Models of decision making on guilt and sanctions
Abstract
AI
AI
This paper explores mathematical models of decision making in criminal cases, focusing on the probabilistic approach using Bayesian probability theory, cognitive algebra, and stochastic processes. It highlights the psychological processes behind decisions on guilt and sentencing, suggesting that these decisions may involve different cognitive strategies depending on whether they are made by judges or jurors. The implications of how information is presented, particularly in DNA evidence cases, are analyzed to illustrate the complexities of legal decision-making.
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