MODELING FOLK KNOWLEDGE AS EXPERT SYSTEMS

There are striking parallels between ideas developed in the study of cognitive systems by anthropologists and the modeling of expertise in artificial intelligence research. These parallels suggest that expert system architectures can provide effective means to formulate rigorous models for theories about native expertise and so-called "cultural competence." We illustrate how such modeling may be done with theprogram, BA TES (Bisayan Address Term Expert System), which recasts the analysis ofBisayan address terms by Geoghegan into an expert system. The expert system was used both to examine the logic ofGeoghegan 's argument and to formulate an alternative model for linking an address term with addressee. Expert systems, we suggest, mayprovide a methodfor examining rigorously what otherwise are more loosely stated, verbal arguments. [folk knowledge, expert systems, cognition, computers, culture]

[1]  C. Geertz,et al.  The Interpretation of Cultures , 1973 .

[2]  G. Lakoff,et al.  The cognitive model of anger inherent in American English , 1983 .

[3]  Dan Sperber,et al.  On anthropological knowledge , 1985 .

[4]  Roger C. Schank,et al.  Scripts, plans, goals and understanding: an inquiry into human knowledge structures , 1978 .

[5]  Marvin Minsky,et al.  A framework for representing knowledge" in the psychology of computer vision , 1975 .

[6]  Debra Skinner,et al.  Prestige and intimacy: The cultural models behind Americans' talk about gender types. , 1987 .

[7]  L. O. Howard.  The Anthropological Society of Washington , 1880, Science.

[8]  Gevarter,et al.  Overview of Expert Systems , 1982 .

[9]  N. Quinn,et al.  “commitment” in American marriage: a cultural analysis , 1982 .

[10]  David M. Schneider,et al.  A critique of the study of kinship , 1984 .

[11]  Dianne C. Berry,et al.  The problem of implicit knowledge , 1987 .

[12]  M. Chibnik.  The Evolution of Cultural Rules , 1981, Journal of Anthropological Research.

[13]  Daniel G. Bobrow,et al.  On Overview of KRL, a Knowledge Representation Language , 1976, Cogn. Sci..

[14]  Brenda J. Mann,et al.  The Cocktail Waitress: Woman's Work in a Man's World , 1974 .

[15]  W. Goodenough.  Componential Analysis and the Study of Meaning , 1956 .

[16]  Bruce G. Buchanan,et al.  The MYCIN Experiments of the Stanford Heuristic Programming Project , 1985 .

[17]  Drew McDermott,et al.  Introduction to artificial intelligence , 1986, Addison-Wesley series in computer science.

[18]  N. Quinn.  decision models of social structure , 1975 .

[19]  P. Caws.  Operational, Representational, and Explanatory Models , 1974 .

[20]  Stephen M. Fjellman.  talking about talking about residence: an Akamba case1 , 1976 .

[21]  Casimir A. Kulikowski,et al.  A Practical Guide to Designing Expert Systems , 1984 .

[22]  Dorothy Holland,et al.  Culture and cognition , 1987 .

[23]  C. Frake.  How to Ask for a Drink in Subanun , 1964 .

[24]  N. Quinn.  Cultural models in language and thought: Convergent evidence for a cultural model of American marriage , 1987 .

[25]  E. J. Bourne,et al.  Does the Concept of the Person Vary Cross-Culturally? , 1982 .

[26]  D. E. Breedlove,et al.  General Principles of Classification and Nomenclature in Folk Biology , 1973 .

[27]  Geoffrey Hunter.  What Computers Can't Do , 1988, Philosophy.

[28]  Paul Harmon,et al.  Expert systems: artificial intelligence in business , 1985 .

[29]  R. W. Casson.  Schemata in Cognitive Anthropology , 1983 .

[30]  P. Kay.  Cultural models in language and thought: Linguistic competence and folk theories of language , 1987 .

[31]  Christina H. Gladwin,et al.  production functions and decision models: complementary models , 1979 .

[32]  Marvin Minsky,et al.  A framework for representing knowledge , 1974 .