Abstract
Judges and jurors must make decisions in an environment of ignoranceand uncertainty for example by hearing statements of possibly unreliable ordishonest witnesses, assessing possibly doubtful or irrelevantevidence, and enduring attempts by the opponents to manipulate thejudge's and the jurors' perceptions and feelings. Three importantaspects of decision making in this environment are the quantificationof sufficient proof, the weighing of pieces of evidence, and therelevancy of evidence. This paper proposes a mathematical frameworkfor dealing with the two first aspects, namely the quantification ofproof and weighing of evidence. Our approach is based on subjectivelogic, which is an extension of standard logic and probability theory,in which the notion of probability is extended by including degrees ofuncertainty. Subjective Logic is a framework for modelling humanreasoning and we show how it can be applied to legalreasoning.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Baldwin, J. 1986. Support logic programming. In: A. Jones et al. (eds.), Fuzzy Sets: Theory and Applications. Reidel.
Cohen, L. 1977. The Probable and the Provable. Clarendon Press. Oxford.
Cohen, M. 1986. An expert system framework for non-monotonic reasoning about probabilistic assumptions. In: L. Kanal and J. Lemmer (eds.), Uncertainty in Artificial Intelligence 1. North-Holland.
Eggleston, R. 1978. Evidence, Proof, and Probability. London: Weidenfeld and Nicholson.
Ellsberg, D. 1961. Risk, Ambiguity, and the Savage Axioms. Quarterly Journal of Ecomonics75, 643–669.
Hunter, A. 1996. Uncertainty in information systems. London: McGraw-Hill.
James, W. 1941. Relevance, probability and the law. California Law Review29, 689–699.
Jø sang, A. 2001. A Logic for Uncertain Probabilities. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems9.3, June 2001.
Jø sang, A. & Knapskog, S. 1998. A Metric for Trusted Systems (full paper). In: Proceedings of the 21st National Information Systems Security Conference. NSA.
Motro, A. & Smets, P. 1997. Uncertainty management in information systems: from needs to solutions. Boston: Kluwer.
PvC. 1968. People vs. Collins. 68 Cal 2d 319; 438 P2d 33.
RvA. 1996. R vs. Adams. 2 Court of Appeal (Criminal Division), R.467.
RvDA. 1997. R vs. Doheny and Adams. 1 Court of Appeal (Criminal Division), R.369.
Shafer, G. 1976. A Mathematical Theory of Evidence. Princeton University Press.
Simon, R. & Mahan, L. 1971. Quantifying burdens of proof. Law and Society Review5, 319–322.
Smets, P. & Kennes, R. 1994. The transferable belief model. Artificial Intelligence66, 191–234.
Smithson, M. 1988. Ignorance and Uncertainty: Emerging Paradigms. Springer.
Thompson, W. & Schumann, E. 1987. Interpretation of statistical evidence in criminal trials: The prosecutor's fallacy and the defense attorney's fallacy. Law and Human Behavior11, 167–187.
Zadeh, L. 1984. Review of Shafer's a mathematical theory of evidence. AI Magazine5, 81–83.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Jøsang, A., Bondi, V.A. Legal reasoning with subjective logic. Artificial Intelligence and Law 8, 289–315 (2000). https://doi.org/10.1023/A:1011219731903
Issue Date:
DOI: https://doi.org/10.1023/A:1011219731903