Does Comprehension Matter?


It’s possible to translate stuff from one language to another without having any clue about either language involved! After all, that’s how Google Translate operates: it’s just an algorithm (albeit an extremely good one) that mines a huge amount of articles in different languages to create its word/phrase map. Which it then uses to translate. No human in involved in translating anything. Is it perfect? No. Is it good enough for most purposes? Absolutely, yes.

I remember this article a long time back by Kevin Kelly on whether this “Google approach” could be applied to science as well: have an algorithm look at all the data we get from all the sensors, satellite pics and Large Hadron Colliders of the world. If the algorithm is smart enough, it’ll come up with patterns of nature and even make predictions. Of course, that approach doesn’t lead to any understanding or comprehension, but do we even need to worry about understanding, Kelly asked?

I always felt the answer to that question was Yes, we should care about understanding. But I was not able to identify why I felt that way. Until I read this statement by Kevin Gold:
“If the solar system’s structure were open for debate today, AI algorithms could successfully predict the planets’ motion without ever discovering Kepler’s laws.”

That line lit the proverbial light bulb in my head: finally, I had the reason why I instinctively felt understanding mattered: we are better off knowing about the Second Law of Thermodynamics rather than just looking at data but never knowing for sure whether a perpetual motion machine is possible. That’s something just finding patterns in raw data can never do.

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