a few obviously good ideas, to which virtually anybody would agree, do not make it through the hurdles of authorization and appropriation.  Was ideology really in the way?

He said ideology was seldom the problem.  If one party has a great idea that the other party agrees is a great idea, the other party will still work to defeat the idea because they do not want the party with the idea to get credit for it.  They would rather see large numbers of people continue to suffer than have the other party get credit for relieving the suffering.

These insights and recent experiences have caused me to draft Seven Habits of Successful Members of Congress.

  1. Gain or retain power
  2. Get elected or reelected
  3. Minimize opponents’ success
  4. Undermine opponents’ initiatives
  5. Cultivate doubts about opponents’ intent, integrity and morality
  6. Support legislation that causes special interests to provide resources to accomplish Goals 1-5
  7. Initiate legislation that provides talking points that support accomplishing Goals 1-5

These habits are rank ordered – no. 1 is more important than no. 2, which is more important than no. 3, and so on.

Those Members of Congress who exhibit these habits – and not all do – have no interest in benefitting the public unless this is of value to retaining power, getting reelected, etc.  How might we get around this situation and create a functional governance enterprise?

Singapore provides an interesting example.  If we followed their model, we would have a highly educated, very well paid cadre of leaders to run the country.  Once approved, they would not be subject to Congressional oversight.  However, they would be required to create business-oriented goals and plans, as well as achieve the outcomes specified in these plans.  Collectively, they could pass laws and regulations.  They would run the public sector.

Congress would have only three duties.  First, Congress would approve the Federal budget.  This budget would consist of one number – the total – and members of Congress could approve this budget or not.  If the budget were not approved, government would immediately shut down.  Second, Congress would approve nominees for the highest posts – the Secretary of each Department and Supreme Court Justices.

Third, members of Congress would devote all remaining time to getting reelected.  There would be no Congressional committees, although members would be free to give endless speeches on any topic.   This would give them something to do, despite it having no impact on government operations.  The aforementioned highly educated, very well paid cadre of leaders would make all operational evaluations.

Once the Secretary of each Department was nominated by the President and confirmed by Congress, both would have minimal power over the affairs of the Department.  A Secretary could only be replaced if they failed to create publicly acceptable business-oriented goals and plans, as well as achieve the outcomes specified in these plans.  It would not be unusual for a Secretary to move from one Department to another after four years or so.  This would avoid someone overstaying their usefulness in one role, while also retaining their expertise.

Departments would be answerable directly to the public.  The attractiveness and effectiveness of their goals and plans would be assessed via nationwide polling conducted using secure, online services.  The news networks would focus on apolitical discussions and debates on these goals and plans.  A Secretary would be replaced if the public found their goals and plans wanting.  This would result in new nomination and confirmation processes to replace the leadership of the Department.

Competency and accountability would reign over rhetoric and ideology.  Presidents would run for reelection based on the quality of the team they built.  Members of Congress would run for reelection based on their efficacy in fulfilling their three responsibilities.  Consequently, leaders in government would learn to deliver value to the public and the public would learn to expect value.  Wouldn’t that be strange?

Disrupting Academia

Academia has become rather frustrating.  Out of control costs have been leading to spiraling students debts, exceeding the total US credit card debt.  Increasingly narrow and unreasonable criteria for tenure have led to people spending endless years in servitude.  The overall academic value proposition has been completely eroded for all but the administrative leadership and staff, and perhaps those involved in major sports.

This sets the stage for disruption.  New value propositions that obsolete the old value propositions seem possible and likely.  Why pay $200,000 for what you can get for $16,000.  My recent book, Universities as Complex Enterprises, explores such scenarios.  It occurs to me that it would indeed be unfortunate to be the last person to pay $200,000 for a bachelor’s degree.

So, let’s start from scratch.  In terms of students, I would focus on the best and brightest, as well as the most creative and committed. Admission processes would include interviews and demonstrations of an intellectual portfolio.  This portfolio could range from academic accomplishments to art exhibitions to classic car restorations.  GPA and AP grades would matter little; SAT and ACT scores would be unnecessary. The focus would be on a student body that would start with 500 students and grow to at most 5000 students.

Of course, this would require high schools, indeed K-12, to prepare students quite differently.  Accomplishments would be characterized in terms of real things created, not test grades.  Teachers would be mentors more than lecturers.  Math, for example, would become a means to accomplish something rather than a set of rules to be memorized.  Education would be more like hands-on internships rather than an industrial process that cranks out standardized products.

How about tuition?  What about fees where, like the airlines, universities have been steadily adding charges for many things?  Both would be free, but students would have to engage with faculty members in research. Students would only be admitted if one or more faculty members agreed to pursue research with them.  The process would be more like picking professional draft picks than choosing among millions of standard applications.  Who cares about scores?  How quickly can you create a data analytics website?

The curricula would be oriented around STEM (science, technology, engineering and mathematics), but laced with humanities and social sciences taught in the context of STEM.  You would still take Western Civilization, but the course would focus on technological and economic innovation, including innovations in music and the arts.  The curricula would also place great emphasis on teamwork, writing and oral communication.  Pure technical skills would not be enough for excellence.

How would the curricula be delivered?  There would be a mix of lectures, labs, and field experiences, all substantially supported by technology.  Classes would be very small, often with projects and research integrated into topics.  We would not be interested at all in students’ abilities to memorize; students’ abilities to solve real problems would be central.

Faculty members would be deep in terms of STEM knowledge and skills, but also great communicators and mentors.  Faculty members would usually have one or more avocations in history, languages, music, etc.  Faculty members would be expected to make student success a priority.  The faculty would start with 50 or so faculty members and grow to 500 at most.  There would be no departments, as faculty would be organized into interest groups, with chairs that rotate each year.

Scholarship will still be central, but much broader than the steadily narrowing research of most contemporary faculty members.  Faculty and students would generate a wide range of creative products, including articles, books, games, exhibitions, proof of concepts, tangible hardware and software prototypes, and perhaps organizations – companies, NGOs, nonprofits.

Tenure would not exist.  Faculty members would start with rolling three-year contracts, which would be extended another year for every year that they are acceptably productive.  The Dean would negotiate the terms of this agreement every year with every faculty member.  Contract terms could be extended to five years after the first three years, or any time later.

There would be two financing models, one for students and one for faculty and staff.   All students would receive 100% scholarships funded by industry, foundations, and governments. In some cases, but by no means all, students would be required to work for their sponsors for one year after graduation. Sponsors would be allowed to interview the students they might sponsor before students are accepted.

All other expenses would be financed by contracts, grants, and philanthropy.  The administration would include President, Dean and VP Academic Affairs, and VP for Finance and Administration, each with an Executive Assistant.  There would be Directors of HR, IT, etc.  The total administration would be roughly 10-20 people.  As noted earlier, faculty members would perform all student-related functions.

I can imagine many people thinking that this could be a great education for the 5000 students eventually enrolled, but what about the rest of the 20+ million college students in the US?  Could we replicate this model 4,000 times?  There are currently over 4,000 colleges and universities in the US – twice that if you count for-profit organizations — so 4,000 would not be a stretch.

Roughly 25% of students are enrolled in STEM disciplines, so only 1,000 universities could follow the model outlined thus far.  The other 3,000 universities would have programs organized around medicine, law, business, humanities, and arts.  Institutions would have agreements whereby students could be involved with more than one institution.  So, for example, people interested in STEM and medicine could satisfy their multi-disciplinary needs.

Universities currently employ over 4 million people, roughly 1.5 million as faculty members and 2.5 million as staff.  The model outlined here assumes 2 million faculty members and perhaps 100,000 administrative staff, not counting personnel for buildings, grounds, food services, etc.  Adding these personnel, total employment would remain in the neighborhood of 3 million.  Increasing faculty numbers by one half million, while reducing staff substantially would be rather disruptive.

Another major disruption would be in college sports.  Club sports would remain but these small institutions would be unable to serve as the farm teams for MLB, NBA, NFL, and NHL.  A distinct possibility is that these professional leagues would pay universities to operate their farm teams.  This raises the prospect of universities having students that only play sports.  Roughly 170,000 Division 1 students participate in these sports.  Therefore, perhaps 30 or so universities could be dedicated to sports.  Only about 1,200 of these students would become professional athletes, but many could work in the $500 billion sports industry.

The overall concept presented here is an example of Joseph Schumpeter’s “creative destruction,” a new business model that, over time, completely destroys an incumbent business model.  The academia ecosystem’s cost bubble has placed it at risk of disruptive innovation, perhaps not in the way argued here, but inevitably in some manner.  Business as usual will be increasingly untenable.

Population Health — For Cars

I have been thinking about population health for people.  Population health, in the fullest sense, requires integrating health, education, and social services to keep a defined population healthy, address their health challenges holistically, and assist them with the realities of being mortal.  It is a very ambitious idea.

Why do I think this is possible?  Are there any analogs where this has been accomplished?  It struck me that a Ford dealer or Subaru dealer is very good at population health – for cars.  I can visit my dealer with any problem and they have the full range of services needed to address it.

I do not have to schedule each element of the service.  There are undoubtedly, specialists for engines, transmissions, brakes, and so on.  However, I need not think about this.  The dealer holistically takes car of my car.  He or she decides which specialists are needed and how to sequence and coordinate their services.

When the range of services relevant to my problem have been completed, I am presented with a single bill that summarizes all the services performed, the price of each service, and the total price I am requested to pay.  If I question any service, including its price, I can get my question answered and concerns resolved before I depart.

Healthcare, obviously, does not work like this.  There are primary care clinicians that refer me to specialists who may further refer me to other specialists.  At each stop, I will complete a new patient record and sign various releases, waiving my rights to complain.  Each of these stops will result in one or more bills sent to me as well as my insurance company.  Most of the items listed on each bill will be meaningless to me.

This chain of services involves disparate organization’s whose objectives may be far from aligned. Success for each organization is typically defined as successful completion of the step for which their organization is responsible.  Success for patients, however, involves successful completion of all steps.  Quite often, assurance of overall success is left to the patients, who are usually unlikely to be capable of performing the task.

Car dealers are able to successfully deliver population health – for cars.  This happens because all the service providers are managed – not necessarily owned — by the same organization.  This organization takes full responsibility for care coordination.  If customers are not pleased with the service, they go to a different dealer or perhaps buy a different car.  This market-based arrangement works.  Healthcare, in contrast, it not really market-based and, consequently, successful delivery of population health will be a major challenge.

Washington Drama

I moved to Washington, DC a bit over four months ago.  I have long liked the city, traveling here at least once a month for business over almost four decades.

During this transition, I started watching TV shows associated with the White House.  I have been binge watching The West Wing – just into the third season of eight seasons.  I binge watched several episodes of House of Cards, but found the show too depressing.  I have been keeping up with Designated Survivor, a series whose first season just ended.

There is a fourth show that is reported each day on the front page of The Washington Post that is delivered to my door each morning.  In this show, events develop so fast that I have to check CNN at mid-day and in the evening to see what has happened in the past few hours.  This show is much more dynamic, surprising, and often amazing than the other three shows.

It usually seems too astounding to be true.  The dialog frequently involves statements that are blatantly and obviously false.  There are often retractions, which are also nakedly false.  People are accused of misdeeds that could not have happened.  Occasionally people, seemingly in the way, get pushed around a bit.  Bit players sometimes assault reporters.

There is a looming conspiracy in the background.  Foreign intrigues, security breeches, and under the table business deals suggest that the major story only involves the White House in that it serves as a pit stop between golf outings and negotiations of naming rights.  Occasionally, someone questions why the American public is funding all the travel and security associated with this deal making, but such questions are lost in the next day’s revelations.

This show has an enormous following as the news media — both liberal and conservative — devotes large portions of time to reporting each character’s statements and behaviors.  There are droves of pundits whose full time jobs are to report and assess the characters’ behaviors, motivations, and intentions.  The ratings have soared and the show will likely be renewed for next season and beyond.

Convincing the World to Support Your Ideas

Government agencies, private sector companies, and philanthropic foundations have billions of dollars to support your ideas, ranging from research projects to community development initiatives.  How can you gain access to these resources?

Millions of people are asking this question.  So, there are lots of competitors and your overall chances of success are quite small.  You might think this means that you have to respond to lots of RFPs (Requests for Proposals).  Writing loads of proposals will increase your chances; perhaps even get your probability of success up to a still frustrating level of ten percent.

Think about this process from the perspective of those receiving your proposal.  A few years ago, I unwittingly participated in a proposal effort where 30,000 proposals were submitted and 100 funded, so 0.33% chance of success.  This is not as bad as playing the lottery, but it is headed in that direction.

What did the review team do with 30,000 proposals?  If it was similar to many of my other experiences, their first task was to eliminate 29,000 proposals, for any credible reason.  One common reason is that no one on the review team knew anybody on the team associated with the proposal.  Unknown?  Gone!

So, the first principle is — Don’t be unknown.  You can become known by winning a Nobel Prize or a MacArthur Award, but this makes as much sense as expecting membership in sports Halls of Fame, before making the teams.  You win these awards after you are known, providing further evidence of the first principle.

The question, then, is how to become known.  The first step is to get to know people in the funding ecosystem of interest.  A good start is attending the same meetings they attend.  Introduce yourself.  Provide your business card.  Be vocal in discussions, making reasonable points, of course.

Prepare 2-4 page white papers on your ideas.  Keep the readers’ perspectives in mind.  Few, if any, of them will be focused on advancing your career.  Some, but not many, will be primarily focused on contributing to your academic discipline.  Many, if not most, will be concerned with how your ideas will benefit society in general, and domain-specific stakeholders in particular.

The second principle is – Articulate your ideas from sponsors’ perspectives.  If done well, they will ask you to elaborate.  What will you do to yield the benefits sought?  How long will it take?  How much will it cost?  Now is your opportunity to develop your ideas more thoroughly, knowing that your chances have become much higher.

Let’s assume your proposal is funded.  Is that the finish line?  It might be if you do not aspire to any more funding in your future.  That is seldom the case.  Future funding depends on how well you deliver on the current funding.  Actually, over delivering is a good idea.  There are no credible excuses.  If someone on your team is not delivering on promises, you have to make up the deficit.  The third principle is – Delight your sponsors; Don’t just satisfy them.

