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From mythology to science

I was having dinner with my friend Andy from college today. Andy, by the way, is an improv theater guy who also majored in Applied Math, making him the funniest math nerd I know :) Anyway, we start talking about Moneyball and quantitative approaches to traditionally qualitative things, and how sciences grow out of mythological approaches.

For the most obvious example, take astronomy. At the very beginning, you had mythology instead of science. Eclipses happen from dragons eating the moon, earth is in the center of the universe, etc. Then, over time, patterns emerge – when the sun sets, or how stars appear, and then qualitative theories can be formed. For astronomy, this is probably when people were building Stonehenge and other things which showed understanding of patterns, but not the underlying reasons why the patterns occured.

But then, as people develop the instruments and expertise to begin measuring results consistently, then these qualitative models become quantitative in nature.  Scientific models form for why they exist. And eventually, this leads to a scientific process of hypothesis, testing, and verification.

Moneyball, for instance, is a story of how baseball made that transition. At first, I’m sure people played it without keeping long, historic, records. And even when they did keep records, a random pattern-seeking person might decide that a pitcher would win games if they threw really quick fastballs, or hitter was good just by hitting homeruns. What Billy Beane was able to do was to apply scientific rigor to the process, and then shape his environment by actually making decisions in accordance with his theories.

This discussion takes us to an interesting place – the jump from mythology to science is a hugely disruptive one. And in general, it may create tremendous opportunities to build companies to capture the inefficiency of the previously flawed foundation. You could argue, for example, that Zillow is making real estate into a more scientific process, rather than one based on conjecture and human-involvement. Does Zillow represent the Billy Beane of real estate?

I don’t know what other opportunities are out there for companies that are able to exploit this – but perhaps the place to look is to understand what kinds of new measurements are taking place? What kinds of new, common-place data is now being collected, and could you apply these assets towards a previously mythologically-driven problem to create efficient, data-driven ones?

UPDATE: Additional thought – one field I’m particularly excited about seeing evolve is the social sciences. For a long time, a lot of pattern-seeking models like Freud’s id/ego/superego might have been formed for pretty silly reasons – I remember thinking Freud was all BS when I took those psychology classes in college. Economics has its flaws too, which is why it’s interesting to see behavioral economics approaches grow and flourish. Both of these might be revolutionized by the advent of two major areas: Brain-scanning devices that measure neurological responses to stimuli, and the DNA-focused initiatives like the Brain Atlas, which may drive us to build a more scientific model of human behavior.

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