When everyone is smarter than you, anyone is...

The title of this post is not just meant to grab your attention - unlike the title What They Do Not Teach You at Harvard Business School, which the author Mark Mc Cormack reveals in the middle of the book was chosen precisely for that purpose.

To a certain extent the timing of this post is attributable to my having just finished reading this allegorical novel The Little Prince by Antoine de Saint-Exuprey.  Books like this send one into a deep and reflective spell.  What a riveting book, a haunting story!.  Hope to write more about it another time.

The idea behind this post goes back to a game that I started playing in childhood and which I have been unable to kick in my old age.  The game started with a riddle that my father used to pose when I was a  boy of seven or eight years.  The riddle had been composed by my Dad's friend Varakavi and would go as follows.

There is this woman wearing a pink saree, walking with a vessel towards a tank to draw water from it.  She has long hair, bedecked with orange coloured flowers and the tank has seven steps leading to the water.  What is the woman's age?

I never asked my father whether Varakavi was the man's real name.  Nor did I ever ask my father what Varakavi did for a living.  I could merely gather he did nothing substantial according to the normal conception of doing anything in life.  

 

My father is now too old to recall anything about Varakavi.  All that one can infer from what I recall therefore is that Varakavi was a poet of some sort, self styled in all probability.  That is all we will know about him.  

 

And that is a real pity.  I believe that in literature of any kind, trivial or sublime, one cannot separate the art from the artist himself.  To understand Varakavi's poetry one would need to understand Varakavi the man.

Varakavi's riddle was one of the triggers that got started me on this game  that I played by myself, where I would draw inferences about people's smartness, their vocation and their disposition based on their external appearances such as the clothes they wore, their gait, attire, shape of their toes and fingers, their mannerisms, if any, and so on.

 

It was multi factor predictive analytics to borrow from contemporary data science.  It drew on unlikely explanatory variables, in much the same way, discerning non-intuitive patterns.

Over time this game turned into an obsession of sorts.  The moment I laid my eyes on any man, woman or child, the algorithms in my head would begin to churn.  To use current machine learning metaphor again these algorithms of mine were capable of learning, constantly revising the probabilities based on new results.  

 

Somewhere though the inference rules were messed up.   Often the trials produced silly and inconsistent results.  I would come across this extremely personable young man who I would imagine was a smart, urbane soul, only to discover that he was poorly informed, uncouth and occasionally ill-bred in his behaviour too.  

 

On the other side I would come across a relatively unimpressive looking guy, with uncouth mannerisms but who would either be utterly bright or possess a kind heart, sometimes both.

 

Yet I persisted, because a game it was, after all.  Moreover, I did have my occasional successes too.  At least often enough for me to hope that the success ratios would improve as my sample size on which I trained my algorithm grew to go back to a metaphor from statistics, now refashioned and rechristened as data science.  

 

Whatever their other shortcomings, you got to give it to these statisticians that they know how to keep themselves in business, evergreen.

 

Years later, last week, as I flipped through the pages of the tome, The Laws of Human Nature I got the impression that the author Robert Greene had developed my game into a discipline, an art.  His many fans who wrote beautiful, grateful reviews of his book would obviously spite me for my apparent trivialisation of Greene's magnum opus.  My intent is far from any of that.

I persisted with the game as I grew older.  It remained almost the same with the passage of years in my life.  The way I played the game and tried to infer about people remained largely the same until I started my life as a teacher at Indian Institute of Management Bangalore where I currently work.
 

My constant application of these horribly erroneous algorithms has had one desirable upshot though. I have come to realise that nearly everyone I see around me inside IIMB and outside is bright.  And everyone, bar none, is brighter and more accomplished than I am.

The most obscure looking guy would turn out to be a tiger in econometrics.  Some one with a highly uninspiring appearance would expound inimitably on an arcane theory of economics or social science and so on.

 

It is a tough, realisation to come to terms with me:  That when it comes to intellectual sophistication one brings up the tail end of the world that one sees around oneself.  

 

There is a great sense of lightness when one has accepted it though.  There is no more proving remaining to be done.  Proof is required normally when one wants to establish that one is smarter than oneself.  Fortunately when one acknowledges that one is down there, no one steps up to say: Prove it.

 

Nanni....Namaskaaram...