Let’s make another assumption.  Your idea succeeds!  You get great results and your publications are accepted in first-rate outlets, or you get glowing newspaper reports of your community project.  You are on the way to promotion, tenure or whatever matters to your career.  However, will one home run be enough?  If you want to sustain your nascent streak, you need to communicate the benefits of your success to your sponsors in terms they will appreciate.  The fourth principle is – Keep your sponsors in the loop; Communicate in their terms.

The bottom line is that success does not depend solely on your being very intelligent, highly motivated, and having lots of ideas.  You have to know how to convince the world to support your ideas.  The four principles outlined above will help you to succeed. 

A Real Train System

What if the US had a modern state of the art train system like other developed countries?  The trip from New York to Washington would take one hour rather than three plus hours.  The trip from Atlanta to Washington would take three hours rather than thirteen hours.  This would be a great boon to personal productivity.

What if we had modern state of the art subways, streetcars, and buses?  What if our transportation infrastructures — roads, bridges, tunnels, and airports — were efficient, safe, and fully functional?  Wouldn’t that be amazing?  This would be another boon to personal productivity.  Travel might be enjoyable again.

It is unlikely to happen, though. We have gotten used to a steadily deteriorating transportation system.  Enormous wastes of time and energy have become grudgingly acceptable. We expect derailments, crumbling freeways, and three-hour trips that become ten-hour trips or much, much longer. Two to three hour commutes each way to work are not common, but also not a surprise.

We do not seem to have the will to fix things.  Deferred maintenance – in other words, no maintenance — has become the norm. We only fix things, patch them up, when they totally fail. We wait for things to collapse. Then we build a new one. Sometimes leaving the rusting hulk of the decaying predecessor still standing along the side of the new structure.

Symptomatic of such neglect are litter strewn transportation infrastructures. Garbage strewn streets, underpasses, and ramps are all too common.  Such litter should be socially unacceptable but for unknown reasons it is not. We accept living awash in plastic bags, fast food refuse, beer bottles and occasional shopping carts, tattered sofas and dismembered dolls.

What would it take to change all this?  It would cost a lot on money, but create an enormous number of good jobs, plus a first-rate transportation system.  We did this with the Eisenhower Highway System and with Medicare and Medicaid, with very strong leadership from Presidents Eisenhower and Johnson, respectively.  President Obama showed glimmers of this type of leadership.  The current administration seems more bent on dismantling things.

The Fragility of Optimized Systems

Delta Air Lines designed and optimized a system to pack the seats on their flights and extract maximum revenue from passengers by charging for every element of an airline trip. The process is called revenue maximization. A senior Delta executive once told me, “We try to pull feathers until just before the goose honks.”

Delta’s system becomes very fragile when off-normal situations arise, potentially causing enormous grief for thousands of passengers. The optimized system has no slack, no resources for responding to off-normal situations.  If there were slack resources, Delta would have eliminated them to increase profits, the only metric that really matters to them.

Earlier this week, weather in Atlanta delayed flights, in my case returning from Los Angeles en route to Washington.  Delays added to delays.  Passengers just waited and waited. Upon landing, hours were consumed waiting for a gate. Whole days were lost, according to the Atlanta Journal-Constitution, due to Delta’s gross incompetence.

“Delta apologizes for your inconvenience. We appreciate your patience.”  This is Delta’s tag line. I hear it on every flight for one reason or another.  However, Delta talks service but does not deliver it. They are too focused on maximizing revenue to pay attention to service. Passengers become incensed and Delta just repeats their tag line.

As my flight was delayed by progressive half hours, a passenger asked the agent why the delay was always 30 minutes. She responded, “That is all we are allowed to tell you.” The passenger asked, “So when is this flight really likely to leave?”  She answered, “We have absolutely no idea. This could go on for several hours and then we may cancel the flight.”

It is rather amazing that many of my worst experiences in life are associated with Delta. This has fostered visceral negative emotions with anything I see or hear about Delta. There are very few, if any, other things that can prompt such negative emotional responses.

What happened to air travel?  When I first traveled with Delta in the 1980s, it was a quite enjoyable experience.  I fondly remember the ice cream sundaes on my frequent Atlanta-California trips.  I also remember my worldwide adventures, typically ending in London when I would relax with Delta who would “take me home.”

My million miler colleagues agree that those times are long gone.  Delta is now an adversary who is focused on extracting revenue from you.  Quality of service is now a joke, glittery words that mean absolutely nothing.  Delta and other airlines are totally focused on what we can do for them.

Beyond the Affordable Care Act

What are we trying to do by rethinking the ACA?  Perhaps we are seeking an ideologically acceptable ACA, one that the Republicans get credit for rather than the Democrats.   On the other hand, is insurance coverage really the ultimate goal?  I don’t think so.  We want a healthy and educated population that is competitive in the global marketplace.

Health insurance is one way to enable this, but so is a single payer system, e.g., Medicare for everyone.  Health insurance is our apparently preferred choice because that is the incumbent mechanism for paying for healthcare in the US.  A broader question is how do we pay for health, education, and social services that enable a healthy and educated population that is competitive in the global marketplace.

At one extreme, the answer could be that everyone pays for these services themselves.  In other words, everything is privatized and we have the world of Charles Dickens.  Of course, lots of people would not be able to afford health and education, so we would have a large class of people stuck in unhealthy, uneducated poverty.  They would eventually revolt, not just at ballot box, but also by physically attacking the privileged – this has happened many times before (Brook, 2013).

Despite the rhetoric of those who argue for a totally market-based approach, most people accept that governments – federal, state, and local – have to play some role in creating a more equitable situation.  And, at the other extreme, few argue that government should provide all health, education, and social services.  For example, there have been few, if any, calls for nationalizing private institutions of higher education, despite the financial bubble that has emerged in this arena (Rouse, 2016).

So either extreme has a rather limited constituency.  The answer is somewhere in the middle – a public-private “enterprise” that enables a healthy and educated population that is competitive in the global marketplace.  By enterprise, I don’t mean a single organizational entity.  I invoke the enterprise concept to motivate the need to look at the whole system that provides health, education, and social services.

Before suggesting how to find the middle ground needed, two phenomena should be explicitly addressed.  First, people both consume and generate resources, which includes money as well as food, housing, etc.  Health, education, and social services cost money, but people who are healthy, educated, and productive generate money and other resources, a portion of which is taxed by federal, state, and local governments to pay for services.

The Centers for Medicare and Medicaid Services (CMS) work to control the costs of health services.  CMS does not tradeoff these costs versus the resources a healthy population generates.  For example, they have no mechanism to incentivize employers to invest in prevention and wellness programs that will result in healthier employees when they retire and enter the Medicare program, despite the fact that this impact has been repeatedly proven (Rouse & Serban, 2014).

The second phenomenon was identified in an analysis of how value can be estimated for investments in people’s training and education, safety and health, and work productivity (Rouse, 2010).  When the entity investing receives the subsequent returns on these investments, it is often rather straightforward to make the economic case compelling.  However, when the entity investing does not receive the returns, they tend to see the expenditures as costs and try to minimize them.

To deal with the above two phenomena, we need to address the overall enterprise that provides health, education, and social services.  How are delivery, payment, and regulation accomplished in each of these service domains?  The high level of fragmentation in the US across federal, state, and local governments has resulted in a large numbers of silos that see monies spent as costs rather than investments.

This fragmentation affects both the effectiveness and efficiency of these services.  We can use computational simulations with interactive visualizations (Rouse, 2015) to explore ways of breaking down the silos of delivery, payment, and regulation.  I propose that the interactive environment be immersive and enable key stakeholders, which includes almost everybody, to explore the complexity of the overall enterprise.  Ideas such as the sharing of returns on investments – across silos — can be investigated.

Creation of such an environment will require many types of data related to the efficacy and costs of health, education, and social services.  Fortunately, the increasing emphasis on evidence-based policy (Haskins & Margolis, 2015) should provide support for the needed data analytics.  This should, in turn, enable investments in achieving the overarching goal of a healthy and educated population that is competitive in the global marketplace.

References

Brook, D. (2013). A History of Future Cities. New York: Norton.

Haskins, R., & Margolis, G. (2015). Show Me the Evidence: Obama’s Fight for Rigor and Results in Social Policy. Washington, DC: Brookings.

Rouse, W.B. (Ed.).(2010). The Economics of Human Systems Integration: Valuation of Investments in People’s Training and Education, Safety and Health, and Work Productivity. New York: Wiley.

Rouse, W.B. (2015). Modeling and Visualization of Complex Systems and Enterprises: Explorations of Physical, Human, Economic, and Social Phenomena. Hoboken, NJ: John Wiley.

Rouse, W.B. (2016). Universities as Complex Enterprises: How Academia Works, Why It Works These Ways, and Where The University Enterprise Is Headed. Hoboken, NJ: Wiley.

Rouse, W.B., & Serban, N. (2014). Understanding and Managing the Complexity of Healthcare. Cambridge, MA: MIT Press.

Test Driving MOOCs

I have been researching Massive Open Online Courses (MOOCs), compiling best practices and other good ideas that I sought from a variety of colleagues.  I recently completed the first lessons of three courses on the best-known MOOC sites:

  • Coursera course: “Chicken Behavior & Welfare”
  • edX course: “Dinosaur Ecosystems”
  • Udacity course: “Design of Everyday Things”

All three courses provide lessons composed of a series of 1-3 minute video clips, interspersed with short exercises and a multiple choice quiz at the end.  All three have forums where students can interact with the instructor(s) and other students.  All three are reasonably engaging.

Forums are like streams of emails or texts, rather than real interactions.  It may be that younger students find this quite acceptable as their daily lives are laced with these forms of communications.  Something like a multi-person Skype might feel more personal, although that would be cumbersome for some courses where large numbers of students are enrolled.  I suppose Skype could be limited to student-teacher interactions, although instructors with hundreds or even thousands of students could be totally overwhelmed.

Ashok Goel of Georgia Tech, working with IBM, created an AI teaching assistant, Jill Watson, to field the 10,000 student questions his MOOC receives each semester.  Obviously, there is much repetition in these questions, which greatly enhances the feasibility of this approach.  Students responded quite positively to Jill, not imagining she was other than human.  This kind of automation has been used in industry for some time to respond to customers’ questions about services being provided.

The production quality of the short videos varies greatly, some being very professional and others looking a bit like home movies.  Some are easy to consume, while others provide enormous detail.  I suppose I could have taken notes, but I would have had to repeatedly stop and restart the videos.  Navigation in each of the three MOOCs can be a bit confusing, but I expect one will quickly get over this.

My sense is that highly polished, well-done MOOCs will increasingly succeed.  Simply posting PowerPoint slides online, with recorded audio lectures, is not engaging, and will eventually disappear.   Such stale offerings do not leverage the engagement potential of online technologies.  Greater engagement can compensate for some of the limitations noted above.

An important hurdle that must be surmounted to succeed is the cost of highly polished, well-done MOOCs.  One very credible estimate is 1,000 hours of design and development time per course.  Those that can make such investments will attract thousands of online students.  Once the credentials associated with success in these online courses are acceptable to employers, it is easy to imagine a massive shift away from traditional classrooms.

Everyone will take the course on any particular topic from the very best instructor of that topic.  For example, everyone will take physics from Richard Feynman and economics from Paul Samuelson.  The fact that these luminaries are no longer with us will not be a hindrance.  Technology will enable them to teach new developments in their fields, despite never having heard of them during their lives.

Appearing In and Winning the Super Bowl

There have been 50 Super Bowls (SB). There have been 100 starting quarterbacks (QB). 62 of the 100 QBs have started more than one SB.  This 62 includes 20 individual QBs.  36 of the 62 QBs won the SB, a 58% winning percentage. 38 (100 – 62) QBs have started only one SB.  14 of these 38 QBs won the SB, a 37% winning percentage.

32 NFL teams times 50 years yields 1600 starting QB years. 4.4 years is the average career length of a QB.  Thus, there have been roughly 364 (1600/4.4) starting QBs.  58 (20 + 38) QBs have started a SB, yielding a 15.9% (58/364) starting percentage and a 9.3% (34/364) winning percentage.

32 NFL teams times 53 players per team times 50 years yields 84,800 player years.  3.3 years is the average career length of an NFL player. Thus, there have been roughly 25,697 (84,800/3.3) players.  There have been 5300 (53 x 2 x 50) players in one or more SB.  Thus, there is a 20.6% (5300/25697) appearance percentage.  However, this estimate is too high for the following reason.

For QBs, multiple appearances are known and included in calculations.  For players in general, this data is not readily available.  If this phenomenon were ignored for QBs, the appearance percentage would be 0.275 (100/364), an overestimate by a factor of 1.73 (.275/.159).  Adjusting the players in general percentage by this factor yields an 11.9% (.206/1.73) appearance percentage.

Professional Relationships

The wonders of the Internet and social media seem to have radically changed the nature of relationships.  This is perhaps most apparent in personal relationships where email, texting, Facebook, Twitter, and other offerings provide constant updates on what a vast network of family and friends are doing and thinking at the moment.  Many people spend a significant portion of their time generating and responding to this flow of messages.  I find this particularly disconcerting when teaching class and several students in the front row never look up from their devices, their fingers endlessly tapping on their smart screens.

As amazing as this all is, in this post I address professional relationships and how information technology has morphed the ways in which individuals seek opportunities, secure positions, and perform once in these positions.  My daughter pursued jobs a few years ago and my son more recently.  They prompted the observations that follow.  It struck me that the value of any advice I could offer was substantially offset by the fact that I have never applied for a job in the sense that this act is now construed.

This is due to the simple fact that all my opportunities over 50+ years have started with relationships, not websites, electronic documents, etc.   During my senior year in college, I interviewed with several companies on campus and took trips to GE (railroad engines), IBM (computers), Pratt & Whitney (aircraft engines), Raytheon (submarine systems), and US Steel (railway cars), and received offers from all five companies. I applied for graduate school at MIT, RPI, and URI and was accepted by all three universities.  Thus, I had eight opportunities that were linked to people I had met and talked with along the way.  Of course, in those days, there was no other way to do this.

