WIRED point of view on AI

In its October 2007 issue, WIRED has special section named “Geekipedia”. In this supplement, WIRED summarizes 149 people, facts or concepts that they think are important. Among the list, one can find “Artificial Intelligence”. The description is quite negative and focus on different aims that AI hasn’t been able to achieve. I agree with them on the first half of the explanation regarding AI. They write that “[…] while researchers have built awesome technology, they’ve failed to grapple with philosophy“. AI researchers can tell me if I’m wrong, but I think this sentence can be considered as acceptable. However, in the middle of the text, things start to go wrong.

Although the message WIRED intends to give about AI (i.e. AI hasn’t yet achieved most of its initial aims), they give bad examples. They write that “[…] computers failed one commonsense task after another […]“. The problem doesn’t come from this sentence, rather from examples of such “tasks”.

First example: computer fails to understand natural languages. Oops! Very bad example. Although one can discuss the meaning of the word “understand”, it is clear that speech processing, recognition and synthesis are examples of successful applications in machine learning. The second example they give is even worst. They write that a computer cannot distinguish a dog from a cat. Oops again! Face recognition is one of the best example of machine learning success story. And there is only one step from the Human to the animal. Indeed, I have a colleague in machine learning who is doing face recognition on a cat database… and it’s working!

But the worst is yet to come (yes, believe me). The last paragraph explaining AI contains the following sentence: “Nowadays, Google “knows” pretty much anything you ask it. But its insanely fast and powerful work is modestly described as data-mining, not thinking“. Out of the spelling, I’m surprised by the bad connotation given to the data mining term. So, although their description is not completely wrong, they haven’t chosen the best examples to illustrate the limitations of AI. There are still a lot of things a computer cannot do, so examples are not missing…


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  1. A.I. has clearly not produced working systems which would satisfy the most optimistic and heady expectations of the 1950s. Kurzweil and his ilk notwithstanding, I don’t think contemporary constructs are much closer to realizing such dreams.

    At the least, though, one might say that the collective field has amassed a set of negatives: Parallel processing alone will not acheive strong A.I. Symbolic processing alone will not acheive strong A.I. Connectionism alone will not acheive strong A.I. The list goes on and on…

    How much one cares about this depends on one’s aims. Though the possibility of strong A.I. is an interesting question, for my part, I doubt that strong A.I. is even possible. Still, I consider myself a pragmatist. Working, practical technologies which have emerged from under the A.I. umbrella are powerful and have solved difficult real-world problems. If computers are evolving into the ultimate “idiot savants”, then so be it. To make a mechanical analogies: automobiles are not thoroughbreds, and robots are not athletes, yet they serve their intended purposes well. I wouldn’t take narcissistic disappointments too seriously.

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