Path: utzoo!attcan!uunet!lll-winken!lll-tis!ames!ncar!mailrus!tut.cis.ohio-state.edu!bloom-beacon!cs.glasgow.ac.UK!gilbert From: gilbert@cs.glasgow.ac.UK (Gilbert Cockton) Newsgroups: comp.ai.digest Subject: Bringing AI back home (Gilbert Cockton) Message-ID: <1776@crete.cs.glasgow.ac.uk> Date: 25 Oct 88 09:24:07 GMT References: <8810122229.AA20257@BOEING.COM> Sender: daemon@bloom-beacon.MIT.EDU Reply-To: Gilbert Cockton Organization: Comp Sci, Glasgow Univ, Scotland Lines: 59 Approved: ailist@ai.ai.mit.edu In a previous article, Ray Allis writes: >If AI is to make progress toward machines with common sense, we >should first rectify the preposterous inverted notion that AI is >somehow a subset of computer science, Nothing preposterous at all about this. AI is about applications of computers, and you can't sensibly apply computers without using computer science. You can hack together a mess of LISP or PROLOG (and have I seen some messes), but this contributes as much to our knowledge of computer applications as a 14 year old's first 10,000 line BASIC program. > or call the research something other than "artificial intelligence". Is this the real thrust of your argument? Most people would agree, even Herb Simon doesn't like the term and says so in "Sciences of the Artificial". Many people would be happy if AI boy scouts came down from their technological utopian fantasies and addressed the sensible problem of optimising human-computer task allocation in a humble, disciplined and well-focussed manner. There are tasks in the world. Computers can assist some of these tasks, but not others. Understanding why this is the case lies at the heart of proper human-machine system design. The problem with hard AI is that it doesn't want to know that a real division between automatable and unautomatable tasks does exist in practice. Because of this, AI can make no practical contribution to real world systems design. Practical applications of AI tools are usually done by people on the fringes of hard AI. Indeed, many AI types do not regard Expert Systems types as AI workers. > Computer science has nothing whatever to say about much of what we call > intelligent behavior, particularly common sense. Only sociology has anything to do with either of these, so to place AI within CS is to lose nothing. To place AI within sociology would result in a massacre :-) Intelligence is a value judgement, not a definable entity. Why are so many AI workers so damned ignorant of the problems with operationalising definitions of intelligence, as borne out by nearly a century of psychometrics here? Common sense is a labelling activity for beliefs which are assumed to be common within a (sub)culture. Hence the distinction between academic knowledge and common sense. Academic knowledge is institutionalised within highly marginal sub-cultures, and thus as sense goes, is far less common than the really common stuff. Such social constructs cannot have a machine embodiment, nor can any academic discipline except sociology sensibly address such woolly epiphenomena. I do include cognitive psychology within this exclusion, as no sensible cognitive psychologist would use terms like common sense or intelligence. The mental phenomena which are explored computationally by cognitive psychologists tend to be more basic and better defined aspects of individual behaviour. The minute words like common sense and intelligence are used, the relevant discipline becomes the sociology of knowledge. -- Gilbert Cockton, Department of Computing Science, The University, Glasgow gilbert@uk.ac.glasgow.cs !ukc!glasgow!gilbert -- Gilbert Cockton, Department of Computing Science, The University, Glasgow gilbert@uk.ac.glasgow.cs !ukc!glasgow!gilbert