Once I finished my PhD at MIT, I took a visiting position at Tufts University on the advice of my advisor.  I then pursued a single alternative, the University of Illinois at Urbana-Champaign, after communicating with the department head.  I spent a year at Delft University of Technology, invited by a colleague with common interests.  The school chair at Georgia Tech contacted me, convinced me that I would find a visit interesting, and subsequently made an offer too good to refuse.  I called the dean at Stevens informing him that I would soon retire from Georgia Tech and I was offered a chaired position there within a few weeks.  I am currently considering a few alternatives that have emerged from a range of professional relationships.

My first company, Search Technology, was founded with a single customer where a former graduate student worked.  The company grew via major contracts with companies where colleagues worked.  The next company, Enterprise Support Systems, emerged when Search Technology customers asked for products and services that were not feasible within the older company’s costs structure.  Specifically, a company used to multi-million dollar contracts can find it quite difficult to create software products selling for $1,000 per copy.  Enterprise Support Systems grew by selling to other divisions of existing customers.  Eighty percent of revenues came from twenty Fortune 500 companies.

One or more of these companies served as lead customers for each new software tool.  They would buy a corporate license, at a big discount, for a product that did not yet exist.  Their users became members of the design and development team, assuring that they were pleased with how well the product met their needs.  Our close relationships enabled their trusting us and investing in yet-to-be-defined solutions.  A side benefit was that no other companies were able to bid against us.

What is different now?  One of my PhD students recently applied for almost 40 faculty positions.  He did this online.  The web-based system immediately requested that I provide a reference letter, with a two-week deadline.  Tailoring the letters a bit to each institution, I managed to almost meet the deadline for the 40 letters.

He will not end up interviewing with even half of these institutions.  However, it was convenient for them – not for me – to request these letters just in case they later needed them.  There were no humans involved – just me and a website.  There were no business relationships – just an IT system executing a workflow.

Lots of things work this way now.  When you submit articles to professional journals, the interactions are all automated.  A year or so ago, I submitted an article and was requested to choose key words from a fixed set.  None of the words matched the journal’s topical areas.

I emailed the editor, asking how to respond.  He said that I had to choose among the key words provided.  The vendor of the platform did not allow changing the choices.  It was rather difficult to map my article on healthcare to reinforced concrete and welding.  It certainly did feel that I was serving the platform rather than it providing services to me.

It used to be that people in your organization were experts in benefits, contracts, purchasing, etc.  You knew them and could call on them for help as needed.  Now there are IT systems, often multiple IT systems that require multiple entries of the same user names and passwords to access a single function.  If, for example, you want to change your mailing address, you have to do this in each system because databases are not integrated.  You need to keep track of what each system knows.

As machine learning increasingly becomes the underpinnings of such systems, they will know a lot about you – but they won’t know you.  We will work remotely, interact through various IT systems, submit work products electronically, and the balance of your bank account will occasionally be incremented.  In the “gig economy” we will bid on opportunities to create work products, compete with untold other bidders, sometimes get selected by the deep learning vendor selection system, and use various online sources to create and deliver the promised outcomes.  We won’t really know anybody professionally, although your buddies at the local pub may argue the strengths and weaknesses of the next generation IT platform.

 

The Academic Job Market

Engineering and science account for roughly three quarters of all PhD graduates, with half of these degrees awarded to US students and the other half to international students. Many of these graduates aspire to tenure-track faculty positions at universities. However, the percentage of faculty openings that are tenure track has been steadily decreasing for quite some time. Universities have found that non-tenure track faculty members, as well as post-docs and adjuncts, are much less expensive, which helps to compensate for strong growth of administrative costs at many institutions.

With more PhD graduates chasing fewer tenure track positions, universities have steadily increased their criteria for hiring. This can include 10-20 published journal articles, extensive teaching performance with good teacher ratings, and professional thought leaders who will write letters extolling your intellectual and social virtues. A fresh PhD graduate cannot possibly satisfy these criteria.

Consequently, especially in the sciences, new PhD graduates seek post-doc positions. These positions pay roughly twice what PhD assistantships pay, i.e., $4,000 per month rather than $2,000 per month, but much less than the $8,000-$10,000 per month paid to tenure track assistant professors. With an average of seven years to earn a PhD and perhaps three years as a post-doc, the candidates are now in their mid 30s before they are ready to compete for coveted tenure track positions.

The competition is fierce. Each position draws hundreds of applications or more. Consequently, people may apply for 50 or more positions. If they win a tenure track position, they now have 7-10 years to earn tenure. During this time, they need to publish 2-4 journal articles per year in top journals as defined by their subdisciplines.  To hit these numbers, they focus on brief incremental contributions that comfortably fit in reigning paradigms. They often get really good at this and will continue in this mode for the rest of their careers. Any effort that is more complicated or takes considerably more time will be shunned, as it will slow them down on the path to full professor in their mid to late 40s.

The process is further complicated for international PhD students. The income they receive in graduate school may be greater than their income would have been in their home countries. Thus, the international student may gain a couple of hundred thousand dollars during the ten years of PhD study plus post-doc.  In contrast, an American PhD student may forgo up to a million dollars of income over the ten years.

The overwhelming problem for international PhD students is the likelihood of being deported immediately after graduation. Federal agencies and other sponsors will have invested perhaps three hundred thousand dollars in creating a top expert, and they then force this expert to leave, to go home and compete against us. It makes no sense.

International students are quite creative in identifying training opportunities and internships that enhance their credentials beyond their degrees. Hoards of lawyers specialize in helping these graduates jump immigration hurdles. A significant number make it and are increasingly filling the ranks of science and engineering faculties across the US. Tenure-track faculty members born in the US are disappearing with retirements, slowed by the Great Recession, but inevitable nonetheless.

Many of the grads from MIT, Stanford, Berkeley, etc. return to China, India, Korea, Singapore, and elsewhere to become faculty members at their best local institutions of science and engineering.  With their countries making much greater investments in these institutions, compared to trends in the US, the numbers of students applying to US institutions are declining, in some cases rather significantly, e.g., Korea.

Combining the inevitable decline in international PhD students at US institutions with the steadily decreasing value proposition for US born PhD students, the future looks rather bleak for US PhD programs.  However, we could choose to change the value proposition for US students.  We would need to (at least) triple PhD students’ stipends and waive tuition.  There is a variety of ways this could be approached.

When I spent a year at Delft University of Technology, all the PhD students were full-time staff members with regular research and teaching responsibilities.  They had reasonable salaries, paid no tuition, and progressed as part of the intellectual fabric of the institution.  This was great for them and great for the university. There are, of course, quite a few implications of this idea.

How would this be funded?  In the current system, the university receives overhead on student’s stipends plus tuition.  Of the $80-100,000 that it annually costs for a half-time graduate student in a private university, only roughly 25% goes to the student.  Tripling the stipend would increase overall costs by at least 50%.  Would research sponsors accept $160-180,000 as the cost of a half time student?

The central balancing factor is that these PhD students would be full-time employees and have substantial research and teaching responsibilities.  These PhD students would be US born with great English skills, reasonable compensation, and aspirations to become faculty members.  It would make enormous sense to invest in enhancing their research and teaching knowledge and skills, particularly since they would not be deported upon graduation.

The availability of these personnel would allow significant reductions in the numbers of tenure-track faculty members.  Decreasing the number of tenure-track faculty members would steepen the promotion pyramid, likely decreasing the chances of becoming full professor.  It would certainly decrease the annual rate of faculty hiring, potentially making the competition even fiercer.

PhD students as full-time professionals would substantially decrease the number of such students needed.  If we were to explore this in more detail, I expect we would find:

  • Decreased numbers of PhD students with substantially increased percentages of US born students
  • Decreased numbers of tenure-track faculty, particularly as inevitable retirements increase
  • Decreased university revenues, but also decreased costs, except perhaps for administrative overheads that seem immune to cost pressures
  • Decreased numbers of journal articles published by PhD students whose full-time responsibilities would not allow the traditional focus on publications

Regarding this last observation, the consequences include the journal article “Laminar Flow Over an Inclined Plate at 17.5 Degrees” never appearing. (17.4 and 17.6 degrees had been addressed in two papers in earlier issues of the journal.)  Is this a loss?  This is a quite complicated question with many implications.  I will return to this question at a later time.

Complexity: Absolute or Relative?

I spent the last few days in Santa Fe, absorbed in discussions of complexity, with particular emphasis on healthcare delivery.  I have delved into this topic for quite some time. Three decades ago, we published our studies on the complexity of troubleshooting – figuring out the source of unfortunate symptoms, e.g., why your car won’t start.

Sponsors of our research asked us to devise a metric for the complexity of a troubleshooting task, which they intended to use to match to the complexity processing abilities of maintenance personnel.  Pursuit of this goal led us to conclude that complexity is related to the intent of the person asking the question or performing the task, as well as the knowledge and skills of this person.

To illustrate, let’s say you purchased a Boeing 747 to use as a paperweight.  From this perspective, this complicated airplane is just a large mass, pretty useful for keeping errant papers on a very large and structurally sufficient desk.  In contrast, if you made this purchase with the intent of operating and maintaining the aircraft, the Boeing 747 is much more complex than your unwieldy paperweight.

This insight leads to a fundamental conclusion.  Complexity has to be defined in terms of a relationship between an observer and an entity.  The observer’s intentions, knowledge, and skills frame the assessment of the complexity of the entity.  Thus, complexity is relative rather than absolute.  Consequently, for example, we can only assess the complexity of a troubleshooting task relative to the personnel involved in the task.

I have discussed this conclusion in many of my talks over the past ten years or so.  Roughly 90% of the people with some level of expertise in the topic agree with me.  The other 10% say something like, “What you are saying makes sense, but what about real complexity?”  These people are usually physicists who firmly believe in the absolute nature of complexity.

Many of those researching complexity construct network diagrams of the elements and relationships among elements of engineered, organizational, and natural systems of interest.  They calculate various metrics associated with these network diagrams and then argue that these metrics reflect the inherent complexity of the systems of interest.  I have done this as well, with the explicit acknowledgement that these network models reflect my intentions, for instance, to predict the difficulty of driving in different urban environments.

There are no intention-free models.  Every model is constructed with the intent to analyze, assess, or predict some set of phenomena.  Any properties of these models used as complexity metrics reflect the intentions of the modeler(s).  This is as essential today as it was for Newton, Darwin, and Einstein in past centuries.  Absolute complexity is a chimera.

Why You Hate Your Airline

The October issue of Consumer Reports outlines “Secrets to Stress-Free Flying.”  This 14-page article provides an interesting history of the airline industry, including the forces that drove your once loved airline to become an object of intense scorn and hatred for most passengers.

Over recent years, the airlines have refined their strategy for making record profits. Charge as much as possible, squeeze passengers into smaller and smaller spaces — which poses medical risks (see Consumer Reports article) — provide as little service as possible, make passengers pay for almost every breath they take in flight, and smile while they say they care about passengers.

I don’t think we should re-regulate the airlines, but they should be forced to pay for the problems they impose on passengers.  For example, they should pay you when they waste your time.  How about $100 per passenger for every hour they are late. This includes delays for mechanical problems, crew complications, and inclement weather.

Airline executives will complain that delays are seldom their fault. This is akin to shipping executives complaining about all the water, or trucking executives complaining about the traffic.  My answer is simple. If you don’t know how to run an airline, get out of the business. Flip burgers. Mow grass. But stay away from airports.

Cultures of Compliance

I have encountered many organizations, mainly in government and academia, where compliance with policies, procedures, and norms became the primary organizational objective. Producing useful outcomes became secondary, almost a nuisance because production took resources away from compliance.

This becomes an almost insurmountable problem when the organization is laced with administrative incompetence. Perhaps well-intended but fundamentally incompetent administrators force compliance on those who would have been producing useful outcomes.

This is further complicated by fragmented and antiquated information systems. One measure of this is the number of times you have to enter your user name and password to accomplish one task. Another measure is the number of times you have to start all over because the system does not recognize the computer they bought for you and told you to use.

The ultimate complication is when the legal function is in charge.  They want to make sure that the organization cannot be blamed and held accountable for anything.   This objective is, of course, much easier if the organization avoids doing anything.

I once asked a Chief Legal Counsel if her compliance job would not be easier if the organization provided no services, accepted no monies from sponsors, and created nothing of value. She replied, “It certainly would minimize our risks.”

I then asked, “How could the organization survive if it provided no value to anyone?”  She responded, “That not my responsibility.  My job is to maximize compliance so as to minimize risks. You need to talk to the President if you are concerned about the value we provide.”

She was right. Her function was risk management, not value creation. I talked to the President, but he was all hype and slogans. His dominant goal was assuring a financial surplus each year that got bigger the following year.

I then talked to the organization’s equivalent of production workers. They were frustrated by increasingly tight budgets, driven by the goal for surpluses.  They were angry about all the time they had to devote to compliance paperwork, often entering the same information into multiple information systems.

Morale was abysmal across the organization. In the executive suite, however, everything was upbeat. All the slogans were prominent. Glossy brochures touted the smoothly running organization.   Everything was aligned for an unfortunate surprise.

The Disruption of Autonomous Vehicles

Many pundits argue that driverless cars will soon be here.  You can argue with the timelines they articulate, but it is difficult to disagree with the distinct possibility of the technology eventually maturing and becoming an increasing portion of the vehicles on the road.  This technology will be truly disruptive.

There will be the benefits of a more efficient transportation system, dramatically fewer accidents, and commute times spent being productive or at least being more relaxing.  There will, however, be costs associated with the technology and infrastructure needed to support it.  There will still be some accidents, although the technology, unlike human drivers, will be continually improved as lessons are learned.

Many of the disruptions will be byproducts of these innovations.  As accidents disappear, the most profitable segment of the insurance industry will wither.  As car and truck services replace individual ownership, vehicles will be used 24 x 7 and the number of vehicles will steadily decrease.  Used cars will disappear, eliminating roughly three quarters of the car loan business.  The after market for vehicle add-ons will disappear.

