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Causal Models of Legal Cases

  • Conference paper
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AI Approaches to the Complexity of Legal Systems (AICOL 2015, AICOL 2016, AICOL 2016, AICOL 2017, AICOL 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10791))

Abstract

Legal causation is a complex aspect of legal reasoning. Due to its significant role in the attribution of legal responsibility, it is important that there is a clear understanding of the requirements for establishing and reasoning with causal links. This paper presents preliminary results of modelling causal arguments based on the legal decisions with particular focus on physical causation. We introduce a semi-formal framework for reasoning with causation that uses strict and defeasible rules for modelling factual causation arguments in legal cases. We further discuss the complex relation between formal, common sense, norm and policy based considerations of causation in legal decision making with particular focus on their role in comparing alternative causal explanations.

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Notes

  1. 1.

    The current article is version of our semi-formal causal argumentation framework, which was presented at AICOL Workshop, JURIX 2017, Luxembourg, Luxembourg. Another version was presented at the Evidence and Decision Making Workshop in ICAIL 2017, London, United Kingdom; that work is being reworked for publication.

  2. 2.

    The most common approach in law being sine qua non: ‘but for the action, the result would not have happened’.

  3. 3.

    At the initial stages of the study, we annotated the decision identifying causal and accompanying hedging expressions. After identifying the main causal links in the case, we ranked the various expressions in two levels of strength. For instance, ‘a probable causal relation between tetanus toxoid and two injuries’, ‘it is more probably than not the case that tetanus toxoid can cause the injuries suffered here’ are examples of level 2 (usually causal) support.

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Author information

Authors and Affiliations

  1. Law Department, European University Institute, Florence, Italy

    Ruta Liepina & Giovanni Sartor

  2. CIRSFID, University of Bologna, Bologna, Italy

    Giovanni Sartor

  3. School of Law and Department of Computer Science, Swansea University, Swansea, UK

    Adam Wyner

Authors
  1. Ruta Liepina
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  2. Giovanni Sartor
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  3. Adam Wyner
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Corresponding author

Correspondence to Ruta Liepina .

Editor information

Editors and Affiliations

  1. University of Turin, Turin, Italy

    Ugo Pagallo

  2. University of Bologna, Bologna, Italy

    Monica Palmirani

  3. La Trobe University, Melbourne, VIC, Australia

    Pompeu Casanovas

  4. University of Bologna, Bologna, Italy

    Giovanni Sartor

  5. Inria - Sophia Antipolis-Méditerranée, Sophia Antipolis, France

    Serena Villata

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Liepina, R., Sartor, G., Wyner, A. (2018). Causal Models of Legal Cases. In: Pagallo, U., Palmirani, M., Casanovas, P., Sartor, G., Villata, S. (eds) AI Approaches to the Complexity of Legal Systems. AICOL AICOL AICOL AICOL AICOL 2015 2016 2016 2017 2017. Lecture Notes in Computer Science(), vol 10791. Springer, Cham. https://doi.org/10.1007/978-3-030-00178-0_11

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  • DOI: https://doi.org/10.1007/978-3-030-00178-0_11

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  • Print ISBN: 978-3-030-00177-3

  • Online ISBN: 978-3-030-00178-0

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