This work deals with the implementation of Artificial Intelligence (AI), and especially of Machine-learning (ML) tools, to the area of civil law disputes. Through the application of mathematical models for the qualification and the measurement of legal situations, the legal values can be objectively determined, while preserving a certain (and specified) domain of discretional power for the policymaker. This system might be experimentally implemented within the realm of tort law disputes, and then be assessed for its possible implementation to other sectors of civil law litigation. This attempt would impose the design of cooperation among machine (AI) and human (NI) agents, guaranteeing to the human agent the role of last-resort decision-maker. Finally some aspects concerning the huge impact of such an experiment on legal practice and theory will be suggested, with particular regards to the prevention and the contrast of corruption, in its broader sense, within the area of civil law adjudications, due to the fact that this system would enhance accountability for any legal operator.
Minima non curat praetor! Arguing for a strategic experimental implementation of AI into the Italian Tort law disputes dynamics
Ferrara M., Gaglioti A. R., Lucisano D., Neri I. S. (2021) "Minima non curat praetor! Arguing for a strategic experimental implementation of AI into the Italian Tort law disputes dynamics " Journal of Ethics and Legal Technologies, 3(1), 95-110. DOI: 10.14658/pupj-JELT-2021-1-6
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Journal of Ethics and Legal Technologies
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