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?”


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!”

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