RSS and CfS Event on Decision-Support in Litigation

Traditionally, much work at the interface of statistics and the law has focussed on the interpretation of evidence and relatively little on strategies for running legal cases. As litigation can have huge implications for individuals and businesses and involve large sums of money, effective decision-making strategies are critical to ensure that good decisions are being made at each stage of the process. There are huge opportunities for statisticians and data scientists to work with lawyers to solve these problems and improve the legal decision-making process but there are many difficult challenges to resolve, for example how to collect appropriate datasets. At this event we will hear from three people working on interdisciplinary problems in this area. Following the talks we will have an open discussion aiming to identify both the key challenges and the ways in which statisticians might be able to contribute. 

This is a joint event organised by the Royal Statistical Society Statistics and Law Section and the Edinburgh Centre for Statistics.

Schedule (abstracts below):

14.00 - 14.40 John MacKenzie, Shepherd and Wedderburn

14.40 - 15.20 Dr Alex Biedermann, University of Lausanne

15.20 - 15.40 Tea break

15.40 - 16.20 Dr Wen Zhang, London School of Economics

16.20 - 17.00 Panel discussion, chaired by Jamie Gardiner, Ampersand Advocates

This event is free to attend but registration is required. 

Abstract: John will share his experience of being a dispute resolution lawyer, and the reality of legal process and the litigation process at the moment. Looking at both the practical reality of a lawyer’s evidence gathering, and the psychology of dispute resolution, his presentation will consider if and how data, data science and statistics might revolutionise (or maybe just help) the dispute resolution world.

Abstract: Decision problems encountered by litigants present challenging features, such as multiple competing propositions, variable costs and uncertain process outcomes. This complicates analyses based on formal decision-theoretic models and the use of diagrammatic devices such as decision trees which mainly provide static views of selected features of a given problem. Moreover, strategic planning and the assessment of legal tactics – given a party’s standpoint – encounter further intricacies when considerations are extended to information provided by forensic science experts. This is because introducing results of forensic examinations may impact on the probability of various trial outcomes and hence play an important role in a party’s strategic analysis. This presentation analyses and discusses examples of decision problems at the interface of the law and forensic science using influence diagrams. Such models can be implemented through commercially and academically available software systems. These normative decision support structures represent core computational models that can be paired with other litigation-support systems, to help address a variety of questions in strategic legal decision analysis.

Abstract: The application of data science methodologies to civil litigation is a rapidly emerging field, which lags behind applications of statistical methods in criminal forensic science. This presentation will discuss how to apply advanced methodologies to the civil litigation process, particularly sequential game theory and decision trees. The benefit will be to decision support in the semi-cooperative environment of the negotiation. Progress will benefit national and professional objectives to decrease the cost and duration of litigation. Wider benefits will include contract design and better use of judicial resources, and in insurance cases, greater fairness to both claimant and defendant.