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Some Expert Systems Need Common Sense

McCarthy, J (1984) Some Expert Systems Need Common Sense. [Preprint]

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Abstract

An expert system is a computer program intended to embody the knowledge and ability of an expert in a certain domain. The ideas behind them and several examples have been described in other lectures in this symposium. Their performance in their specialized domains are often very impressive. Nevertheless, hardly any of them have certain common sense knowledge and ability possessed by any non-feeble-minded human. This lack makes them ``brittle''. By this is meant that they are difficult to extend beyond the scope originally contemplated by their designers, and they usually don't recognize their own limitations. Many important applications will require common sense abilities. The object of this lecture is to describe common sense abilities and the problems that require them. Common sense facts and methods are only very partially understood today, and extending this understanding is the key problem facing artificial intelligence. This isn't exactly a new point of view. I have been advocating ``Computer Programs with Common Sense''since I wrote a paper with that title in 1958. Studying common sense capability has sometimes been popular and sometimes unpopular among AI researchers. At present it's popular, perhaps because new AI knowledge offers new hope of progress. Certainly AI researchers today know a lot more about what common sense is than I knew in 1958 -- or in 1969 when I wrote another paper on the subject. However, expressing common sense knowledge in formal terms has proved very difficult, and the number of scientists working in the area is still far too small. One of the best known expert systems is MYCIN (Shortliffe 1976; Davis, Buchanan and Shortliffe 1977), a program for advising physicians on treating bacterial infections of the blood and meningitis. It does reasonably well without common sense, provided the user has common sense and understands the program's limitations. MYCIN conducts a question and answer dialog. After asking basic facts about the patient such as name, sex and age, MYCIN asks about suspected bacterial organisms, suspected sites of infection, the presence of specific symptoms (e.g. fever, headache) relevant to diagnosis, the outcome of laboratory tests, and some others. It then recommends a certain course of antibiotics. While the dialog is in English, MYCIN avoids having to understand freely written English by controlling the dialog. It outputs sentences, but the user types only single words or standard phrases. Its major innovations over many previous expert systems were that it uses measures of uncertainty (not probabilities) for its diagnoses and the fact that it is prepared to explain its reasoning to the physician, so he can decide whether to accept it. Our discussion of MYCIN begins with its ontology. The ontology of a program is the set of entities that its variables range over. Essentially this is what it can have information about. MYCIN's ontology includes bacteria, symptoms, tests, possible sites of infection, antibiotics and treatments. Doctors, hospitals, illness and death are absent. Even patients are not really part of the ontology, although MYCIN asks for many facts about the specific patient. This is because patients aren't values of variables, and MYCIN never compares the infections of two different patients. It would therefore be difficult to modify MYCIN to learn from its experience. MYCIN's program, written in a general scheme called EMYCIN, is a so-called production system. A production system is a collection of rules, each of which has two parts -- a pattern part and an action part. When a rule is activated, MYCIN tests whether the pattern part matches the database. If so this results in the variables in the pattern being matched to whatever entities are required for the match of the database. If not the pattern fails and MYCIN tries another. If the match is successful, then MYCIN performs the action part of the pattern using the values of the variables determined by the pattern part. The whole process of questioning and recommending is built up out of productions. The production formalism turned out to be suitable for representing a large amount of information about the diagnosis and treatment of bacterial infections. When MYCIN is used in its intended manner it scores better than medical students or interns or practicing physicians and on a par with experts in bacterial diseases when the latter are asked to perform in the same way. However, MYCIN has not been put into production use, and the reasons given by experts in the area varied when I asked whether it would be appropriate to sell MYCIN cassettes to doctors wanting to put it on their micro-computers. Some said it would be ok if there were a means of keeping MYCIN's database current with new discoveries in the field, i.e. with new tests, new theories, new diagnoses and new antibiotics. For example, MYCIN would have to be told about Legionnaire's disease and the associated Legionnella bacteria which became understood only after MYCIN was finished. (MYCIN is very stubborn about new bacteria, and simply replies ``unrecognized response''.) Others say that MYCIN is not even close to usable except experimentally, because it doesn't know its own limitations. I suppose this is partly a question of whether the doctor using MYCIN is trusted to understand the documentation about its limitations. Programmers always develop the idea that the users of their programs are idiots, so the opinion that doctors aren't smart enough not to be misled by MYCIN's limitations may be at least partly a consequence of this ideology. An example of MYCIN not knowing its limitations can be excited by telling MYCIN that the patient has Cholerae Vibrio in his intestines. MYCIN will cheerfully recommend two weeks of tetracycline and nothing else. Presumably this would indeed kill the bacteria, but most likely the patient will be dead of cholera long before that. However, the physician will presumably know that the diarrhea has to be treated and look elsewhere for how to do it. On the other hand it may be really true that some measure of common sense is required for usefulness even in this narrow domain. We'll list some areas of common sense knowledge and reasoning ability and also apply the criteria to MYCIN and other hypothetical programs operating in MYCIN's domain.

Item Type:Preprint
Subjects:Computer Science > Artificial Intelligence
ID Code:423
Deposited By:McCarthy, John
Deposited On:27 Feb 1998
Last Modified:11 Mar 2011 08:53

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