作者: Ephraim Nissan , None
DOI: 10.1007/978-90-481-8990-8_1
关键词: Sociology 、 Reasonable doubt 、 Epistemology 、 State (polity) 、 Argumentation theory 、 Ranking (information retrieval) 、 Narrative 、 Duty 、 Causality 、 Convict
摘要: This introductory chapter makes considerations about the thematics, organisation of book, and (along very broad lines) state art, latter’s historical development, its publication forums. The book is organised around three poles: modelling reasoning, argumentation application to narratives, a cluster data mining techniques specifics forensic science disciplines. We mention controversy, among legal scholars, those willing accept probabilistic models, who want instead ranking relative plausibility alternative accounts narrative, without committing Bayesian framework. Artificial intelligence able contribute both camps, has already done so. networks are often applied causality also in domain, but arguing against quantification at present vindicated by rise narratives (Section “Bex’s Approach Combining Stories Arguments Sense-Making Software for Crime Investigation”, Chapter “The Narrative Dimension”, Section “Another Critical Questions” “Argumentation”) within research (Chapter “Argumentation”). Intelligence (AI) practitioners need exercise care, lest methodological flaws vitiate their tools domain with some let alone opponents litigation. There would be little point computer scientists develop evidence, if scholars find them vitiated ab initio. especially true that reason evidence criminal cases, view fact-finding courtroom: whether convict or not – this being different from situation police, whose aim detect crime suspects, having duty proving guilt beyond reasonable doubt, which task prosecutors. Tools helping prosecutor predict an outcome choose prosecute as central to, problematic for, prescriptive models judicial decision-making are. says something communities users may benefit advances AI & Law technology. In particular, we devote discussion assistance policing.