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Looks really interesting, but seems limited (maybe wisely) to analytic philosophy. There is a whole strain of work from the 80s that was partly inspired by Hei
by mtraven 15y ago
Looks really interesting, but seems limited (maybe wisely) to analytic philosophy.
There is a whole strain of work from the 80s that was partly inspired by Heidegger and phenomenology AND the realization that some classical AI problems were computationally intractable. This work was controversial, to say the least, but influential in its way. I'd suggest that any course on this topic ought to at least touch on this work.
http://mit.dspace.org/bitstream/handle/1721.1/6947/AITR-802.pdf http://mit.dspace.org/bitstream/handle/1721.1/6947/AITR-802....
http://leidlmair.at/doc/WhyHeideggerianAIFailed.pdf http://leidlmair.at/doc/WhyHeideggerianAIFailed.pdf
- mshron 15y agoI can see why the Dreyfus article would be controversial, but so far (first ten pages or so) I found it very enlightening. This really struck a chord with me: > What the learner acquires through experience is not represented at all but is presented to the learner as more and more finely discriminated situations, and, if the situation does not clearly solicit a single response or if the response does not produce a satisfactory result, the learner is led to further refine his discriminations, which, in turn, solicit more refined responses. Comparing that to the meaning of "learn" commonly used in ML to mean "finding optimal weights for some features" and you can see the gulf pretty starkly.