litow@uwm-cs.UUCP (10/28/87)
Recently postings have focused on the topic: 'AI - success or failure'. Some postings have been concerned with epistemological or metaphysical matters. Other postings have taken the view that AI is a vast collection of design problems for which much of the metaphysical worry is irrelevant. Based upon its history and current state it seems to me that AI is an area of applied computer science largely aimed at design problems. I think that AI is an unfortunate moniker because AI work is basically fuzzy programming (more accurately the design of systems supporting fuzzier and fuzzier programming) where the term 'fuzzy' is not being used in a pejorative sense. All of the automation issues in AI work are support issues for really fuzzy programming i.e. where humans can extend the interface with automata so that human/automata interaction becomes increasingly complex and 'undisciplined'. Thus in a large sense AI is the frontier part of software science. It could be claimed that at some stage of extension the interface becomes so complex (by human standards at the time) that cognition can be ascribed to the systems. Personally I doubt this will happen. On the other hand the free use of play-like interfaces must have unforeseeable and gigantic consequences for humans. This is where I see the importance of AI. I distinguish between cognitive studies and AI. The metaphysics belongs to the former,not the latter.
vangelde@cisunx.UUCP (Timothy J Van) (07/13/88)
What with the connectionist bandwagon, everyone seems to be getting a lot clearer about just what AI is and what sort of a picture of cognition it embodies. The short story, of course, is that AI claims that thought in general and intelligence in particular is the rule governed manipulation of symbols. So AI is committed to symbolic representations with a combinatorial syntax and formal rules defined over them. The implemenation of those rules is computation. Supposedly, the standard or "classical" view in cognitive psychology is committed to exactly the same picture in the case of human cognition, and so goes around devising models and experiments based on these commitments. My question is - how much of cognitive psychology literally fits this kind of characterization? Some classics, for example the early Shepard and Metzler experiments on image rotation dont seem to fit the description very closely at all. Others, such as the SOAR system, often seem to remain pretty vague about exactly how much of their symbolic machinery they are really attributing to the human cognizer. So, to make my question a little more concrete - I'd be interested to know what people's favorite examples of systems that REALLY DO FIT THE DESCRIPTION are? (Or any other interesting comments, of course.) Tim van Gelder