Q&A: Douglas Hofstadter on why AI is far from intelligent
The further we get into the future, the more I think, what if our data-crunching approach to AI is simply the best thing there is?<p>Hofstadter said in GEB (in 1979) that the only program that could be capable of beating the best humans at chess would need to be a general and human intelligence... human enough to decline  your suggestion to play chess, and suggest you talk about poetry instead.<p>It seems that people today are still engaging in the same sort of fallacy. I keep hearing that deep learning is too hyper-specialized, that it&#x27;s a tool and not an intelligence, that we&#x27;re still waiting for a revolution of <i>general</i> intelligence, where intelligences will have sophisticated logic and make their decisions without billions of data points, just like humans do.<p>My counter-hypothesis is this: Computers, compared to humans, will always be more data-hungry (i.e. worse at making general decisions without huge amounts of data) and more data-capable (i.e. better at making decisions with it). And this isn&#x27;t really a bad thing. We will still see revolutions allowing more and more general problems to be solved, revolutions allowing more and more general data to be considered, and revolutions giving more and more usable interfaces for inputing data and specifying problems. We&#x27;ll still see data-driven intelligent assistants and data-driven board members making critical decisions like in everyone&#x27;s utopian dreams&#x2F;dystopian nightmares.<p>But these foretold &quot;general&quot; intelligences, who don&#x27;t need excessive data, the intelligences who beat the Turing test, the intelligences who &quot;want&quot; things and &quot;feel&quot; things, who attempt to solve the problem of replicating humans... those come unimaginably far in the future. And when they do arrive, they won&#x27;t really solve any problems that the data-crunchers haven&#x27;t already solved better.