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The Rationale and Approach of the Legal Expert System Construction
Shanghai University of Political Science and Law, Shanghai, China
Shanghai University of Political Science and Law, Shanghai, China
Shanghai University of Political Science and Law, Shanghai, China
- 1 Shanghai University of Political Science and Law, Shanghai, China
- 2 Shanghai University of Political Science and Law, Shanghai, China
- 3 Shanghai University of Political Science and Law, Shanghai, China
Beijing Law Review·Volume 13 (2022)·Pages 204–216·Published 23 February 2022·DOI10.4236/blr.2022.131013
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Abstract
Based on the interpretation on the evolution of theoretical basis of the construction of legal expert system as the clue, this article mainly analyzes and points out the dilemma faced by symbolism and connectionism as the algorithm on construction of legal expert system. Through defeasible reasoning, a contextual-based legal expert system could be realized. The legal expert system should be constructed with the judge as the center character, in which the personality of the judge could not necessarily be eliminated. As a result, the article provides a model of a legal expert system based on dual processing, including factual argumentation and legal argumentation.
KeywordsLegal Expert SystemSymbolismConnectionismDefeasible Reasoning
- Cao, Y. (2021). The Application of Extraterritorial Artificial Intelligence in the Judicial Field. People’s Court Daily, 008.
- Ge, X. (2018). Reality and Prospects of the Application of Artificial Intelligence in Judicial Practice-Taking the Shanghai Court’s Intelligent Assistant Case Handling System for Administrative Cases as a Reference. ECUPL Journal, 21, 67-76.
- Hage, J. (2003). Law and Defeasibility. Artificial Intelligence and Law, 11, 221-243. https://doi.org/10.1023/B:ARTI.0000046011.13621.08
- Ji, D. (2018). Changes in Judicial Power in the Era of Artificial Intelligence. Oriental Law, 1, 125-133.
- Lei, L. (2016). Defend for the Subsumption Model. Peking University Law Journal, 28, 1206-1233.
- Ma, C., Yu, H., & He, B. (2016). Big Data Analysis: Online Public Report of Chinese Judicial Judgment Documents. China Law Review, 4, 195-246.
- Popp, W. G., & Schlink, B. (1975). Judith, a Computer Program to Advise Lawyers in Reasoning a Case. Jurimetrics Journal, 15, 303-314.
- Popple, J. (1996). A Pragmatic Legal Expert System. Dartmouth Publishing Company. https://doi.org/10.2139/ssrn.1335176
- Prakken, H., & Vreeswijk, G. (2002). Logics for Defeasible Argumentation. In D. M. Gabbay, & F. Guenthner (Eds.), Handbook of Philosophical Logic (Vol. 4, pp. 219-318). Kluwer Academic Publishers. https://doi.org/10.1007/978-94-017-0456-4_3
- Song, G. (2019). On the Defeasibility in Jurisprudence. Law and Social Development, 25, 120-135.
- Sun, F., & Fu, R. (2021). The Logical Starting Point of “Weak” Legal Artificial Intelligence Research. Social Scientists, 11, 123-129.
- Toulmin, S., Rieke, R. D., & Janik, A. (1979). An Introduction to Reasoning. Macmillan.
- Wu, D., & Sun, Y. (2021). Towards Explainable Interactive Artificial Intelligence: Motivation, Approach and Research Trend. Journal of Wuhan University (Philosophy and Social Sciences Edition), 74, 16-28.
- Wu, Z. (2006). The Interaction of Legal Logic and Argumentation Logic. Studies in Law and Business, 5, 153-160.
- Xu, J. (2018). The Limits and Future of Artificial Intelligence. Journal of Dialectics of Nature, 40, 27-32.
- Yang, F. (2018). The Function of Discourse Analysis Method in Judicial Research—An Investigation Regarding “Judicial Rationalization” as the Standard Target. ECUPL Journal, 21, 159-169.