Truck drivers will become rare, as will drivers of taxis, limos, and other car services.  The autonomous car service industry will have their own service operations, replacing corner filling stations and car washes.  The need for parking places will plummet, proving real estate for other purposes but also significantly reducing municipal revenues.  The need for traffic police and the issuing of speeding tickets will disappear, also reducing municipal revenues.

I have read that as many as 5,000,000 jobs will be eliminated.  At the same time, millions of new jobs will be created, but probably not for the same people.  This has happened before.  Electricity disrupted the marketplace in the late 19th century and automobiles dramatically disrupted horse-drawn transportation in the early 20th century.  The acreage and labor associated with feeding and caring for horses plummeted.  The pollution of horse manure did as well.

The process of one or more technologies disrupting a market is often termed “creative destruction.”  The creation of innovative new ways of doing things results in destroying the old ways.  This process can be very painful for those skilled in the old ways.  Efforts and resources have to be devoted to gaining new skills.  Over time, the new ways flourish and the overall economy greatly benefits.

Clock Speed in Academia

An industry executive that chaired an advisory board at a major research university once commented to me that academia’s unit of time is the semester.  “When a faculty member says he will get back to me right away, he means by the end of the semester.”

We measure performance of computers in cycles per second, manufacturing processes in cycles per hour or day, and academia in cycles per semester.  Classes are taught once per semester.  Research papers are produced roughly once per semester.  Students graduate once per semester. Proposals for funding are typically due once per semester.  Thus, it is rather natural to have a metric of cycles per semester.

Each semester appears to be roughly four months in duration.  Nothing can be accomplished in the summer months because quorums are impossible.  Little can be done from mid December to mid January due to holiday plans and celebration recovery.  Once Fall and Spring breaks are subtracted, as well as numerous holidays, each semester ends up having about three months of useful time.

I won’t detail here what needs to be done – see my recent book if this is of interest*.  The overall set of things is called faculty governance, which includes evaluating and approving courses and curricula, reviewing and recommending (or not) promotions and tenure, and endless revisions of the faculty handbook.  Most faculty members do not enjoy this, but do not want anyone else doing it.

A committee that meets once per semester is considered reasonable.  More than once per semester is judged outstanding.  Committee membership often changes every year, so a particular set of people have two chances to accomplish something.  The next set of members of the committee may be such that they undo what the previous set did.  At the very least, the next set is usually unaware of the previous set’s decisions.

Difficulties arise when decisions about classes, research, proposals, etc. need to happen faster.  Most faculty members will do their best to meet hard deadlines, e.g., proposals not accepted after March 15th.  On the other hand, soft deadlines, e.g., let’s try to get a first draft done by next Monday, are difficult for many faculty members to understand.  Hence, soft deadlines are often ignored.

Faculty members with earlier careers in business, or those like me who took extended leaves of absence to found and grow businesses, are often frustrated with the cycles per semester clock speed.  They feel that it takes far too long to accomplish things.  They are astonished by faculty members who have spent their whole careers in academia and see the stumbling progress as fine indeed.



*Rouse, W.B. (2016). Universities as Complex Enterprises: How Academia Works, Why It Works These Ways, and Where the University Enterprise Is Headed.  Hoboken, NJ: John Wiley.

Student Debt and Jobs

The August 2016 issue of Consumer Reports summarizes a much longer report from revealnews.org on student debt.  Their headline is 42 million people owe $1.3 trillion.  Their survey found that “45% of the people with student loan debt said that college was not worth the cost.  Of those who said college wasn’t worth the money, 38% didn’t graduate, 69% have had trouble making loan payments, and 78% earn less than $50,000 per year.”

The US Department of Education holds 93% of the $1.3 trillion in outstanding loans, making it one of the world’s largest banks.  They outsource debt collection to private firms, many of which are owned by JP Morgan Chase and Citigroup.   These debt collection firms pursue the 7.6 million borrowers in default, making more than $2 billion in commissions this year.

Of course, as noted in my last post, the whole process is driven by spiraling costs of higher education, which is driven, in turn, by academia’s “cost disease,” that results in cost increases far exceeding inflation.  Universities are unwilling and unable to control costs, in large part due to the bloating of administrative and support functions.

The June 25th edition of The Economist includes a special report on artificial intelligence.  They project that jobs such as telemarketers, accountants and auditors, retail sales people, technical writers, real estate agents, and word processors and typists will likely disappear.  I have reviewed many articles on the top ten jobs of the future.  They all require technical skills.  Many require advanced degrees.

These two trends are on a collision course — higher education that is unaffordable and jobs that require higher education.  Further, as noted in my last post, the third trend is younger people who cannot afford to repay their debts, cannot afford to buy a house, cannot afford to get married, and cannot afford to have children.  The good news is that JP Morgan Chase, Citigroup, et al. made $2 billion in commissions.

Higher Education Bubble

The steadily escalating costs of a college education coupled with spiraling mountains of student debts cannot be sustained.  Universities are unwilling and unable to control costs, in large part due to the bloating of administrative and support functions (Rouse, 2016).

A great example is the University of California System where, excluding the number of faculty members, there is roughly one administrator per student.  The daughter of a friend enrolled at UCLA last year.  I suggested that she ask to meet her administrator.

These bloated costs result in constantly increasing tuition, fees, and room and board.  Another friend has a 12 year old who hopes to go to Stanford in six years.  This friend is planning on Stanford costing $100,000 per year by then, and saving accordingly.  This is all but impossible for the vast majority of families.

In a recent meeting of academic health centers, the impact of healthcare reform on physician salaries was discussed.  Physicians’ pieces of the pie are likely to get smaller when payment for outcomes replaces fees for services.  With lower incomes, physicians are unlikely to be willing to finish their education with $300,000 of student debt.

More typical student debts are much smaller, in the range of $30-50,000, with repayment amounting to roughly $500 per month over ten years.  Ben Casselman (2016) reports, “New graduates’ wages are rising faster than those of most other groups; the typical recent college graduate earned $13 an hour.”  $26,000 per year translates into a bit over $20,000 after taxes, social security, Medicare, etc.  So these new graduates will need roughly 30% of their after-tax income to repay their loans.

This leaves about $1,200 per month for everything else.  The possibility of buying a home disappears.  Marriage may be avoided or long delayed.  Children are unaffordable.  Without owning homes or having children, young people are not buying appliances, carpeting, strollers, etc. There are frequent reports of data that portray these trends.

How will the higher education bubble burst?  I think it will be a combination of technological disruption and changing values and norms. Online education, in its many forms, will continually get better.  Studies will eventually show that online education yields superior results to traditional education in many, but not all, areas.  In a recent analysis, I show how this could result in the total cost of a college degree being $16,000 (Rouse, 2016).

Values and norms will change in the sense that employers will come to accept credentials earned online as equivalent to those earned in traditional education.  In parallel, accreditation bodies will adapt to these trends rather then thwart them.  These changes will not happen all at once.  Hybrid offerings might, for example, involve years 1-2 online and years 3-4 on campus.  Those who drop out in the first two years will have $4-8,000 of debt, at most.

What happens to all the bricks and mortar of higher education when on campus enrollments steadily decrease?  One idea is to turn facilities into retirement homes.  It has often been noted that retiring in a college community has several attractions, one of which is the possibility of taking classes and perhaps earning credits in literature, history, political science or art.  The growing demand for education by much older students is another scenario that I have recently explored (Rouse, 2016).

References

Casselman, B. (2016). This Year’s College Grads Are The Luckiest In A Decade, http://fivethirtyeight.com/features/this-years-college-grads-are-the-luckiest-in-a-decade/

Rouse, W.B. (2016). Universities as Complex Enterprises: How Academia Works, Why It Works These Ways, and Where the University Enterprise is Headed. Hoboken, NJ: John Wiley.

The Allure of Quests

I really enjoy stories, and particularly movies, where an older man and younger woman are on a quest – perhaps to solve a mystery, right a wrong, or flee an evil force.  They are thrown together and their shared aspirations drive them closer as they work together to pursue their quest.  They learn from each other, despite occasional conflicts, and eventually succeed.

Movies that come to mind are North by Northwest (Cary Grant and Eva Marie Saint), Charade (Cary Grant and Audrey Hepburn), and The Big Sleep (Humphrey Bogart and Lauren Bacall).  There is an emergent romantic undertone in these stories, but the plot is dominated by the quest.  The older man helps the younger woman to achieve her goals, in these examples, stopping the bad guys, finding the murderers, and saving her sister from her fate.  Once the quest is successful, the romantic undertones take center stage as the story ends.

I think that what appeals to me is the idea of shared aspirations to achieve substantial goals involving some risks of failure.  The couple – actually a team more than a couple – support each other to contribute to progress toward the goal.  Conflicts of priorities and personalities emerge along the way, but the importance of the quest helps them to move beyond these conflicts. Respect for each other’s role and competency grows.  They become truly interdependent.  And, of course, the team achieves its goal, with warm affection as the immediate reward.

It seems to me that male-female relationships are much richer when there is a shared sense of purpose beyond going to respective jobs, keeping house, paying the bills, eating and drinking, and taking holidays and vacations.  Raising children can, of course, provide a shared purpose, but also can tend to feel like another job with enormous responsibilities to buy more and more things, oversee schooling and homework, address logistics of extracurricular activities, and save for higher education.  The idea that your only purpose is to foster the next generation has always felt rather limiting to me.

Yet, quests that benefit humankind are very appealing and, certainly, raising children to become good citizens fits in here.  Plus, the joys of seeing your progeny succeed in life are difficult to overestimate.  Nevertheless, the idea that your primary role is to prepare the next generation to accomplish what you could not seems like passing the buck – why couldn’t you do it?  My sense is that you can have both great accomplishments and great kids.  In fact, your kids can be even greater if they experience what you accomplish.

A Student’s Questions

One of the PhD students in the School of Systems and Enterprises asked me a few questions after reading my March 15th blog post on “Thoughts on Teaching, Classrooms, and Computers.” She wanted to know what I would do if I was now a PhD student. Before getting to her specific questions, I need to cover two preliminaries.

First, I often get questions from students who are trying to decide on future directions. I have a simple, yet I think powerful, answer.  “Identify a scarce skill that is highly valued and you love doing.”

If the skill you love exercising, is abundant in the population, it will not be highly compensated. If the skill is not highly valued, it will not be highly compensated. Of course, you may be satisfied with modest compensation.

Second, I am rather biased toward recommending STEM fields, particularly engineering. My experiences are that engineering prepares people for an amazing range of futures. People with well-honed problem solving skills can succeed in many arenas.

Now, let’s consider her questions.  How would you choose your dissertation research topic?   Choose what fascinates you, but be realistic. You need to become an expert at something that society cares about. This still leaves a wide range of possibilities.

What courses would you take?  Required courses are, obviously, required. Add courses needed to directly support your research. Throw in a couple for fun, for example, economic history or creative writing.  The payoffs from such courses will surprise you.

What extracurricular activities would best advance your career?  Such activities only count, career wise, if they are related to your research. I chose woodworking, hiking, and travel, but not to advance my career.  Keep in mind that you are creating you, not just your resume.

What internships would best advance your career?  Again, these only count if they are related to your research. On the other hand, paid internships (or just plain jobs) can create a rainy day fund while you are completing your degree program.  I always liked real hands-on work, e.g., plumbing, or real technical work, e.g., engineering analyses.

Overall, I am driven by problems that I want to understand and contribute to solving. I am problem-oriented. In contrast, some people are method-oriented. They look for problems that are good fits for their chosen methods.  They often have to scale down problems to fit their method. In contrast, I often have to scale up methods to fit my problem of interest.

Career success is rather different for these two perspectives. Method-oriented people are judged by their abilities to extend methods in some substantial way, often with associated theorems and proofs.  The domain of application is of less importance.

Problem-oriented people tend to immerse themselves in the domains of the problems of interest. They are judged by their contributions to solving problems in these domains. This often involves providing empirical evidence of the impacts of their contributions.  Advancing methods is secondary.

Keep in mind that the world needs both Newtons and Darwins.  If you are problem person like me, sailing the enterprise seas, you are glad that someone else is forging the next generation methods.  Problem people are often really good at formulating problems, but given a valid formulation, the method people can be invaluable.

Thoughts on Teaching, Classrooms, and Computers

The purpose of teaching is to enable learning and, over time, mastery.  Classrooms and computers – smart boards, workstations, laptops, tablets, smart phones, etc. – are enablers of learning.  The most important enabler is student engagement.  This can be a challenge as ubiquitous digital devices often lead to significant student multi-tasking, much of it irrelevant to the topic at hand.

There is abundant potential variety in terms of modes of delivery that might enhance engagement. However, “Didactic teaching remains the pedagogical mainstay of many traditional classrooms and traditional teachers. It is the pedagogy of instruction and immutable facts, of authority and telling, and of right and wrong answers – it is teacher-centered and values learners who sit still and listen quietly and attentively, passively accepting the teacher as the knower and expert, both the source of knowledge and judge-jury of knowing.” (New Learning, 2016).

I have found in large undergraduate courses (60-80 students) that traditional didactic teaching can prompt disengagement, especially when lecture notes or slides are provided and the lecture closely follows these notes or slides.  What seems to work better is the addition of real-world examples and stories (not on the notes or slides) that illustrate the use or misuse of the material being presented.   In a recent experiment, we announced at the beginning of the lecture that there would a quiz on the lecture at the end of the class, i.e., 45 minutes later.  Students’ digital devices were little used during those 45 minutes.

In graduate courses, typically much smaller (8-12 students), my experience is that engagement increases if the students do more of the talking.  In three cases, I designed the course and compiled the course materials, but had the students give the lectures.  The students found this very rewarding.  Rather serendipitously, I learned to always have one of the better students lecture first as this sets the benchmark for the rest of the students.  By “better” I mean motivated, organized, and articulate, as well as with a sense of humor, rather than the student with the highest grade point average.

Table 1 contrasts didactic and Socratic teaching in terms of passive versus active learning.  Of course, there are more than two choices; there is a continuum.  The experiences mentioned above suggest that I have achieved greater student engagement when classes are more towards the Socratic end on the continuum.  How can the use of smart boards, workstations, laptops, tablets, smart phones, etc. enhance this approach?

