Briefly noted: Deep Thinking — Garry Kasparov

If you’ve read Average is Over you’ve gotten enough of Kasparov’s book to skip it; the abstract lessons from the second section of Average is Over are similar to Deep Thinking‘s. Still, human-computer play remain underrated and also remains a key metaphor for what human-computer interaction will look like in the near future. Computer-assisted driving is maybe the most familiar aspect right now, and that sort of dynamic will likely increase as time goes on and as the number of transistors that can inhabit a given area continues to increase.

Deep Thinking is most interesting about halfway through when Kasparov describes in detail the conditions under which he played the famous 1997 Deep Blue match. Before and after there is some interesting material but less than one would like. Maybe I’m just a sucker for narrative, and the middle section is primarily narrative. Still, the more I read of Kasparov the more I think I should read more, and his writing about Putin and Russia is consistently insightful. If you want a conventional review of Deep Thinking, Robin Hanson’s “Grandmasters vs. Gigabytes” is good.

There are few aesthetically beautiful sentences but still some useful observations. For example:

Connections between chess skill and general intelligence are weak at best. There is no more truth to the thought that all chess players are geniuses than in saying that all geniuses play chess. In fact, one of the things that makes chess so interesting is that it’s still unclear exactly what separates good chess players from great ones.

That last sentence is true of novelists and other writers too. “Good” and “great” can be felt and the critical faculty can be honed over time, but specific definitions remain elusive. Oddly, though, two pages later Kasparov returns to notions of greatness in a way that almost contradict the quote above:

When Der Spiegel asked me what I thought separated me, the world champion, from other strong chess players, I answered, ‘The willingness to take on new challenges,’ the same answer I would give today. The willingness to keep trying new things—different methods, uncomfortable tasks—when you are already an expert at something is what separates good from great. Focusing on your strengths is required for peak performance, but improving your weaknesses has the potential for the greatest gains.

So there is an answer to what separates good from great (“The willingness to try new challenges”) or there isn’t? Both sections are interesting and both might be true, but this is the sort of internal contradiction editors (or Kasparov’s ghost writer / assistant, Mig Greengard) are supposed to find.

Then there are sentences like, “It’s a privilege to be able to focus on the negative potential of world-changing breakthroughs like artificial intelligence. As real as these issues may be, we will not solve them unless we keep innovating even more ambitiously, creating solutions and new problems, and yet more solutions, as we always have.” Everyone else seems to be for innovation, making me tempted to come out as anti-innovation simply to be contrary.

But there are very useful sentences too, like the last one here:

How professional chess changed when computers and databases arrived is a useful metaphor for how new technology is adopted across industries and societies in general. It’s a well-established phenomenon, but I feel that the motivations are underanalyzed. Being young and less set in our ways definitely makes us more open to trying new things. But simply being older isn’t the only factor that works against this openness—there is also being successful. When you have success, when the status quo favors you, it becomes very hard to voluntarily change your ways.

Success is never final. Yet we, collectively, never seem to know that. Peak performance sustained over a lifetime may have to incorporate this idea.

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