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Modelling competing legal arguments using Bayesian model comparison and averaging.

Martin Neil1,2, Norman Fenton1,2, David Lagnado3

  • 11School of Electronic Engineering and Computer Science, Queen Mary, University of London, London, UK.

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This summary is machine-generated.

This study introduces a new method to compare independent Bayesian models of legal arguments. It weights models based on how well they explain trial facts, allowing a single rational judgment from multiple arguments.

Keywords:
Bayesian model comparison and averagingBayesian networksLegal argumentation

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Area of Science:

  • Legal informatics
  • Computational law
  • Bayesian modeling

Background:

  • Traditional Bayesian models integrate legal arguments into a single framework.
  • This integration assumes consistency in variables and causal assumptions, which is often unrealistic for competing legal narratives.

Purpose of the Study:

  • To develop a novel approach for comparing and averaging independently built Bayesian models of legal arguments.
  • To address the challenge of integrating models with inconsistent variables, causal assumptions, or parameterizations.

Main Methods:

  • Comparing independent Bayesian models of legal arguments.
  • Assessing model performance based on their ability to explain or predict trial facts.
  • Weighting models using a Bayesian model comparison and averaging framework, down-weighting those disconfirmed by evidence.

Main Results:

  • A method is presented to evaluate and combine disparate Bayesian legal argument models.
  • Model plausibility is determined by their empirical disconfirmation by trial facts.
  • This approach allows for a plurality of arguments while enabling a single, rational judgment.

Conclusions:

  • The proposed method provides a rational framework for synthesizing multiple, independently developed Bayesian legal argument models.
  • It allows for the incorporation of conflicting arguments by weighting them based on factual evidence.
  • This facilitates a more robust and evidence-based legal decision-making process.