The most ubiquitous use of computer technology is computer-projected PowerPoint slides.  This saves the lecturer having to write notes on a whiteboard or, in rare cases, a blackboard.  This means that the lecturer spends more time looking at the class rather than the board.  This enables much quicker detection of student disengagement.

Didactic

Socratic

[Master-Disciple]

[Shared Inquiry]

Passive Learning

Active Learning

1. Teacher centered: based on the assumption that the teacher is the primary agent in learning. 1. Problem centered: based on the assumption that the student is the primary agent in learning.
2. Teacher’s role: to impart the results of experience, personal study, and reflection. 2. Teacher’s role: to uncover the question that the answer hides. To be a co-learner.
3. Primarily deductive: the usual methods are lecture, story telling, use of analogy, and aphorism. 3. Primarily inductive: the usual methods discussion, dialogue, and problem solving.
4. Test of truth: authority and experience. 4. Test of truth: reason and evidence.
5. Learning is the reception of ideas. 5. Learning is a conflict of ideas: a thesis, antithesis, and a synthesis that results in new knowledge (Hegel).
6. Student’s role: to be passive, open, receptive, trusting, and unquestioning. 6. Student’s role: to be active, questioning, critical, and discriminating–learning to trust one’s own judgment (independent thinking).
7. Evaluation is factual recall of data–commonly in the form of objective tests–right and wrong answers. 7. Evaluation is application of understanding interpretation of data–commonly in an essay, speech, journal, or a review.
8. Ultimate goal: wisdom viewed as the internalization of truths and beliefs. 8. Ultimate goal: wisdom viewed as an informed ignorance (knowing what one does not know–the Socratic paradox).

 

Table 1. Didactic vs. Socratic Teaching (College English, 2016)

The downsides of PowerPoint, or equivalent, includes tendencies to express all ideas as bullet points, cram too much text into slides, and use colors combinations that are unreadable, e.g., dark blue lettering on a black background.  In general, PowerPoint helps the speaker more than the audience.  The best illustration of this is when speakers literally read their slides.  In general, most PowerPoint presentations represent little more than computer-aided didactic teaching.

Hands-on interactive demonstrations can help to engage students, particularly when the students are the creators of the demonstrations.  Conservations about real-life experiences can also be engaging.  Teachers’ expositions of real-life applications of the material being discussed in class usually cause greater student attention, particularly when they can ask questions about the experiences, and especially when they can discuss their related experiences.  Students’ shared demonstrations and experiences are often of great value to other students.

How is this different for online versus face-to-face classrooms?  To address this question, we need to differentiate between synchronous online courses — where faculty members and students are online together at the same time — versus courses where people’s presence is asynchronous.  There are several commercial platforms that can support synchronous classes to enable sharing of materials and discussions where people can see each other.

Asynchronous courses, almost by definition, have to be more scripted or canned.  This raises the question of the extent to which asynchronous courses can be fully interactive and reflect good educational practices.  Chickering and Gamson (1987) discuss seven principles for good practice in undergraduate education:

  • Encourages contacts between student and faculty
  • Develops reciprocity and cooperation among students
  • Uses active learning techniques
  • Gives prompt feedback
  • Emphasizes time on task
  • Communicates high expectations
  • Respects diverse talents and ways of learning

Roblyer and Ekhami (2000) have developed a rubric for assessing interaction in distance learning.  The rubric focuses on five aspects of distance learning:

  • Social/rapport building
  • Instructional design
  • Interactivity of technology
  • Learner engagement
  • Instructor engagement

They provide scales for each of these aspects where the assessment can provide up to five points per aspect and 25 points overall.

Wagner (1997) discusses interactions in terms of those between students and instructors, students and other students, and students and content.  She argues that interactions must change learners and move leaners toward an action state of goal attainment.  Interactions can increase participation, enable communication, provide feedback, enhance elaboration and retention, support leaner control/self-regulation, increase motivation, negotiate understanding, and enhance team building.  Interactions should be designed, or at least enabled, to support one or more of these purposes.

Expressed in these terms, technology is an enabler, a means rather than an end, for interactions that support learning and mastery.  Weidemann and Pollack (2016) argue that technology has become so ubiquitous that it is effectively disappearing.  Online tools from course management systems, to email list services, to web-based demonstrations are pervasively used in a large percentage of courses.  Thus, almost all education has online components.

It seems to me that we know what high quality education looks like, and we have some inkling of how to achieve quality for online offerings.  We also know that PowerPoint based didactic teaching does not pass muster.  To move beyond this, we need larger numbers of college instructors to embrace the principles and findings discussed here.

REFERENCES

Chickering, A.W., & Gamson, Z.F. (1987). Seven principles for good practice in undergraduate education. AAHE Bulletin, 3, 3-7.

College English (2016). http://www.collegeenglishbooks.com/two-models-of-teaching-learning.html, Accessed March 12, 2016

New Learning (2016). http://newlearningonline.com/learning-by-design/glossary/didactic, Accessed March 12, 2016.

Roblyer, M.D., & Ekhami, D. (2000). How interactive are YOUR distance courses? A rubric for assessing interaction in distance learning. Online Journal of Distance Learning Administration, 3 (2).

Wagner, E.D. (1997). Interactivity: From agents to outcomes. New Directions for Teaching and Learning, 71, 19-26.

Weidemann, C., & Pollack, K. (2016). The death of “online” learning in higher ed: As technologies become ubiquitous, familiar labels will vanish. University Business Magazine, March.

Autonomous Vehicles

Various pundits are projecting that by 2020 – just four years – the driving of cars and trucks will be completely automated.  Vehicle services, whether for consumers or businesses, will be readily available for very reasonable prices.  I will not need to own a personal vehicle and my business can dispense with its fleet of delivery trucks.  Taxi or truck drivers will no longer be professions; they will go the ways of elevator operators, bank tellers, and secretaries.

Personal cars are typically in use 5% of their lives.  The maturation of autonomous vehicles will cause utilization to approach 90-100%, dramatically reducing the number of vehicles needed to meet demands.   The greatly reduced number of vehicles will, in turn, enormously decrease the demand for independent servicing of vehicles – the vehicle service companies will handle this.  The number of gas stations, repair shops, and car washes will precipitously drop.

Reduced production of vehicles will result in the supplier base for vehicle manufacturers being steadily weaned due to less demands for nuts, bolts, rims, tires, floor mats, etc.  Auto insurance, the cash cow of the insurance industry, will be transformed once accidents cannot happen.  People will not pay to avoid risks that are no longer at all likely.  I have read projections that 5 million jobs will disappear.

This all seems plausible if the automation performs flawlessly.  Then, I can sit in the back seat and snooze on the way to the office, train station, or airport.  To evaluate this possibility, I have used my frequent Uber rides as an experiment where I ask myself, “What if there were no driver in the car?”  Two examples are very revealing.

I was going to the airport for a flight to Los Angeles.  The Uber app guided the driver to take a route that would have taken us away from the airport, not towards it.  I told this to the Uber driver and he said, “I have not driven this route before.  If you know a better way, just tell me what to do.”  Everything worked out fine.  What if there had been no driver?

More recently, I was taking Uber to work on a very cold morning.  I saw that the driver who would pick me up was just three blocks away and would pick me up in three minutes.  As I watched his car on my phone, it did not move and the time increased for 3, to 4, to 5, to 8 minutes.  I called him, and he said he would be there in five minutes, which he was.

Upon entering the car, I asked him, “You weren’t in your car when you responded to my request, were you?”  He responded, “No I was in my apartment, headed to my car in the parking garage.  It took me a few minutes to get there and then drive the three blocks to you.”  Driverless cars are unlikely to have apartments, but how will customers deal with departures from “normal” operations?

One extreme possibility is that drivers will be able to ignore vehicle operations until just before an imminent accident when the vehicle signals that the human driver should take over.  They will not have manually driven a vehicle in perhaps months and they now have a few seconds to get back in the loop.  Not surprisingly, this will not work. Decades of research have repeatedly shown this.

The impacts of autonomous vehicles on the overall economy will be pervasive.  The impact on the notion of “driving” will be profound.  We need to explore these futures deeply and carefully.  Like the canal barges, steamboats, railroads, automobiles, and airplanes, these changes will inevitably happen. How can we better understand and facilitate such changes to assure positive outcomes?

The Quartet

In “The Quartet: Orchestrating the Second American Revolution, 1783-1789,” Joseph J. Ellis chronicles the planning, drafting, and ratification of the US Constitution and Bill of Rights in 1789.  The title refers to George Washington, Alexander Hamilton, John Jay and James Madison.  These four men, with support from Robert Morris, Gouverneur Morris and Thomas Jefferson, led the transformation of thirteen colonies into a united republic.

It had never occurred to me that formation of the United States of America was not necessarily the outcome sought via the Revolutionary War.  The Continental Congress adopted the Articles of Confederation in 1777.  They were ratified by all thirteen states by 1781.  The thirteen states remained sovereign and independent.  The role of the federal government was limited to diplomacy and resolving territorial disputes.

The basic idea was to form a federation of thirteen independent countries, each with their own constitution, laws, processes, and so on.  Thus, during the Revolutionary War (1776-1783), the federal government had no power to raise troops and collect taxes.  Each state made its own decisions with regard to contributing troops and money.  The result was thousands of poorly equipped and unpaid soldiers.

Having escaped the reins of the British King and Parliament, the states were in no mood to reinstitute centralized governance and control.  However, the Treaty of Paris in 1784 required payment of pre-war debts and return of confiscated properties.  The credit ratings of each of the states were such that money could not be borrowed to address these needs.  The minimal central government could not borrow either because it had no sources of revenue.

The Treaty also resulted in the Mississippi River being the western border of the colonial territories.  There would eventually be 26 states east of the Mississippi.   However, there were at that time many competing claims on the less settled portions of these territories.  Virginia, for example, was quite aggressive in its territorial claims.  There was need for a mechanism to address claims and form new states.

Washington, Hamilton, Jay and Madison felt that the federation was at great risk of imploding.  Many European powers hoped this would happen, as they did not want the competition likely from a large united republic.  Ellis masterfully tells the story of how these four men planned and orchestrated a process that resulted in thirteen states voting for something that most of their citizens did not want.  Ratification of the Constitution and Bill of Rights in 1789 was the result.

The tension between states’ rights and federal governance is woven into the fabric of our national culture.  The Tea Party is just the latest manifestation of this tension.  The Constitution provides the means for addressing this tension but does inherently resolve it.  As Ellis explains, the quartet facilitated creating, in effect, a work in progress.

The Big Short

Just watched this movie this week, after having read many of the books published on the Great Recession, as well as having served on a National Academy study committee of what happened.  During this study, I had a chance to chat with the second most senior executive at one of the major banks involved, one that disappeared in the aftermath of the crisis.

I asked him if senior executives at his bank understood the questionable assumptions underlying the mortgage-based derivative securities.  He responded, “I understood, but we were making so much money from these securities that it was socially unacceptable to raise any questions.”  Put simply, they wanted to milk the real estate bubble as long as they could.

Of course, the bubble burst and millions of people lost their jobs and their homes.  The assets of the executives in these financial firms were protected.  They even received their usual bonuses, funded by the federal bailout of these firms.  Despite the obvious fraud by financial firms and rating agencies, almost no one was indicted and convicted.  Taxpayers paid, in one way or another, for the $5 trillion of lost wealth.

This movie certainly renews the anger felt in 2007-09.  I felt then, but less so now, that Goldman Sachs, Morgan Chase, Morgan Stanley, et al. should have been forced to fail, with top executives losing all of their personal assets and serving long prison terms, eventually emerging impoverished.  This would have been cathartic, but would it have made a difference in the longer term?  Would greed, fraud, and crime in general have been deterred?

The more fundamental question concerns the nature of value in our society and economy.  I have chaired, or been a member of, a few National Academy committees that wrestled with this question in terms of overarching goals for Academy initiatives.  We eventually agreed on one overarching goal:

To foster and sustain a healthy, educated, and productive population that is competitive in the global marketplace.

This goal is very compelling.  We want people to be healthy and engaged in work and making creative contributions in general.  To do this, we need people to be educated, as that is key to health and readiness for productivity.  People also need to be trained and aided to be productive and educated so they are competitive in the global marketplace.

My earlier post on “Five Million Jobs” outlines how we could accomplish these goals for 3% of the Federal budget.  I also discuss in that post why this obviously highly valuable investment will never happen.  The reason is simple – a sizable portion of our electorate feels that health, education, and productivity are now private goods, no longer public goods.  The idea that we all benefit by everyone being healthy, educated, and productive is no longer par of the national psyche.

So, let’s go back to The Big Short.  Was the financial community focused on improving health, education, or productivity?  More generally, were they providing value to society – and were they rewarded accordingly?  There is certainly value in providing capital to buy homes, start businesses, and develop inventions with potential to become market innovations.  Investors who provide this capital deserve reasonable returns for putting their monies at risk.

The financial community has various mechanisms for decreasing risks, for example, diversifying investment portfolios.  However, the financial players in The Big Short were hiding increasing risks, with the fraudulent compliance of the rating agencies.  These players created toxic portfolios of subprime mortgages.  The risks of default were steadily increasing, in part due to adjustable mortgage interest rates that resulted in payments that many borrowers could not possibly sustain.

The rating agencies helped the banks to hide ballooning risks, but savvy players realized that the bubble must eventually burst and sold these portfolios short. Some of our smartest people found a way to make billions of dollars betting that the marketplace would soon recognize the worthless investment instruments created by the financial community.  In effect, these smart people bet against the economy, against sustained value creation.

It is terrible when the smart money bets on failure.  Greed, fraud, and other criminal activities, in contrast to value, created this situation.  The financial community often talked value creation, but they did not walk it.  Instead, they focused on big paychecks, associated perks, and enormous bonuses.  In the end, they got to keep their windfall earnings while US taxpayers bailed out their enterprises.  Their homes in the Hamptons have kept them safely shielded from the broad loss of confidence they created.

