Path: utzoo!mnetor!uunet!mcvax!ukc!strath-cs!glasgow!gilbert From: gilbert@cs.glasgow.ac.uk (Gilbert Cockton) Newsgroups: comp.ai Subject: Arguments against AI are arguments against human formalisms Message-ID: <1103@crete.cs.glasgow.ac.uk> Date: 5 May 88 10:54:23 GMT References: <368693.880430.MINSKY@AI.AI.MIT.EDU> <1579@pt.cs.cmu.edu> Reply-To: gilbert@cs.glasgow.ac.uk (Gilbert Cockton) Organization: Comp Sci, Glasgow Univ, Scotland Lines: 104 In article <1579@pt.cs.cmu.edu> yamauchi@speech2.cs.cmu.edu (Brian Yamauchi) writes: >Cockton seems to be saying that humans do have free will, but is totally >impossible for AIs to ever have free will. I am curious as to what he bases >this belief upon other than "conflict with traditional Western values". Isn't that enough? What's so special about academia that it should be allowed to support any intellectual activity without criticism from the society which supports it? Surely it is the duty of all academics to look to the social implications of their work? Having free will, they are not obliged to pursue lines of enquiry which are so controversial. I have other arguments, which have popped up now and again in postings over the last few years: 1) Rule-based systems require fully formalised knowledge-bases. Rule-based systems are impossible in areas where no written formalisation exists. Note how scholars like John Anderson restrict themselves to proper psycholgical data. I regard Anderson as a psychologist, not as an AI worker. He is investigating computational accounts of known phenomena. As such, his research is a respectable confrontation with the boundaries of the computational paradigm. His writing is candid and I have yet to see him proceed confidently from assumptions, though he often has to live with some. Conclusion, AI as a collection of mathematicians and computer scientists playing with machines, cannot formalise psychology where no convincing written account exists. Advances here will come from non-computational psychology first, as computational psychology has to follow in the wake of the real thing. The real thing unfortunately cuts a slow and shallow bow-wave. [yes, I know about connectionism, but then you have to formalise the inputs. Furthermore, you don't know what a PDP network does know] 2) Formal accounts of nearly every area of human activity are rare. I have a degree in Education. For it I studied Philosophy, Psychology and Sociology. My undegraduate dissertation was on Curriculum design - an interdisciplinary topic which has to draw on inputs from a number of disciplines. What I learnt here was which horse was best suited for which course, and thus when not to use mathematics, which was most of the time. I did philosophy with a (ex-)mathematician BTW I know of few areas in psychology where there is a WRITTEN account of human decision making which is convincing. If no written account exists, no computational account, a more restrictive representation, is possible. Computability adds nothing to 'writability', and many things in this world have not been well represented using written language. Academics are often seduced by the word, and forget that the real decisions in life are rarely written down, and when they are (laws, treaties) they seem worlds apart from what originally was said AI depends on being able to use written language (physical symbol hypothesis) to represent the whole human and physical universe. AI and any degree of literate-ignorance are incompatible. Humans, by contrast, may be ignorant in a literate sense, but knowlegeable in their activities. AI fails as this unformalised knowledge is violated in formalisation, just as the Mona Lisa is indescribable. Philosophically, this is a brand of scepticism. I'm not arguing that nothing is knowable, just that public, formal knolwedge accounts for a small part of our effective everyday knowledge (see Heider). So, AI person, you say you can compute it. Let's forget the Turing Test and replace it with the Touring Test. Write down what you did on your holidays, in English, then come up with a computational model to account for everything you did. There is a warm-up problem which involves the first 10-minutes as you step out of bed in the morning. After 10 minutes, write down EVERYTHING you did (from video?). Then elaborate what happened. This writing will be hard enough. Get my point? The world's just too big for your head. The arrogance of AI lies in its not grasping this. AI needs everything formalised (world-knowledge problem). BTW, Robots aren't AI. Robots are robots. 3) The real world is social, not printed. Because so little of our effective knowledge is formalised, we learn in social contexts, not from books. I presume AI is full of relative loners who have learnt more of what they publicly interact with from books rather than from people. Well I didn't, and I prefer interaction to reading. Learning in a social context is the root of our humanity. It is observations of this social context that reveal our free will in action. Note that we become convinced of our free will, we do not formalise accounts of it. This is the humanity which is beyond AI. Feigenbaum & McCorduck (5th Gen) mention this 'socialisation' objection to AI in passing, but produce no argument for rejecting it. It is the strongest argument against AI. Look at language acquisition in its social context. AI people cannot program a system at the same rate as humans acquire language. OK, perhaps 'n' generations of AI workers could slowly program a NLP system up to competence. But as more gets added, there is more to learn, and there would come a point that the programmers wouldn't understand the system until they were a few years from retirement. We spend enough of our time growing in this world to ever have time to formalise it. The moment we grasp ourselves, we are already out of date, for this grasping is now part of the self that was grasped. Anyway, you did ask. Hope this makes sense.