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===But chess-playing supercomputers... === | ===But chess-playing supercomputers... === | ||
Hand-waving about | Hand-waving about [[Chess]] and [[Go]]-playing supercomputers — there is a lot of that in {{br|A World Without Work}} — does not advance the argument. Both are hermetically sealed games on small, finite boards with simple sets of unvarying rules between two players sharing a common objective. Outcomes are entirely deterministic, and you can see that, at the limit, the player with the superior number-crunching power ''must'' win. Even here the natural imagination of human players, otherwise at a ''colossal'' disadvantage from an information processing perspective, made the job of beating them surprisingly hard. This ought to be the lesson: even in thoroughly simplistic binary games, it takes a ton of dumb processing power to beat a puny imagineer. Instead, Susskind reads this as a signpost to the [[Apocalypse]]. | ||
But life is not a two-person board-game on a small-board with fixed rules a static, common, zero-sum objective. Analogising from this — ironically, something a computer could not do — is not great police-work. In the world of [[systems analysis]], [[Chess]] and [[Go]] are [[complicated]], not [[complex]], problems. The risk payoff is normal, not exponential. They can, in theory, be “brute force” managed by skilled operation of an algorithm, and the consequences of failure are predictable and contained — you lose. ''[[Complex]]'' problems — those one finds at the frontier, when one has boldly gone where no-one has gone before, in dynamic systems, where information is not perfect, where risk outcomes are [[convexity|convex]] — so-called “[[wicked environment]]s” — are not like that.<ref>There is more on this topic at [[complex systems]].</ref> Here algorithms are no good. One needs experience, wisdom and judgment. | But life is not a two-person board-game on a small-board with fixed rules a static, common, zero-sum objective. Analogising from this — ironically, something a computer could not do — is not great police-work. In the world of [[systems analysis]], [[Chess]] and [[Go]] are [[complicated]], not [[complex]], problems. The risk payoff is normal, not exponential. They can, in theory, be “brute force” managed by skilled operation of an algorithm, and the consequences of failure are predictable and contained — you lose. ''[[Complex]]'' problems — those one finds at the frontier, when one has boldly gone where no-one has gone before, in dynamic systems, where information is not perfect, where risk outcomes are [[convexity|convex]] — so-called “[[wicked environment]]s” — are not like that.<ref>There is more on this topic at [[complex systems]].</ref> Here algorithms are no good. One needs experience, wisdom and judgment. |