research-article

Scenario analytics: analyzing jury verdicts to evaluate legal case outcomes

Authors:

Jack G. Conrad,

Khalid Al-KofahiAuthors Info & Claims

ICAIL '17: Proceedings of the 16th edition of the International Conference on Articial Intelligence and Law

Pages 29 - 37

https://doi.org/10.1145/3086512.3086516

Published: 12 June 2017 Publication History

Abstract

Scenario Analytics is a type of analysis that focuses on the evaluation of different scenarios, their merits and their consequences. In the context of the legal domain, this could be in the form of analyzing large databases of legal cases, their facts and their claims, to answer questions such as: Do the current facts warrant litigation?, Is the litigation best pursued before a judge or a jury?, How long is it likely to take?, and What are the best strategies to use for achieving the most favorable outcome for the client? In this work, we report on research directed at answering such questions. We use one of a set of jury verdicts databases totaling nearly a half-million records. At the same time, we conduct a series of experiments that answer key questions and build, sequentially, a powerful data-driven legal decision support system, one that can assist an attorney to differentiate more effective from less effective legal principles and strategies. Ultimately, it represents a productivity tool that can help a litigation attorney make the most prudent decisions for his or her client.

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Cited By

Ganguly DConrad JGhosh KGhosh SGoyal PBhattacharya PNigam SPaul S(2023)Legal IR and NLP: The History, Challenges, and State-of-the-ArtAdvances in Information Retrieval10.1007/978-3-031-28241-6_34(331-340)Online publication date: 16-Mar-2023
https://doi.org/10.1007/978-3-031-28241-6_34
Rodríguez Oconitrillo LVargas JCamacho ABurgos ÁCorchado J(2021)RYEL: An Experimental Study in the Behavioral Response of Judges Using a Novel Technique for Acquiring Higher-Order Thinking Based on Explainable Artificial Intelligence and Case-Based ReasoningElectronics10.3390/electronics1012150010:12(1500)Online publication date: 21-Jun-2021
https://doi.org/10.3390/electronics10121500
Naqvi A(2020)Forensic AccountingArtificial Intelligence for Audit, Forensic Accounting, and Valuation10.1002/9781119601906.ch13(227-239)Online publication date: 3-Aug-2020
https://doi.org/10.1002/9781119601906.ch13
Show More Cited By

Index Terms

Scenario analytics: analyzing jury verdicts to evaluate legal case outcomes
1. Information systems
  1. Information retrieval
    1. Specialized information retrieval
      1. Environment-specific retrieval
  2. Information systems applications
    1. Data mining
      1. Clustering
    2. Decision support systems
      1. Data analytics

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Published In

cover image ACM Conferences

ICAIL '17: Proceedings of the 16th edition of the International Conference on Articial Intelligence and Law

June 2017

299 pages

ISBN:9781450348911

DOI:10.1145/3086512

Conference Chair:
Jeroen Keppens
King's College London, United Kingdom
,
Program Chair:
Guido Governatori
Data61, CSIRO, Australia

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGAI: ACM Special Interest Group on Artificial Intelligence

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 June 2017

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ICAIL '17

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SIGAI

ICAIL '17: Sixteenth International Conference on Artificial Intelligence and Law

June 12 - 16, 2017

London, United Kingdom

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Overall Acceptance Rate 69 of 169 submissions, 41%

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Cited By

Ganguly DConrad JGhosh KGhosh SGoyal PBhattacharya PNigam SPaul S(2023)Legal IR and NLP: The History, Challenges, and State-of-the-ArtAdvances in Information Retrieval10.1007/978-3-031-28241-6_34(331-340)Online publication date: 16-Mar-2023
https://doi.org/10.1007/978-3-031-28241-6_34
Rodríguez Oconitrillo LVargas JCamacho ABurgos ÁCorchado J(2021)RYEL: An Experimental Study in the Behavioral Response of Judges Using a Novel Technique for Acquiring Higher-Order Thinking Based on Explainable Artificial Intelligence and Case-Based ReasoningElectronics10.3390/electronics1012150010:12(1500)Online publication date: 21-Jun-2021
https://doi.org/10.3390/electronics10121500
Naqvi A(2020)Forensic AccountingArtificial Intelligence for Audit, Forensic Accounting, and Valuation10.1002/9781119601906.ch13(227-239)Online publication date: 3-Aug-2020
https://doi.org/10.1002/9781119601906.ch13
Broughton G(2019)Vertical precedents in formal models of precedential constraintArtificial Intelligence and Law10.1007/s10506-019-09244-1Online publication date: 8-Feb-2019
https://doi.org/10.1007/s10506-019-09244-1
Raghupathi VZhou YRaghupathi W(2018)Legal Decision Support: Exploring Big Data Analytics Approach to Modeling Pharma Patent Validity CasesIEEE Access10.1109/ACCESS.2018.28590526(41518-41528)Online publication date: 2018
https://doi.org/10.1109/ACCESS.2018.2859052

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