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Fact finding in judicial proceedings is a dynamic process. This collection of papers considers whether computational methods or other formal logical methods developed in disciplines such as artificial intelligence, decision theory, and probability theory can facilitate the study and management of dynamic evidentiary and inferential processes in litigation. The papers gathered here have several epicenters, including (i) the dynamics of judicial proof, (ii) the relationship between artificial intelligence or formal analysis and "common sense," (iii) the logic of factual inference, including (a) the relationship between causality and inference and (b) the relationship between language and factual inference, (iv) the logic of discovery, including the role of abduction and serendipity in the process of investigation and proof of factual matters, and (v) the relationship between decision and inference.
Table des matières
Making Sense of the Process of Proof in Litigation.- One: Common Sense Reasoning.- Artificial Intelligence, Mindreading, and Reasoning in Law.- Common Sense, Rationality and the Legal Process.- What Is "Common" about Common Sense? Cautionary Tales for Travelers Crossing Disciplinary Boundaries.- Two: Fuzzy and Rough Logic.- From Computing with Numbers to Computing with Words: From Manipulation of Measurements to Manipulation of Perceptions.- Fuzzy Logic and Its Application to Legal Reasoning - A Comment to Professor Zadeh.- A Primer on Rough Sets: A New Approach to Drawing Conclusions from Data.- Three: The Structure of Factual Inference in Judicial Settings.- Alternative Views of Argument Construction from a Mass of Evidence.- Explaining Relevance.- Theories of Uncertainty: Explaining the Possible Sources of Error in Inferences.- Models of Data Generation vs. Models of Events that Generate Data.- Four: Dynamic Inference and Choice in Dynamic Environments.- Action and Procedure in Reasoning.- Decision Analysis and Law.- Five: Abductive Inference.- Serendipity and Abduction in Proofs, Presumptions and Emerging Laws.- On the Proof Dynamics of Inference to the Best Explanation.- Species of Abductive Reasoning in Fact Investigation in Law.- Abductive Reasoning in Law: Taxonomy and Inference to the Best Explanation.- Six: From Theory to Practice: "Intelligent" Procedures for Drawing Inferences in Static and Dynamic Legal Environments.- Computational Inference for Evidential Reasoning in Support of Judicial Proof.- Logical Argumentation, Abduction and Bayesian Decision Theory: A Bayesian Approach to Logical Arguments and Its Application to Legal Evidential Reasoning.- Structured Deliberation for Dynamic Uncertain Inference.- Seven: Judicial Proof and EconomicRationality.- Saving Desdemona.- Othello Could Not Optimize: Economics, Hearsay, and Less Adversary Systems.- Eight: Causality.- Causality and Responsibility.- Liability for Increased Risk of Harm: A Lawyer's Response to Professor Shafer.
Résumé
Fact finding in judicial proceedings is a dynamic process. This collection of papers considers whether computational methods or other formal logical methods developed in disciplines such as artificial intelligence, decision theory, and probability theory can facilitate the study and management of dynamic evidentiary and inferential processes in litigation. The papers gathered here have several epicenters, including (i) the dynamics of judicial proof, (ii) the relationship between artificial intelligence or formal analysis and "common sense," (iii) the logic of factual inference, including (a) the relationship between causality and inference and (b) the relationship between language and factual inference, (iv) the logic of discovery, including the role of abduction and serendipity in the process of investigation and proof of factual matters, and (v) the relationship between decision and inference.
