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  1. Counterfactuals for causal responsibility in legal contexts.Holger Andreas, Matthias Armgardt & Mario Gunther - 2023 - Artificial Intelligence and Law 31 (1):115-132.
    We define a formal semantics of conditionals based on _normatively ideal worlds_. Such worlds are described informally by Armgardt (Gabbay D, Magnani L, Park W, Pietarinen A-V (eds) Natural arguments: a tribute to john woods, College Publications, London, pp 699–708, 2018) to address well-known problems of the counterfactual approach to causation. Drawing on Armgardt’s proposal, we use iterated conditionals in order to analyse causal relations in scenarios of multi-agent interaction. This results in a refined counterfactual approach to causal responsibility in (...)
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  • Modelling last-act attempted crime in criminal law.Jiraporn Pooksook, Phan Minh Dung, Ken Satoh & Giovanni Sartor - 2019 - Journal of Applied Non-Classical Logics 29 (4):327-357.
    In the court of law, a person can be punished for attempting to commit a crime. An open issue in the study of Artificial Intelligence and Law is whether the law of attempts could be formally modelled. There are distinct legal rules for determining attempted crime whereas the last-act rule (also called proximity rule) represents the strictest approach. In this paper, we provide a formal model of the last-act rule using structured argumentation.
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  • Definitions of intent suitable for algorithms.Hal Ashton - 2022 - Artificial Intelligence and Law 31 (3):515-546.
    This article introduces definitions for direct, means-end, oblique (or indirect) and ulterior intent which can be used to test for intent in an algorithmic actor. These definitions of intent are informed by legal theory from common law jurisdictions. Certain crimes exist where the harm caused is dependent on the reason it was done so. Here the actus reus or performative element of the crime is dependent on the mental state or mens rea of the actor. The ability to prosecute these (...)
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