Path: utzoo!attcan!uunet!mcvax!ukc!strath-cs!glasgow!gilbert From: gilbert@cs.glasgow.ac.uk (Gilbert Cockton) Newsgroups: comp.ai Subject: Bad AI: A Clarification Message-ID: <1299@crete.cs.glasgow.ac.uk> Date: 30 May 88 08:34:58 GMT References: <1242@crete.cs.glasgow.ac.uk> Reply-To: gilbert@cs.glasgow.ac.uk (Gilbert Cockton) Organization: Comp Sci, Glasgow Univ, Scotland Lines: 72 In article <1242@crete.cs.glasgow.ac.uk> gilbert@cs.glasgow.ac.uk (Gilbert Cockton) blurts: >Mindless application of the computational paradigm to > a) problems which have not yielded to stronger methods > b) problems which no other paradigm has yet provided any understanding of. This is poorly expressed and misleading. Between "problems" and "which" insert "concerning human existence". As this stands, it looks like I want to withdraw encouragement from ALL computer research. Apologies to anyone who's taken this seriously enough to follow-up, or was just annoyed (but you shouldn't be anyway) Bad AI is research into human behaviour and reasoning, usually conducted by mathematicians or computer scientists who are as well-qualified for the study of humanity as is an archaeologist with a luminous watch for the study of radiation (of course I understand radiation, I've got a luminous watch, haven't I? ;-)) AI research seems to fall into two groups: a) machine intelligence; b) simulation of human behaviour. No problem with a), apart from the use of the now vacuous term "intelligence", which psychometricians have failed miserably to pin down. No problem with b) if the researcher has a command of the study of humanity, hence the respectability of computational modelling in psychology. Also, mathematicians and computer scientists have no handicaps, and many advantages when the human behaviour in b) is equation solving, symbolic mathematics, theorem proving and configuring VAXES. They are domain experts here. Problems only arise when they confuse their excellent and most ingenious programs with human reasoning. 1) because maths and logic has little to do with normal everyday reasoning (i.e. most reasoning is not consciously mathematical, symbolic, denotational, driven by inference rules). Maths procedures are not equivalent to any human reasoning. There is an overlap, but it's small 2) because they have no training in the difficulties involved in studying human behaviour, unlike professional psychologists, sociologists, political scientists and economists. At best, they are informed amateurs, and it is sad that their research is funded when research in established disciplines is not. Explaining this political phenomena requires a simple appeal to the hype of "pure" AI and the gullibility of its sponsors, as well as to the honesty of established disciplines who know that coming to understand ourselves is difficult, fraught with methodological problems. Hence the appeal of the boy scout enthusiasm of the LISP hacker. So, the reason for not encouraging AI is twofold. Firstly, any research which does not address human reasoning directly is either pure computer science, or a domain application of computing. There is no need for a separate body of research called AI (or cybernetics for that matter). There are just computational techniques. Full stop. It would be nice if they followed good software engineering practices and structured development methods as well. Secondly, where research does address human reasoning directly, it should be under the watchful eye of competent disciplines. Neither mathematics or computer science are competent disciplines. Supporting "pure" AI research by logic or LISP hackers makes as much sense as putting a group of historians, anthropologists and linguists in charge of a fusion experiment. The word is "skill". Research requires skill. Research into humanity requires special skills. Computer scientists and mathematicians are not taught these skills. When hardware was expensive, it made sense to concentrate research using computational approaches to our behaviour. The result was AI jounals, AI conferences, and a cosy AI community insulated from the intellectual demands of the real human disciplines. I hope, with MacLisp and all the other cheap AI environments, that control of the computational paradigm is lost by the technical experts and passes to those who understand what it is to study ourselves. AI will disappear, but the work won't. Indeed it will get better, and having to submit to an AI conference rather than a psychology or related conference (for research into ourselves), or a computing or application area conference (for machine 'intelligence') will be a true reflection of the quality of the work. -- Gilbert Cockton, Department of Computing Science, The University, Glasgow gilbert@uk.ac.glasgow.cs!ukc!glasgow!gilbert The proper object of the study of humanity is humans, not machines