NFL Denies Referee Conspiracy

There is growing evidence that NFL referees have been instructed to make calls – particularly pass interference calls and false start calls – to control the outcomes of NFL games.  The NFL vehemently denies these accusations, but the data are very clear.  The NFL knows the outcomes that will maximize television revenues as well as ticket and clothing sales, and they are determined to make sure these outcomes happen.

Our operatives have managed to make contact with people at Black Rock Big Data Analytics who provide services to the NFL.  None of these people would speak on the record, but they provided various insights.  A key manager said, “Keep in mind that this is all about entertainment, not athletics.  We are focused on earnings per share, not Hall of Fame inductions.  Our goal is to sell beer, pickup trucks, and game shirts.”

We asked, “What does this mean operationally?”  She responded, “The Patriots and Panthers were undefeated until recently.  We maximized the sales of game shirts, and then we needed these teams to lose because there were no more shirts to sell.”  She continued, “We instructed the referees to make sure these teams lost.”  They delivered, sales improved, and the referees got their bonuses.

“Doesn’t this conflict with the whole spirit of the game?” we asked.  The response was simply, “College and pro sports are the essence of corruption, exploiting talented athletes for maximal corporate earnings.”  So, we asked, “Does it not matter that millions of people are totally focused on their teams and their success?”  The response was simple, “Of course this matters.  Our goal is to maximize the percent of their income that ends up in the NFL coffers.”

Finally, our contacts added, “You realize that the whole athletics enterprise is focused on exploiting talented athletes, university presidents, and the general public to fill corporate coffers at the expense of the health and well-being of athletics and academia.  The idea of a student athlete is a farce.  All that matters is earnings per share.”

So, we asked, how far might you take this idea?  “Well, if we look at ultimate fighting, the extreme is death of the competitors.  This could generate enormous amounts of revenue.”  We could not help but ask, “Is this ethical?”  The answer was simple, “All that matters is earnings per share.  Dead athletes are just an insurance premium payment.”

The New Reality

Our operatives have uncovered the motivation and reasoning behind various presidential candidates now emphasizing what many of them are calling the “new realty.”  This reality relates to their personal histories, climate change, economic prospects, and so on.  All of the candidates have “repositioned” their personal stories to gain voter support.

One candidate, born to immense family wealth, tells his story of hardscrabble poverty and Horatio Alger like immersion from this poverty.  The media, their fact checking having discredited this story, finds itself dismissed by the candidate.  They have to ask questions and report answers in the context of this seemingly ridiculous reality.

Other candidates advocate policies, e.g., nuclear attacks on adversaries, which make no sense in terms of costs or consequences but are great pitches for support and votes.  Let’s build a wall between Mexico and the US, or between Canada and the US.  Great idea for construction companies that build walls!

There are lots of ideas about taxes.  The majority of Americans pay no taxes beyond Social Security assessments.  Thus, income tax revenues must come from everybody else.  How can we best redistribute income from earners with high incomes to everyone else?

Our tax policies shield many high-income people by designating their earnings as capital gains.  Thus, they pay 20% rather than 40% of their income in taxes.  The real victims are people whose incomes are designated salaries.  Between federal, state, and local income taxes, as well as property and sales taxes, these people can pay as much as 60% of their income in taxes.

The candidates have long argued for lower taxes, but it has all been just rhetoric.  The country cannot function without many high earners paying 60% in taxes while the majority of people pay 0% in taxes.  This is not going to change.  The minority of people with above average incomes is going to pay dearly to support everyone else.  Otherwise, the stability of the overall social system is at risk.

The candidates, from either political party, cannot embrace this reality.  The idea that we have to redistribute income to avoid social unrest is not acceptable, except for the fact that this is exactly what we do.   The reality is that a minority of people is positioned to benefit enormously from various technology and market opportunities; everybody else will find such changes challenging.  The political system needs to spread the benefits around.

Nevertheless, several candidates are advocating zero income taxes across the board, as well as zero corporate taxes.  They would create a national Value Added Tax.  They suggest 2% but replacing the lost revenue from income and corporate taxes would require a VAT of 15-20%.  Adding this VAT to state and city sales taxes could yield an overall tax of 30% on all consumption.  Commentators have pointed this out but candidates respond with putdowns like, “You need to take a math class.”

The rhetoric really soars when addressing defense spending.  Several candidates have advocated doubling the defense budget immediately.  They argue that this will pump money into the economy.  It has been pointed out to them that the absence of income and corporate taxes will mean that such pump priming will yield little revenue to the government.  They typically respond, “Good.  Less tax revenue the better.”

Candidates’ poll standings reflect the general public’s enthusiasm for the new reality.  The simple fact that the math does not work – the deficits would be immense – is of no interest to the public.  They are apparently believing and very much liking the rhetoric.

We decided it was time to explore the genesis of these audacious positions and promises.  Our operatives posed as representatives of potential European donors to the candidates’ campaigns.  It turns out that a potential donation of $10 million is the price for getting serious attention.  $100 million gets you a meeting with the candidate, but we did not need that.

We ended up meeting with three campaign managers.  We asked about the reality of their candidate’s positions and promises.  All three managers responded similarly, “We are trying to win the nomination and then the presidency.  Period.  We will take whatever position is needed to win convention delegates and electoral votes.”

But, we asked, “What if you win?  How will you deliver on your promises?”  They responded, “Promises?  If we win the presidency, the slate is clean. Whatever we said during the primaries and the election is irrelevant.  Once we are in control, we will do whatever we want.  At that point, the public’s preferences do not matter.”

So, we commented, “You are assuming a one term presidency?”  Their retort was, “Not at all.  Any shortfalls in delivering on promises can easily be attributed to the opposition.  We want to do the right things, but we cannot because the other party stymies our every move.”  We asked, “How do you know that will happen?”  Their response was, “It doesn’t matter.  We weren’t going to do those things anyways.”

This readily begged the question, “Why do you want the presidency if there is nothing that you plan to achieve?”  With a knowing smile, they each responded, “The key objective is to keep anybody else from accomplishing anything.  We want to keep government perpetually dysfunctional.”  We asked, “What’s the purpose of that?”  With a knowing look, they replied, “While the turmoil plays out, our donors and supporters will be making loads of money, which can help fuel the next round of this charade.”

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NFL Rules

Confidential sources have indicated that the NFL is considering some sweeping rule changes, all with a goal of increasing the entertainment value of the former sport.  Unnamed executives indicated that, “Our goal is for fans to have fun, to go home with memories of exciting games when their team miraculously won despite the odds against such outcomes.”

One conclusion was that home field advantage has to mean something more.  Consequently, the NFL is considering giving the home team five downs per possession, while the visiting team will still have only four downs per possession.  Purists have protested, but the NFL has reminded them that the focus is on the fans.  “Our sponsors want to sell beer and pickup trucks.  The home team winning is good for viewer retention.  If the home team is losing, fans tend to change the channel.  That does not sell anything.”

Another proposal receiving serious consideration is requiring both teams to wear identical uniforms without numbers or names on the jerseys.  This idea would so totally confuse players that miscues and mistakes would be rampant.  The idea emerged from some enthusiasts of America’s Funniest Home Videos.  The players union is adamant in their opposition to this idea.  One spokesperson said, “This is the most ridiculous idea since Bill Veeck tried midget players.”

Yet another extreme proposal is limiting each player, except the quarterback or kicker, from touching the ball more than once per game.  Each player gets one carry or one catch per game.  Enthusiasts have pointed out that this would give many other players chances to display their skills.  Naysayers respond that this would decimate the record books.  Almost no one could excel with one possession per game.

The Consolidated NFL Hall of Fame is studying this proposal.  Since the Consolidated Corporation acquired the HOF, they have changed many policies and procedures.  HOF members no longer vote on potential inductees to the Hall.  Election is now based on sales of apparel and accessories.  Not surprisingly, the result has been that players are elected in their first year of eligibility or not at all.  Once no one remembers them and their game shirts are not selling, players simply disappear from the collective consciousness.

The most controversial proposal by far would eliminate any play calling by coaches.  Head coaches, offensive coordinators, and defensive coordinators would be prohibited from directing plays.  The quarterback would be solely responsible for choosing and executing plays.  Any evidence that the coaching staff was trying to intervene in the calls would result in forfeiture of downs.  Two assessments would result in forfeiture of the game.

The backdrop for all these deliberations is the desire to increase fan enjoyment and commitment.  Everyone wants their team to make the playoffs.  Another proposal being considered is that every team makes the playoffs.  Further, each round of the playoffs would be the best two of three games rather than a single game.  The three games would be played in a one-week period.  This would push the Super Bowl into April or May.  This would yield a windfall of revenue from advertising and ticket sales.

Finally, initial ideas are emerging for decreasing the current 12 minutes that the ball is in play during a typical three hour telecast.  Another 2-3 minutes of advertising time would be highly valuable.  The most popular suggestion was to eliminate stopping the clock during a series of downs and then adding an additional minute of advertising between each of the four quarters.  Enthusiasts argue that the faster-paced game would be more exciting.

Overall responses of fans to these suggestions have been quite negative.  One fan said, “If you make the real game so short and I only get to see my favorite player once, how am I going to be able to justify three hours of drinking beer and scarfing junk food?  I already have a new pickup truck.”  Another fan remarked, “Well, at least these changes will reduce injuries.  Football is just an excuse to hang out with my friends anyways.”

Disruptive Service Innovations in Healthcare

A recent issue of The Economist provided an in-depth review of how high technology financial startups are poaching high-margin financial services from large banks.  The large banks are not standing still; they are often acquiring these startups once they prove viable.  This may keep them in the game, but high margins are being substantially eroded for services that were once cash cows.

There have been many related discussions in the vehicle industry.  Many vehicle manufacturers are trying to position their vehicles as service platforms.  OnStar by GM is a classic example.  As more high-tech vehicle services emerge, it may be that Apple and Google, for example, will be the innovators rather traditional automobile companies.  They won’t produce the cars, but they will make the profits.

Both of these examples involve industries with business models, especially cost structures, which overprice technological innovations, yielding profit margins that can compensate for enormous inefficiencies elsewhere throughout their enterprises.  In general, disruptive technology-based innovations can obsolete business models and displace mainstream providers who are deluded by the incumbency of their traditional approaches to their markets.

There is a significant opportunity to disrupt the business models of consulting service companies that provide business process improvement services to healthcare providers.  The disruption will completely undermine the construct of the “billable hour” for these services.  Consider these observations:

  • Healthcare providers are notoriously inefficient users of capacities, in part because they get paid for everything they do regardless of relevance or efficiency.  Any reasonably competent process engineer can see countless low hanging fruit in terms of process improvements.
  • All major healthcare providers are delivering the same services, i.e., caring for the same maladies of humans ranging from hypertension, diabetes, and heart disease to automobile accidents and gunshot wounds.  There is no inherent reason that they could not all provide these services in the same ways.
  • Such standardization has led to major efficiencies and increased effectiveness for sales force automation, logistics, supply chain, and inventory management, and numerous other industrial processes.  Healthcare delivery is ripe for such process innovations.

It is important to differentiate process innovations that involve direct adoption of, for example, logistics, supply chain, and inventory management, from those innovations that address healthcare delivery specifically.  The latter must draw upon evidence-based medicine to devise, evaluate, and generalize care processes for hypertension, diabetes, heart disease, etc.  Standardizing such services requires deep knowledge of diseases and procedures for screening patients, diagnosing disease states, and treating diseases.

One approach to standardizing care delivery processes has been to map the processes of each provider, leading to one-off solutions for each enterprise.  These process maps are used to identify process inefficiencies, redesign processes to eliminate inefficiencies, deploy new processes, and then evaluate both efficiency and effectiveness.  This usually requires an enormous number of consulting person-hours and, hence, is very expensive.

This approach is based on the idea that every provider is unique and, of course, every patient is unique, and only the knowledge and skills of their individual primary care physicians and specialists are adequate to know how best to treat an individual patient.  Such reasoning is deeply flawed.

The Institute of Medicine has found the following — from the time that a new best practice is proven until the majority of physicians have adopted the practice averages 17 years.  Other studies have shown that physicians’ approaches to care are much more affected by where they graduated from medical school than by research findings since they graduated.  Thus, most patients are not getting the best care.

To be fair, various thought leaders have shown that it is absolutely impossible for clinicians to keep up with the developments in their specialty.  They could spend all their time reading and still not be able to keep up.  The individual clinician, despite high motivation and commitment, simply cannot keep up with the generation of medical knowledge and delivery skills.

It might be argued that the medical literature provides all the knowledge needed to specify best practices.  However, the literature focuses on scientifically defensible knowledge rather than how to deploy this knowledge in the care delivery system.  The need to translate increasing knowledge to constantly improving best care practices presents an enormous business opportunity.

This opportunity is premised on the strong belief that there are definable best practices that every provider should follow.  These best practices can be identified and constantly updated.  Knowledge of these best practices can be deployed in terms of web-based interactive visualizations enabled by computational models that embody these practices.  Clinicians can interact with these visualizations, perform any desired “What if?” experiments, and assess the impact of updated best practices on health outcomes and financial consequences.

Once decision makers are convinced of the merits of the best care practices portrayed in the web-based interactive visualizations, it is inevitable that many will ask about how these practices can be customized to the demographics of their patient populations.  Much of this type of customization can be enabled online. Other types of customization, e.g., to their physical infrastructures, may be difficult to fully automate, at least initially.

The fully customized version of a provider’s processes and practices can be created and maintained online for their use in strategic and operational management.  Parameters within these processes and practices can be updated monthly.  Performance outcomes can be compared to predicted outcomes.  Deviations can be used to track down performance problems, for example, unusually long delays for out-patient diabetics.

The vision is to provide to medical practice what SAP provides to logistics, supply chain, and inventory management and Salesforce.com provides for sales force automation.  This will require a combination of compelling online capabilities with deep knowledge of medical practice, as well as an efficient and fine-tuned mechanism for constantly updating knowledge of the state of the art in medical practice.  In the process, the 17 years it takes to for the majority of clinicians to adopt best practices should be reduced to perhaps six months.  This will be a major contribution.

Leading a University Research Center

University research centers are delicate organizational systems.  They bring together faculty, research staff, and graduate students for several reasons.   Centers are often formed as a result of a large NIH or NSF grant or because of a large gift or grant from industry or wealthy alumni.  So, there is money on the table and researchers are naturally attracted to funding.

