Donald Trump: A Black Swan Presidency?

 In 2016, the only reading I did about the presidential election was Scott Adams’ blog. Scott is the creator of the Dilbert comic strip and has spent 30 years studying persuasion and hypnosis. I read his blog because he understood what was happening on a psychological and emotional level. Almost daily, he would review the previous day(s) events from his “persuasion filter” highlighting the method to the perceived madness from the Trump campaign and shedding light on the missteps that led to Clinton losing the election.

At the moment, I am re-reading Taleb’s Black Swan and remembering, probably slightly inaccurately, the major events that led to the once improbable and unpredictable (by almost every “reputable” source) election of Donald Trump. This book is a fantastic lens through which one can understand this election because you are reminded of the purpose of the human mind which is not to understand facts, but to make sense of non-sense.  

I am going to focus on the nonsense of predictions and polls because they serve as the canary in the coal mine for many voters and politicians. So, what the hell happened? In short, they drank their own kool-aid aka “confirmation bias”, but more broadly, the media tried to mathematically quantify events that were driven by emotion, not facts.  
Unfortunately for pundits and statisticians, prediction becomes exponentially harder with each added variable, especially since we do not know what these variables will be. Let me remind you, we had A LOT of variables this year and a President-Elect who understands persuasion better than almost everyone else. We were ripe for an “upset”. 

In his book, Taleb examines the work of French Professor Henri Poincaré who introduced the concept of nonlinearities, small effects that lead to severe consequences, later renamed “chaos theory”. Taleb, via Poincaré, suggests that “as you project into the future you need an increasing amount of precision about the dynamics of the process you are modeling since your error rate grows very rapidly”. This is why so many people got things so wrong. 

I am not suggesting that the collective media got it wrong because they did the math wrong. My point is that they could not have possibly got it right because this was not a mathematical problem.  I suspect these types of errors will continue throughout 2017.

Perhaps my predictions will be wrong and the optimist in me will prevail. 

Thank you for reading! You are great.