A Preliminary Historical Perspective

  • Ephraim Nissan
Part of the Law, Governance and Technology Series book series (LGTS, volume 5)


This introductory chapter makes considerations about the thematics, the organisation of the book, and (along very broad lines) the state of the art, the latter’s historical development, and its publication forums. The book is organised around three poles: the modelling of reasoning, the modelling of argumentation and its application to narratives, and a cluster of data mining techniques and the specifics of forensic science disciplines. We mention the controversy, among legal scholars, among those willing to accept probabilistic models, and those who want instead a ranking of the relative plausibility of alternative accounts of a legal narrative, without committing to a Bayesian framework. Artificial intelligence is able to contribute to both camps, and has already done so. Bayesian networks are often applied to causality also in the legal domain, but those arguing against probabilistic quantification are at present vindicated by the rise of the plausibility ranking of legal narratives (Section “Bex’s Approach to Combining Stories and Arguments in Sense-Making Software for Crime Investigation”, in Chapter “The Narrative Dimension”, and Section “Another Approach to Critical Questions” in Chapter “Argumentation”) within argumentation research (Chapter “Argumentation”). Artificial Intelligence (AI) practitioners need to exercise care, lest methodological flaws vitiate their tools in the domain with some legal scholars, let alone opponents in litigation. There would be little point for computer scientists to develop tools for legal evidence, if legal scholars would find them vitiated ab initio. This is especially true of tools that would reason about the evidence in criminal cases, in view of fact-finding in the courtroom: whether to convict or not – this being different from the situation of the police, whose aim is to detect crime and to find suspects, without having the duty of proving their guilt beyond reasonable doubt, which is the task of the prosecutors. Tools helping the prosecutor to predict an outcome and choose whether to prosecute are not as central to, and problematic for, the Bayesian controversy, as prescriptive models of judicial decision-making are. This chapter also says something about the communities of users that may benefit from advances in AI & Law technology. In particular, we devote some discussion to computer assistance in policing.


Artificial Intelligence Forensic Science Computer Tool Legal Scholar Artificial Intelligence Technique 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Department of ComputingGoldsmiths’ College, University of LondonLondonEngland

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