Researchers can also be attracted to the research agenda of the center.  They like the center’s portfolio and other researchers involved and want to affiliate with the endeavor.   This is also true for graduate students, who are often attracted to the research portfolio but also looking for graduate assistantships.  Prudence is needed to identify students who have the potential to make real contributions.

I have found that any university will embrace a research center that is totally externally funded and places no demands on the university.    Such centers provide resources, at least in terms of overhead, to pay for use of the brand on letterhead and brochures.  If all goes well, they hit a homerun; otherwise they quietly fold after the external resources are expended.

Universities tend to have two strategies.  For things that they view as mission critical, e.g., nanoscience and genomics, they will invest far beyond any possible returns – except bragging rights.  Other things have to earn their way onto the agenda, typically by paying returns far in excess of required investments.  This excess is used to further fund mission critical areas.

If your assignment is to run a university research center, here is some advice.  First, determine whether or not you are mission critical.  If you are receiving resources in excess of what you generate, chances are you are mission critical.  If you are, in effect, paying taxes on the resources you generate, you are a cash cow, at least as long as the cash lasts.

If you are mission critical, your success is assured – the university needs you to succeed and needs to trumpet your success.  If you are a cash cow, consider alternative futures.  A commercial spinoff might make sense.  Another possibility is to move the whole center to another university.   This might seem like being disloyal, but keep in mind that you have enjoyed little loyalty thus far.

While you are still a cash cow at your university of origin – where the center was founded – there are several tactics worth considering.  First, do your best to avoid taxes.  A primary mechanism to achieve this is to secure funds that allow no overhead charges.  Since you are not getting a share of overhead, why contribute to the pool?

Why would universities accept such stipulations?  Quite simply, they cannot walk away from money on the table.  Money received in this way makes you less of a cash cow.  However, you are not getting a share of the milk – or meat! – so why should your research center contribute?  If you are really good at this, you will find the university administration wanting to talk about how they can better support you.

When I was 12 or so, I came home from Charlie Boyd’s farm with a pigeon under my arm.  I proclaimed to my mother, “Charlie Boyd gave me a pigeon!”   My mother responded, “He didn’t give you a pigeon, he got rid of a pigeon.”  If you are directing a research center, especially one newly founded, you need to learn how to identify and avoid pigeons.

Pigeons, in the context of university research centers, are faculty members who are difficult to work with and/or consistently underperform.  Deans and department chairs often tend to recommend pigeons to research center leaders.  If you manage to transform their attitudes and performance, you have solved a problem for the dean or department head.  If not, it is now your problem.

One of the primary objectives of the leader of a research center is brand development.  You want the broad community to see your center as a prime time player in the areas of its research and teaching.  My experience is that the university will not help you with this.  Their marketing and communications staff members are oriented to serving the needs of the president, provost, et al.

Thus, you need to identify the constituencies with whom you want to communicate, develop the messages and associated packaging to communicate with these constituencies, and create the capabilities and opportunities to communicate. You will, of course, be the primary one to deliver these messages.  However, getting other faculty members involved with this messaging can contribute enormously to fostering a shared mental model of the center’s vision.

As soon as possible, you want to get to the point that you are not writing all proposals and leading all projects.  Mentoring faculty members, particularly junior faculty members, is the way to grow these competencies.  An important aspect of this is providing them opportunities to present their research to senior audiences from industry and government, not just academia.  Speaking skills, as well as writing skills, benefit from frequent opportunities to use them.

Finally, as the leader of a research center you should invest little time enhancing your resume and much time doing things that improve others’ resumes.  Your center needs to be vehicle for personal growth of faculty, staff, and students.  The outcomes from your center may include many articles, books, patents, etc., but the primary product of a university research center is the people who employ their knowledge and skills to address the needs of society, typically from a long-term perspective, but nonetheless as contributions to the common good.

Thoughts on Location

Does location matter?  It depends on what you are seeking.  If economic opportunity is your yardstick, here are some interesting statistics.

Greater New York City generated $1.5 trillion in GDP for 2014.  Greater Los Angeles provided $0.8 trillion; greater Chicago $0.6 trillion; greater Houston and greater Washington, DC $0.5 trillion each; and greater Dallas, San Francisco, Philadelphia, and Boston $0.4 trillion each.  The total US GDP for 2014 was $17 trillion.  New York City generated roughly 10% of this, and these nine metro areas generated over one third of the country’s GDP.

Most of the government research-funding agencies are in Washington, DC, as are many foundations.  A large percentage of research-funding foundations and potential Fortune 500 sponsors are in New York City. The top five homes of Fortune 500 companies include California (54), Texas (52), New York (47), Illinois (33), and New Jersey (28), accounting for almost half of the Fortune 500.  New York and New Jersey account for 16% of the Fortune 500.

High tech cities, ranked by numbers of jobs, are San Jose (Silicon Valley), Seattle, Boston, Washington, Los Angeles, Dallas, San Diego, Orange County, New York, and San Francisco.  Silicon Valley once dominated in IT related jobs but has been losing jobs as companies migrate.  The majority of aerospace and defense companies are on the West Coast – Arizona, California and Washington — although their headquarters have migrated to the east, mainly to Washington, DC, but also Chicago.

In the Sun Belt, Atlanta companies include AT&T Mobility, Coca-Cola, Delta Airlines, Home Depot, NCR, Newell-Rubbermaid, Southern Company, Turner, and UPS.  These companies are focused on transportation, supply chain and operations issues.  Dallas companies include Advance PCS, Dean Foods, ExxonMobil, Kimberly-Clark, Neiman Marcus, Southwest Airlines, and Texas Instruments, a quite diverse mix.  Houston companies include Phillips 66, Conoco Phillips, Sysco, Halliburton, Baker Hughes, and Marathon Oil, obviously reflecting a strong energy sector.  Charlotte is the second largest banking center after New York City.

Multiple healthcare providers are in all major cities. The top ten cities for healthcare employment, in rank order, are Houston, Philadelphia, Baltimore, Boston, Milwaukee, Denver, Fargo (ND), New York, Cleveland, and Norfolk.  Healthcare is the largest employer in Pittsburgh.  Seven of the 25 largest employers in New York City are healthcare providers.

The essential tradeoff is economic opportunity versus cost of living.  The Cost of Living Indices for each region’s major cities are shown below.  The average index nationally is set to 100.  A major contributor to high or low values is the cost of housing.

  • Northeast: New, York (Manhattan, 217; Brooklyn, 182; Queens, 159), Hoboken (183), Washington (140), Boston (133), and Philadelphia (127)
  • West Coast: San Francisco (164), San Jose (156), Orange, County (146), Los Angeles (136), San Diego (132), and Seattle (121)
  • Midwest: Chicago (117), Minneapolis (110), Denver (103), Salt Lake City (101), Kansas City (98), Cincinnati (94), Pittsburgh (92), and St. Louis (90)
  • Sun Belt: Miami (106), Phoenix (101), Raleigh (98), Atlanta (96), Charlotte (93), Houston (92), and Dallas (92).

Clearly, the large Sun Belt cities offer jobs and low costs of living, with a major contributor being significantly lower costs of housing.  The Northeast and West Coast have lots of job opportunities but are very expensive places to live.  The Midwest is closer to the Sun Belt in costs, but not in terms of job opportunities.

Pundits’ Performance

There is a wealth of self-proclaimed pundits providing pronouncements on sports, politics, the economy, and so on.  There seem to be unlimited numbers of Democrat and Republican strategists.  Some are wizened pros that have been through many campaigns, some successful and some less so.  Many are quite young.  Despite having seemingly no credentials, they are happy to make sweeping pronouncements about global warming, same-sex marriage, and tea party turmoil.

Editorial writers for major newspapers seem to be better informed and balanced, and are usually quite transparent about their liberal or conservative leanings.  They are usually clear about their opinions versus observations based on data.  My experience has been that print journalists are much more thought provoking that television or radio journalists.  Writing takes much more discipline than speaking.  Of course, reading also takes more discipline than listening.  Sound bites are much more likely to be misleading.

Sports pundits are rather different.  Many are former professional athletes or coaches.  So, they have reasonable credentials.  Their prognostications are readily evaluated by the outcomes of the sport they follow.  The successes of their predictions are tabulated and reported.  They tend to do a bit better than just flipping coins, but are seldom highly successful.  Nevertheless, fans seem to enjoy their banter and tune in regularly.

How are pundits judged?  Expecting their predictions to be correct is a tough yardstick.  We can assess whether or not sports pundits’ predictions are accurate.  However, it is difficult to evaluate the statement by the 28-year-old Republican strategist that global warming is a hoax and same-sex marriage will lead to the end of civilization.  It is equally difficult to judge the equally young Democratic strategist pronouncement that income inequality will likely lead to a revolt of the downtrodden.

It may be that people like pundits whose pronouncements agree with their positions and whose choices of positions and articulations are entertaining.  People are not looking for enlightenment.  They want to feel comfortable in their preconceived opinions and entertained in the process.  It is not about fact-finding journalism.  It is about intellectual comfort food with a few laughs thrown in for entertainment.

The Economics of Retirement

My last post addressed my frustration with a 60% taxation rate that left me wondering if my role was mainly to provide resources to be redistributed to other, undoubtedly needy, people who do not pay taxes.  The 40% that I get to spend barely covers my financial commitments.  So, how do I ever get ahead of the game and retire when I am 75 or 80 years old?

Many people are asking this question.  The number of highly educated older seniors delaying retirement has soared, resulting in an income tax windfall for the government that has helped fund the early retirement of less educated people caught by the Great Recession and unable to find employment.  Despite the recent recovery, such seniors continue to delay retirement.  What choices do they have?

One scenario is to simply die with their boots on, provide various life insurance proceeds, and accept the tax folks scarfing up their portion of the proceeds.  Another scenario is to make sure they end up poor.  Give away everything.  Leave themselves wards of the state.  Do their best to assure the state pays for hip, knee, kidney, and heart transplants.  Could be pretty expensive.

I can imagine this becoming a sport for baby boomers.  How much can you cost the system?  What percent of lifetime taxes paid can you recoup via medical expenses paid?  If you can exceed 100%, you get a free heart transplant or an evening with an aging Hollywood star.  If you identify a mechanism that others can use, you get an additional double hip replacement and an annual evening with aging Hollywood stars.

Of course, all of these whimsical ideas are avoiding the central issue.  We need the capable folks to provide the resources for the 50%+ of people who cannot be net contributors.   There is obviously a point at which the capable people will balk.  However, such people have demonstrated abilities to game the system in ways that minimize the number of capable earners who walk away from continued earning.  They find loopholes, which once closed, lead them to find new loopholes.

Underlying this dilemma are three compensating phenomena – people who are really capable, motivated to work very hard, and sufficiently insightful to identify opportunities for innovation – see Malcolm Gladwell’s Outliers.  These types of people change the world. Everyone else, in effect, lives off the consequences of these phenomena.

Well, it is not at all that simple.  If the masses of workers do not have the income needed to consume, markets will not have the scale to enable cars, airplanes, and smart phones.  Henry Ford identified this need a century ago when he doubled wages to $5 per day, although his primary motivation was to reduce the substantial employee turnover he was experiencing.

We need masses of people who are willing and able to consume.  Carnegie, Ford, Morgan, Rockefeller, and Vanderbilt depended on this.  Bezos, Brin, Gates, Jobs, Page, and Zuckerberg more recently have depended on people to consume.  Thus, income redistribution via taxes is essential to the economic growth of the country.  Our consumption-driven economy totally depends on people consuming – buying more and more stuff.  This, in turn, depends on people having incomes sufficient to enable the needed consumption.

What does this mean for the economics of retirement?  The success of my attempt to recoup my retirement investments lost to the real estate bubble has been diminished by the unexpected heavy taxation on my “homestretch” income.  In fact, I have to use retirement assets to pay the increased taxes, so the nest egg is decreasing rather than increasing.

In other countries, there is a substantial value added tax on consumption that provides a large percentage of the government’s income.  This tax on consumption is often called regressive, as it is indifferent to the income of the consumer.  The benefit to someone close to retirement is that you can choose to not consume, e.g., not buy a new car or engage in expensive travel.

Yet, this does not address the dilemma.  Income redistribution is essential to a civil society. Without redistribution, the impoverished inevitably revolt at the ballot box or in the streets. However, there is another solution — full employment and well-paying jobs. This may sound utopian, but it is not. See my earlier post “Five Million Jobs.”

Income Taxes

Over the past three years, my tax rate has increased to over 60% of my income.  This includes Federal and State Income Taxes, Social Security Taxes, Workmen’s Compensation, Medicare Tax, Sales Tax, and Property Taxes.  This tax rate, combined with the costs of living in an area where I earn a high enough income to pay over 60% taxes, has given me some pause.  The amount remaining after taxes, and high rents, provides for Ramen noodles and an occasional beer.

This post reviews various “theories” of taxation, starting in the late 19th century.  All of these theories recognize the difficulty of high rates of taxation decreasing the motivation of high earners to continue earning.  For example, at a 100% tax rate, the government could redistribute all income to meet its obligations.  In fact, incomes would no longer be individual citizens’ incomes; it all would be the government’s income.

Government could then provide citizens their daily Ramen allocation – probably no beer though.  People would work their 10-12 hour days, eagerly looking forward to their Ramen, and a bit of rest before the next day.  People could even work seven days per week.  Why not?  Such a scheme would provide the resources needed to redistribute income to the 50%+ low-income Americans who pay no income taxes.

I could see many of the “powers at be” being quite excited about this model.  The most capable people would be indentured to support the least capable.  This is not a new idea.  Many people have thought about this possibility over the past 100+ years.

Edgeworth (1897) discusses what he terms the pure theory of taxation. Written before the 1913 establishment of U.S. federal income tax, he focuses on taxes on the consumption of goods and commodities.  Invoking the principle of equal sacrifice, he assesses impacts of taxes on each stakeholder.  Equal sacrifice is defined as each taxpayer losing the same utility to the tax collector – in other words, the goal is equality of perceived pain for each taxpayer.

