by Ashutosh Jogalekar
Primitive science began when mankind looked upward at the sky and downward at the earth and asked why. Modern science began when Galileo and Kepler and Newton answered these questions using the language of mathematics and started codifying them into general scientific laws. Since then scientific discovery has been constantly driven by curiosity, and many of the most important answers have come from questions of the kind asked by a child: Why is the sky blue? Why is grass green? Why do monkeys look similar to us? How does a hummingbird flap its wings? With the powerful tool of curiosity came the even more powerful fulcrum of creativity around which all of science hinged. Einstein’s imagining himself on a light beam was a thoroughly creative act; so were Ada Lovelace’s thoughts about a calculating machine as doing something beyond mere calculation, James Watson and Francis Crick’s DNA model-building exercise, Enrico Fermi’s sudden decision to put a block of paraffin wax in the path of neutrons.
What is common to all these flights of fancy is that they were spontaneous, often spur-of-the-moment, informed at best by meager data and mostly by intuition. If Einstein, Lovelace and Fermi had paused to reconsider their thoughts because of the absence of hard evidence or statistical data, they might at the very least been discouraged from exploring these creative ideas further. And yet that is what I think the future Einsteins and Lovelaces of our day are in danger of doing. They are in danger of doing this because they are increasingly living in a world where statistics and data-driven decisions are becoming the beginning and end of everything, where young minds are constantly cautioned to not speculate before they have enough data.
We live in an age where Big Data, More Data and Still More Data seem to be all consuming, looming over decisions both big and mundane; from driving to ordering pet food to getting a mammogram. We are being told that we should not make any decision pending its substantiation through statistics and large-scale data analysis. Now, I will be the first one to advocate making decisions based on data and statistics, especially in an era where sloppy thinking and speculation based on incomplete or non-existent data seems to have turned into the very air which the media and large segments of the population breathe. Statistics has especially been found to be both paramount and sorely lacking in making decisions, and books like Daniel Kahneman’s “Thinking Fast and Slow” and Nate Silver’s “The Signal and the Noise” have stressed how humans are intrinsically bad at probabilistic and statistical thinking and how this disadvantage leads to them consistently making wrong decisions. It seems that a restructuring of our collective thinking process that is grounded in data would be a good thing for everyone.
But there are inherent problems with implementing this principle, quite apart from the severe limitations on creative speculation that an excess of data-based thinking imposes.