Genius and Big Data have limits.

It’s easy for a person to wish they were smarter.  If only each of us were smarter, wouldn’t it be easier to solve all of our problems?  But it’s probably not just a question of smarts.  It may also be a problem of limited time and also what kind of temperament a person has.  Here’s something to think about that might help in understanding the likely impact of Big Data, and perhaps the disappointing outcome of trying to make humans smarter by using Big Data.

We all know that some humans are geniuses.  But if you imagine making a genius smarter, would that person be able to accomplish more in their lifetime?  For instance, if we could install a computer chip into a genius’s brain to give them more smarts…I’m thinking of people like Leonardo Da Vinci or Sigmund Freud.  As we think of Leonardo and Freud we can’t help but notice that they aren’t a genius of everything.  Leonardo Da Vinci was a genius of science and mechanics but not psychology.  Sigmund Freud was a genius of psychology but not of science or mechanics.  They both knew something about anatomy but each of them was inclined to study and excel in a specific area and they spent all their time doing that.  There wasn’t time enough to do everything and probably they also were inclined to focus upon their area of expertise.  Would having a chip in their brain give them more time?  No.  And would it make them inclined to learn about everything?  Maybe not.

Let’s think of using an external source of smarts.  Think of using Big Data instead of installing a chip inside a person’s brain.  Imagine that this would make a large amount of information accessible to a person.  If we think about using Big Data in the workplace or anywhere else, it may be of use to remember that there’s only so much time to evaluate data and make use of it.  And there’s also a talent constraint.  A person who wouldn’t care about trend analysis may not be helped by Big Data trend information.  They might not be inclined in such a way that the data can become meaningful to them.

If the whole human potential to learn and become aware of the world is held by the total population of humans on earth, then each human being can posses only their small fraction of that total human potential.  Humans need each other because we each possess only a small amount of the total human potential.  We need each other for social interaction but also to get help in areas where we don’t excel but where someone else does.  We need specialists who have the time to help human society by doing what they do best.

This realization works against today’s fascination with the empowering potential of Big Data.  Some have believed that using Big Data can make everyone a genius.  A huge amount of information or Big Data can be plugged into an algorithm that is supposed to be a mathematical model of some tiny facet of a problem that is being considered.  It might be employee performance or sales or productivity, for example.  The information can be run through the algorithm thousands of times.  Some people imagine that this process would be a kind of higher intelligence or AI.  But being plugged into only an algorithm, means that both the strengths and weaknesses of the algorithm can multiply errors in the Big Data.  That can lead to brutal consequences, like the Great Recession which was caused when Quants made imperfect assumptions and put them in algorithms that were used with Big Data.

Some have imagined that Big Data can substitute for human judgement and they have wanted to de-skill a variety of professions like medicine by using diagnostic trees, for example.  A skilled doctor can use his or her experience to decide on a treatment and would probably get to a diagnosis faster than a doctor using a diagnostic tree.  But if the goal is more billable tests, the diagnostic tree would probably increase profits.  If profitability is more desirable than treating a patient with greater skill and efficiency, de-skilling the medical profession might seem attractive unless and until you also consider increased costs for unnecessary treatments and increased mortality on the patient’s side.  Diagnostic trees in medicine can cause brutal patient outcomes and alienate doctors.

De-skilling teachers has also been tried using a testing regime and teaching to test.  Teachers have been fired because of evaluation algorithms that were misused upstream by a previous teacher.  Big Data run through an algorithm just can’t take the place of human experience and judgement.  While Big Data can provide new perspectives about information in large quantities, plugging Big Data into an algorithm will never provide a balanced perspective like the kind that a human being has because of having long acquired experience with information considered in context with real happenings.  An algorithm provides a much narrower perspective.

I think in the age of Big Data the importance of each person’s potential to make a contribution is being overlooked.  I think that human beings are just as important as they ever have been.  And they are almost as limited with Big Data as they are without it.  Big Data can collate a lot of information.  But what use is information or analysis except in the context of what’s meaningful to a person?

Do you think that Big Data can make anyone who isn’t a good manager into one?  Not everyone is capable of realizing why information might matter in the context of the workplace.  Having even more information might not help at all.  There’s been a lot of talk about robots replacing humans in the workforce.  Setting aside the economics of robots, do you think that a manager or analyst can use Big Data to get rid of the need for specialist humans?  Can a manager use Big Data to replace a person with a large learning and experience investment and substitute a robot running on a program?  Or can a manager substitute just anyone as though people have interchangeable training and aptitude?  I don’t think that can work.

As more disruption continues in this economy which has been at the mercy of Big Data and algorithm analysis for almost two decades now, I think greater caution is in order.   Big Data has even more limitations when it is plugged into an algorithm than people have limited genius.  We have seen some brutal consequences when Big Data is plugged into narrow math formulas called algorithms.  Instead of more of that, I would rather see more respect for what’s possible in human society and for each person’s potential to contribute.

If you’d like to learn more about three ideological periods in American politics and how our economy works with our politics, buy a copy of Political Catsup with Economy Fries and, today.


Rebalancing trade matters to the little guy.

President Trump promised workers in the U.S. that he would fight to reduce unnecessary regulations, simplify the tax code and fight for American prosperity.  He promised to fight to protect American jobs.  He said that he wouldn’t forget the American worker.  Lately, President Trump is getting bad press for his efforts to negotiate with China to reduce our trade imbalance with them.  Why would he do that? And who will likely benefit and who might experience harm?

According to Roger L. Ransom in Coping With Capitalism: The Economic Transformation of the United States 1776-1980, “Tariffs save jobs.”(1)  And that’s just what the American worker needs right now.  Alexander Hamilton during the classical liberal period in early America raised most U.S. revenue through tariffs on incoming goods when he used his American System.  His system of tariffs helped to protect American manufacturing and agriculture.  In fact Hamilton’s American System may have inspired China to add tariffs to foreign products in order to protect Chinese industry.(2)

In the recent past, other American presidents have tried to negotiate with China to reduce its tariffs on American products by asking for a change in China’s policies.  But no change happened.  Trump is trying to renegotiate by raising tariffs on Chinese products in order to make trade more fair and reduce the trade deficit.  This policy goes along with his new tax policy to encourage more products to be made here in the U.S. where making these products will employ U.S. workers.  He may succeed where Bush and Obama failed because he was able to pass the new territorial tax system first.

Who will likely benefit and who might experience harm as tariff policies change?  Since the economy is a complex adaptive system under stress, the economy may change in surprising ways.  Outsourcing may become less profitable.  Some workers may gain and others may lose employment because global corporations will be stressed by changes caused by new tariffs.  Growing jobs by changing our tax policies and now adding tariffs will move our complicated economy towards new outcomes but it will take some time for some changes to happen.  Other changes may be quicker.  Some products from abroad will become more expensive and that may discourage Americans from buying some of them.  But President Trump is changing our trade policies in a way that may eventually help American workers to get a job and keep a job.

If you want to learn more about the American economy and our politics pick up a copy of Political Catsup with Economy Fries at, today.

(1)  Roger Ransom, Coping With Capitalism: The Economic Transformation of the United States 1776-1980, Prentice-Hall, Inc., Englewood Cliffs, NJ, 1981, p.162.

(2) Mel Scanlan Stahl, Political Catsup With Economy Fries: Liberalism, Pragmatism, Opportunism, Fast Car Publishing, Spokane, WA, 2015, p. 13.