Publicação
AI Modelling of Counterfactual Thinking for Judicial Reasoning and Governance of Law
| Resumo: | When speaking of moral judgment, we refer to a function of recognizing appropriate or condemnable actions and the possibility of choice between them by agents. Their ability to construct possible causal sequences enables them to devise alternatives in which choosing one implies setting aside others. This internal deliberation requires a cognitive ability, namely that of constructing counterfactual arguments. These serve not just to analyse possible futures, being prospective, but also to analyse past situations, by imagining the gains or losses resulting from alternatives to the actions actually carried out, given evaluative information subsequently known. Counterfactual thinking is in thus a prerequisite for AI agents concerned with Law cases, in order to pass judgement and, additionally, for evaluation of the ongoing governance of such AI agents. Moreover, given the wide cognitive empowerment of counterfactual reasoning in the human individual, namely in making judgments, the question arises of how the presence of individuals with this ability can improve cooperation and consensus in populations of otherwise self-regarding individuals. Our results, using Evolutionary Game Theory (EGT), suggest that counterfactual thinking fosters coordination in collective action problems occurring in large populations and has limited impact on cooperation dilemmas in which such coordination is not required. |
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| Autores principais: | Pereira, Luís Moniz |
| Outros Autores: | Santos, Francisco C.; Lopes, António Barata |
| Assunto: | AI governance Counterfactual thinking Evolutionary game theory Judicial reasoning Computer Science Applications Law Artificial Intelligence |
| Ano: | 2024 |
| País: | Portugal |
| Tipo de documento: | capítulo de livro |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| Resumo: | When speaking of moral judgment, we refer to a function of recognizing appropriate or condemnable actions and the possibility of choice between them by agents. Their ability to construct possible causal sequences enables them to devise alternatives in which choosing one implies setting aside others. This internal deliberation requires a cognitive ability, namely that of constructing counterfactual arguments. These serve not just to analyse possible futures, being prospective, but also to analyse past situations, by imagining the gains or losses resulting from alternatives to the actions actually carried out, given evaluative information subsequently known. Counterfactual thinking is in thus a prerequisite for AI agents concerned with Law cases, in order to pass judgement and, additionally, for evaluation of the ongoing governance of such AI agents. Moreover, given the wide cognitive empowerment of counterfactual reasoning in the human individual, namely in making judgments, the question arises of how the presence of individuals with this ability can improve cooperation and consensus in populations of otherwise self-regarding individuals. Our results, using Evolutionary Game Theory (EGT), suggest that counterfactual thinking fosters coordination in collective action problems occurring in large populations and has limited impact on cooperation dilemmas in which such coordination is not required. |
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