Artificial Intelligence and Law 9 (2-3):153-163 (2001)

Lennart Åqvist (1992) proposed a logical theory of legal evidence, based on the Bolding-Ekelöf of degrees of evidential strength. This paper reformulates Åqvist's model in terms of the probabilistic version of the kappa calculus. Proving its acceptability in the legal context is beyond the present scope, but the epistemological debate about Bayesian Law isclearly relevant. While the present model is a possible link to that lineof inquiry, we offer some considerations about the broader picture of thepotential of AI & Law in the evidentiary context. Whereas probabilisticreasoning is well-researched in AI, calculations about the threshold ofpersuasion in litigation, whatever their value, are just the tip of theiceberg. The bulk of the modeling desiderata is arguably elsewhere, if one isto ideally make the most of AI's distinctive contribution as envisaged forlegal evidence research
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DOI 10.1023/A:1017995916308
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References found in this work BETA

Cost-Based Abduction and MAP Explanation.Eugene Charniak & Solomon Eyal Shimony - 1994 - Artificial Intelligence 66 (2):345-374.
Evidence Marshaling for Imaginative Fact Investigation.David A. Schum - 2001 - Artificial Intelligence and Law 9 (2-3):165-188.
Overall Positive Causal Impact.Igal Kvart - 1994 - Canadian Journal of Philosophy 24 (2):205 - 227.
Truth or Proof?: The Criminal Verdict.Bernard S. Jackson - 1998 - International Journal for the Semiotics of Law - Revue Internationale de Sémiotique Juridique 11 (3):227-273.
Emotion, Culture, Communication.Ephraim Nissan - 1997 - Pragmatics and Cognition 5 (2):355-369.

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