The Seven Deadly Sins of Predicting the Future of AI

This is a long, but fast moving and very readable, essay on why AI will arrive more slowly and do less than some of its more starry-eyed proponents assert. It’s littered with thought-provoking examples and weaves together a number of themes touched on here before – the inertial power of the installed base, the risk of confusing task completion with intelligence (and still more so general intelligence), the difference between tasks and jobs, and just how long it takes to get from proof of concept to anything close to real world practicality. There are some interesting second order thoughts as well. There is a tendency, for example, to assume that technologies (particularly digital technologies) will keep improving. But though that may well be true over a period, it’s very unlikely to be true indefinitely: in the real world, S-curves are more common than exponential growth.

Rodney Brooks

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