Ramsey (1927) continues this line of reasoning.  He is concerned with the following:  Given a bundle of goods and commodities, how to design the differing tax rates on each type of item to minimize loss of utility of those taxed.   He mathematically shows that “the taxes should be such as to diminish the production of all commodities in the proportion” (p. 54).  The key point here is that taxes on goods and commodities will diminish consumption of them.

Mirrlees (1971) explores the theory of optimal income taxation.  He presents a mathematically rigorous approach to determining optimal progressive income taxes such that taxes impose equal utility losses on everyone.  Individuals have a utility function for consumption (x) and time worked (y). An individual of ability n is paid ny for his or her work.  The government imposes an income tax percentage of c(ny) on this income.  The overall result is that a c(ny) function that is linear in rate progression is near optimal, unless “the supply of highly skilled labor is inelastic.”

Mirrlees suggests, however, that greater equality could be achieved by taxing people by ability to earn income, perhaps proportional to IQ, rather than actual income.  He argues that this would be “an effective method for offsetting the unmerited favors that some of us receive from our genes and family advantages.”  The difficulty that Mirrlees is trying to overcome with this idea is that high tax rates are likely to discourage high ability people from maximizing their earnings, thereby undercutting the tax revenues that were expected from them.  Taxing by IQ, in theory at least, implies that people would have to pay taxes on what they could earn even if they chose not to earn these amounts.  It is, of course, very difficult to imagine this ever being implemented – but is it?

More recently, Feldstein (1982) and Summers (1981) address the impacts of tax rates and inflation on investments. Feldstein argues that, “Inflation creates fictitious income for the government to tax” (p. 154).  Taxes are paid on inflated returns while investors only gain real returns.  In this way, a positive real return can become a net loss once taxes are deducted.

Summers (1981) discusses trends in business investments versus those made to satisfy regulations, e.g., pollution control.  The investment rate in the 1975-1979 period was 3%, the lowest in three decades.   Total taxes (on corporate profits, dividends, and capital returns) declined from 71.5% in 1953 to 52.7% in 1979. Inflation soared, “In a tax-less world, firms invest as long as each dollar spent purchasing capital raises the market value of the firm by more than one dollar” (p. 77).  However, as Feldstein notes, high inflation rates undermine this possibility.

Much more recently, Mankiw, Weinzierl, and Yagan (2009) discuss optimal taxation in theory and practice. They argue that, “The social planner has to make sure the tax system provides sufficient incentive for high-ability taxpayers to keep producing at the high levels that correspond to their ability, even though the social planner would like to target this group with higher taxes.”  They report a range of lessons from their review: 1) optimal marginal tax rate schedules depend on the distribution of ability, 2) the optimal extent of redistribution rises with wage inequality and 3) optimal taxes should depend on personal characteristics as well as income.

Thomas Piketty has focused on income inequality and capital taxation (Piketty & Saez, 2012; Piketty, 2014), with his 2014 book receiving an enormous amount of attention.  They focus on “socially-optimal capital taxation,” on both savings and bequests, to deal with the problem of a “large concentration of inherited capital ownership.”  They assert that, “Inequality permanently arises from two dimensions: differences in labor income due to differences in ability, and differences in inheritance due to differences in parental tastes for bequests and parental resources.”

They show that the “socially optimal” tax rate on inheritances, TB, can range from 40-60% to 70-80% when bequests are highly likely.  Increasing TB allows decreasing the tax rate for labor, TL.  For a 20% bequest probability, TB = 73% and TL = 22%.  Their model also includes a tax rate for capital gains, TK.  They consider how people shift income from monies subject to TL versus TK.  They find that the optimal TK increases with uncertainty about future returns due to TB.  They also consider a consumption tax, TC.  This tax can enable TL < 0, which implies a labor subsidy for low-income people.

Of course, whatever schemes are proposed for TB, TL, TK and TC, high ability people will figure out how to take advantage of these schemes, effectively thwarting income redistribution.  People with high incomes and/or wealth, will have the resources to hire high ability people to figure this out for them.  Thus, any scheme is subject to “gaming” and adaptation will inevitably be necessary.

So, is my frustration with my 60% tax rate justified?  I clearly am doing my part to help with income inequality.  Further, I am still working; so the tax rate has not reached the extent to which I have given up trying.  Of course, I am keenly aware of my financial commitments.  The 40% that I still get to spend covers many things.  There is a point, however, where living in a high cost of living area to earn a highly taxed income is no longer worth it.

I have a vague sense that the taxation system understands this, if only implicitly.  The intention is to squeeze as much revenue as possible from highly capable earners to just before they are no longer willing or capable.   Upon retirement, the taxation system will drain taxable resources from former earners via one mechanism or another, e.g., required Medicare charges linked to income.  It almost seems that the system will, if possible, create penniless citizens just as they draw their last breadths in nursing homes, having no assets and supported by Medicaid.

There are various mechanisms to fend off this future.  Trusts can be formed and foundations can play a role.  However, perhaps with the exceptions of the super rich, the system is designed to suck resources from capable people who earned them and redistribute these resources to people who need them.  Interestingly, this redistribution leads to a subset of these under-resourced people becoming enormously successful and then being subject to the same dynamic.

The redistribution of resources keeps society from rebelling.  High ability folks – creative and crafty – understand how to prosper.  The social and political system knows how to balance idea generation, venture formation and allocation of resources, while also redistributing income to support those who, for one reason or another, cannot compete.  Those losing income, like me, gripe and complain but, as the long history discussed above illustrates, redistribution is a necessity of modern society.  The mechanisms and magnitudes are debatable, but the phenomenon is not.

References

Edgeworth, F.Y. (1897). The pure theory of taxation. The Economic Journal, 7 (25), 46-70.

Feldstein, M. (1982). Inflation, capital taxation and monetary policy. In R.E. Hall, Ed., Inflation: Causes and Effects (pp. 153-168). Chicago: University of Chicago Press.

Mankiw, N. G., Weinzierl, M., & Yagan, D. (2009). Optimal taxation in theory and practice. Journal of Economic Perspectives, 23 (4), 147-74.

Mirrlees, J.A. (1971). An exploration of the theory of optimal income taxation. The Review of Economic Studies, 38 (2), 175-208.

Piketty, T. (2014). Capital in the Twenty-First Century. Cambridge, MA: Belknap Press.

Piketty, T., & Saez, E. (2012). A Theory of Optimal Capital Taxation. Cambridge, MA: National Bureau of Economic Research, Working Paper 17989.

Ramsey, F.P. (1927). A contribution to the theory of taxation. The Economic Journal, 37 (145), 47-61.

Summers, L.H. (1981). Taxation and corporate investment: A q-theory approach. Brookings Papers on Economic Activity, 1, 67-140.

Reflections on New York City

I am on the homestretch of being in New York City for three years, actually in the bleachers of Hoboken watching the game played by this remarkable city.  For over 400 years, it has been an innovation ecosystem embracing change, creativity, and diversity.  The only colony without a religious or political agenda, New York City was, and still is, focused on commercial success.  Your religion and politics did not matter – and still do not matter.  Abilities to attain power and make money mattered – and they still do.

One element of the City’s success has been constant change in the gene pool of its citizens.  The endless stream of immigrants was at first dominated by the Dutch, then the English, and in the 19th century by the Irish, then Germans, and then Italians, followed by Eastern European Jews, and more recently in the 20th century by Blacks, Hispanics and Asians.  The resulting diversity is truly astounding.  A walk on the City’s streets displays every skin color imaginable.  The idea of race becomes completely lacking in meaning.

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As impressed, perhaps awed, as I am of New York City, there are drawbacks.  The city is quite dirty, noisy and, in general, rather untidy.  People are always in a rush.  Watching people trying to get out of the city on a Friday afternoon is like viewing panicked lemmings with horns, not extensions of the skull, but technological noise-making devices.  I cannot help but speculate on the potential benefits of banning personal vehicles in Manhattan.

The city is also amazingly expensive.  Everyday staples are reasonable, but everything to do with real estate is overwhelming.  Purchasing or renting a place to live is off the charts.  Property taxes make mortgages look modest in terms of monthly payments.  Income taxes are not for the faint hearted.  It costs a lot to run this complex city and it often feels that you are the main source of municipal income.

I was recently part of a dinner discussion of the costs of living in the City.  One person who had recently moved to Manhattan mentioned that she had looked at a building where the monthly condo fee was $50,000.  Everyone gasped.  She said that you could endure this expense by just thinking in terms of buying the management services company a BMW every month.  Few of the people around the dinner table felt that this characterization made the idea more palatable.

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Politics in greater New York City, including northeastern New Jersey and southwestern Connecticut, have always been complex and messy.  Centuries of massive immigration have created a wide range of political camps and mechanisms for achieving desired ends.  A good example is provided by the ways that Tammany Hall looked after the interests of Irish immigrants.  Of course, the Tammany leaders also made sure that they personally benefitted from these political shenanigans.

The constant flood of immigrants into the City seeking economic opportunity results in modest population growth despite the steady flow of people out of the City to the suburbs and elsewhere, for example, the Sun Belt.  Most immigrants start at the bottom of the economic ladder.  Once they make it up a few rungs, and have a couple of children, many move to the suburbs or elsewhere in search of larger and less expensive housing, better schools and more opportunities for their children and, in general, the American Dream.

Many still have economic ties to the City and commute from the suburbs to Manhattan each day.  1.6 million commuters each day double the daytime population of the island.  Nevertheless, the suburbanites’ political issues morph from urban issues of fair housing, rent control, and so on to property taxes, school concerns, and especially transportation infrastructure to lessen the pains of their daily commutes.  The overall result across greater New York City is fragmentation of political interests in terms of who gets what benefits and who pays for them.

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I was born on the island part of Rhode Island, rather than the Providence Plantations part.  From Fort Butts, a high earthworks from the Revolutionary War, we could see the Sakonnet River to the East and Narragansett Bay to the West and North.  There were two bridges to and from the island on the north end, and a ferry at the south end in Newport.  Water and boats were pervasive on the island.

My relationship with water is deeply seated and hence my affinity for the Hudson, East, and Harlem Rivers, as well as Long Island Sound.  My great-great grandfather’s Fall River Line steamboats provided overnight service from Fall River to Newport, then into the Atlantic, and through the Sound to the East River, and then to the Hudson to dock at Piers 18 and 19.  I can see where these piers were from my office window at Stevens Institute of Technology, five stories above the western shore of the Hudson.

A couple of boat tours of the City, as well as many walking excursions, have easily displayed the ways in which water has been and is integral to the fabric of the City.  Getting over or under one or more rivers is a daily task for millions.  Countless business ventures took advantage of and sometimes abused these rivers.  The ebb and flow of the Hudson in particular affects river traffic to the head of the tide in Troy, 140 miles to the north.  The power and beauty of the water are transcendent.

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New York City used to be the largest port in the US – a position gained with the opening of the Erie Canal in 1825.  Now it needs to join with New Jersey to be in second place behind Los Angeles/Long Beach.  The shipping container was the culprit.  The container eventually decreased the cost of shipping by 90%+ per pound, but Manhattan had no place to stage containers, much to New Jersey’s benefit.  Employment of longshoremen was decimated in the City and elsewhere.  Manufacturing jobs in the City plummeted.  If you can move things so cheaply, why assemble them in a high cost place like the City?

The dramatic loss of manufacturing jobs, in parallel with energy crises, cheap labor in the South, increased global competition, and decreased defense budgets, created great economic stress for the City in the 1960s and 1970s.  Over 10% of the population left.  The City’s service sector eventually led the rebound — finance, law, public relations, advertising, publishing, and entertainment.  Dramatic increases of immigrants from Puerto Rico, Dominican Republic, and Asia replaced the out migration to the suburbs and Sun Belt.

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Weather is a challenging aspect of New York City.  I grew up in the northeast – Boston and Rhode Island – so I felt prepared for the weather in New York City.  I was wrong.  The wind down the Hudson is unforgiving.  Silk long underwear is a necessity.  Without a car, iced sidewalks and intersections result in very slow walking.  Falls are anathema to people my age and it requires significant effort to be careful.

Summer is also a challenge.  One would think that winter represents “dues paid” for a pleasant summer.  However, June and especially July are as unbearable as summer in the south, enough so that I need to bring changes of clothes to the office so that I can shed sweat-drenched clothes from the walk to the office.  Mercifully, by mid August, one can sense Fall coming and changes of clothing are no longer necessary.

The weather also makes traveling more complicated, more so for airline travel then the trains.  Winter snowstorms and ice can completely bog down airports.  Summer thunderstorms, not to mention hurricanes and nor-easters, also wreck havoc.  Delays at airports get longer and longer, and people get increasingly frustrated and angry.  Enormous amounts of time are wasted.

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Diversity and creativity are the hallmarks of the City.  This can be seen in many ways.  Certainly the architecture of the City displays the richness of ideas for urban form and function.  The number corporations headquartered in greater New York City, as well as the number of professional sports franchises, are also indicators.  The best measure, however, is the breadth and depth of creative contributions by people.

The industrial tycoons such as John Jacob Astor, J.P. Morgan, John D. Rockefeller, and Cornelius Vanderbilt are well known.  Beyond these captains of industry, the City has benefitted from many creative contributors in cosmetics (Elizabeth Arden, Helena Rubenstein and C.J. Walker), fashion (Hattie Carnegie and Ralph Lauren), entertainment (Samuel Rothafel and Florenz Ziegfeld), performance (Leonard Bernstein and Duke Ellington), publishing (Bennett Cerf and Horace Liveright), and media (William Paley and David Sarnoff).  These are just a few members of an enormous cast of creative and influential people who have woven the fabric of New York City.

Why New York City, rather than Boston or Chicago, for instance?  Urban economist Edward Glaeser provides the answer. “The tendency of people to attract more people is the central idea of urban economics, and nowhere is that idea more obvious than in America’s largest city.  New York’s remarkable survival is a result of its dominance in the fields of finance, business services, and corporate management. Finally, and most spectacularly, for almost 200 years, the success of New York owes a great deal to the city’s role as a place where the latest news can be picked up quickly.”