A process specification of expert lawyer reasoning

ABSTRACT

The ability to think like a lawyer is an often heard phrase but a vaguely understood phenomena. What is lawyer reasoning? Does it differ from reasoning in other fields and disciplines? This paper begins to answer these questions by explicating the problem solving and reasoning processes of an experienced practicing attorney and law professor in the field of housing law. A particularly noteworthy finding of these investigations involves the subject's construction and use of “component” mental models and “stories”. The active construction of mental models and the coherence of stories comprise the expert's problem solving and ald indexing and retrieval of legal theories from previous case experiences in episodic memory. These characteristics have strong architectural consequences for the use of artificial intelligence tools and techniques in law. Parallels are drawn between the approach taken in this study of lawyer reasoning and the growing body of research on “mental models”. Current efforts aimed at specifying the conceptual differences between novice and expert practitioners are outlined.

REFERENCES

• 1: Abelson, R.P. "Psychological Status of the Script Concept." American Psychologist, 36,7, (1981): 715-729.
• 2: Anderson, J.R. "Methodologies for Studying Human Knowledge." Behavior and Brain Sciences: (1987)in press.
• 3: Bartlett, F.C. "Remembering". Cambridge, England: Cambridge University Press, (1932).
• 4: Bellow, G, & Moulton, B. "The Lawyering Process: Materials for Ctinical Instruction in Advocacy." Mineola, New York: The Foundation Press, (1978).
• 5: Bok, D. "The President's Report to the Board of Overseers of Harvard College." Cambridge, Massachusetts: Harvard University (1982),
• 6: Burger, W.E. "Annual Report on the Slate of the Judiciary." ABA 3ournat, 66, (19B0): 2eJ5-2c59.
• 7: Cardozo, B.N. "The Nature of the Judicial Process." New Haven, Connecticut: Yale University Press (1921).
• 8: Carey, $.E. "Conceptual Change." Bradtord Books, MIT Press (1985).
• 9: Collins, A. "Component Models of Physical Systems," Proceedings of The Seventh Annual Conference of the Cognitive Sciences Society (1985): 80-89.
• 10: deKleer, J. & Brown, J.S, "Assumptions and Ambiguities in Mechanistic Mentat Models." tn D. Genter & A.L. Stevens (Eds.) Menial Models. Hillsdale, NJ: Erlbaurn (1983): 155-190.
• 11: Dinsmore, J. "Mental Spaces from a Functional Perspective." Cognitive Science 11, (1987): 1- 21.
• 12: Dyer, M.G. "AI and Legal Reasoning." Report of a panel chaired by E. Rlssland. Proceedings o! the Nineth International Joint Conference on Artificial Intelligence (1985).
• 13: Dyer, M.G. & Flowers, M. "Toward Automating Legat Expertise." Computer Power & Legal Reasoning, C. Walter (Ed.) West Publishing Company (1985): 49-68.
• 14: Ericsson, K.A. & Simon H.A, "Verbal Reports as Data." Psychologiclal Review (1980).
• 15: Gentner, D. "Structure Mapping: A Theoretical Framework for Analogy. "Cognitive Science 7, (1983): 155.170.
• 16: Gentner, D. & Stevens, A.L. (Eds.) "Mental Models." Hillsdale, Nj: Erlbaum (1983).
• 17: Golding, M.P. "Legal Reasoning." New York: Alfred Knopf (1984),
• 18: John H. Holland , Keith J. Holyoak , Richard E. Nisbett , Paul R. Thagard, Induction: processes of inference, learning, and discovery, MIT Press, Cambridge, MA, 1986
• 19: Johnson-Laird, P.N. "The Form and Function of Mental Models." Proceedings of the Third Annual Conference of !he Cognitive Sciences Society (1981): 103-105.
• 20: Johnson, M. & Johnson, P. "Competence and Specialization in the Practice of Law: An Empirical investigation of Lawyer Reasoning." National Science Foundation, Project Summary (1981).
• 21: Kempton, W. "Two Theories of Home Heat Control." Cognitive Science 10, (1986): 75-90.
• 22: Kibler, D. & Hall, R.P. "A Model of Acquiring Problem Solving Expertise." Proceedings of the Seventh Annual Conference of the Cognitive Sciences Society, (1985): 303-307.
• 23: Kolodner, J.L. "Maintaining Organization in a Dynamic Long Term Memory." Cognitive Science 7, (1983): 243-280.
• 24: Koiodner, J.L. & Simpson, R.L. "Experience and Problem Solving: A Framework." Proceedings of the Sixth Annual Conference of the Cognitive Sciences Society (1984): 239-243.
• 25: Kulpers, B. & Kassirer, J.P. "Causal Reasoning in Medicine: Analysis ol a Protocol." Cognitive Science 8, (1984): 363-385,
• 26: Levi, E,H. "An Introduction to Legal Reasoning." Chicago: University of Chicago Press, (1921).
• 27: Mandler, J.M. & Johnson, N.S. "Remembrance of Things Parsed: Story Structure Recall." Cognitive Psychology 9, (1977): 111-151.
• 28: McCloskey, M. "Naive Theories of Motion." In D. Genter & A.L. Stevens (Eds.) Mental Models. HIllsdale, NJ: Erlbaum (1983): 299-324.
• 29: O'Neil D.P. & Wood, G.D. "Artificial Intelligence and Law." Cambridge, Massachusetts: Harvard University Information Technology Review (1986),
• 30: Ross, B.H. "Memory Effects in Learning and Problem Solving." Second Annual Workshop on Theoretical Issues in Conceptual Information Processing. New Haven, Connecticut: Yale University (1985).
• 31: Rumelharl, D.E. "Notes on a Schema for Stories." in D.G. Bobrow & A. Collins (Eds.) Representation and UnderstandLng: Studies In Cognitive Science. New York: Academic Press (1975).
• 32: Schank, R.C. "The Explanation Game." Yale University CSD/RR #307 (1984).
• 33: Schank, R.C. "Explanation: A First Pass." Yale Univesity CSDIRR #330 (1984).
• 34: Stratman, J. "Studying the Appelate Brief and Opinion Composing Process: A Window on Legal Thinking." Jurts 19, no.1 (1984): 9-14 and no.2 12-19.
• 35: Walker, W.H. & Kintsch, W. "Automatic and Strategic Aspects of Knowledge Retrieval." Cognitive Science 9, (1985): 261-283.

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.1 Applications and Expert Systems
          Subjects: Law

Additional Classification:
  H. Information Systems
  H.1 MODELS AND PRINCIPLES
      H.1.2 User/Machine Systems
          Subjects: Human information processing
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Retrieval models

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.3 Deduction and Theorem Proving
          Subjects: Deduction (e.g., natural, rule-based)

General Terms:
Design, Human Factors