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  1. Ant: a process aware annotation software for regulatory compliance.Raphaël Gyory, David Restrepo Amariles, Gregory Lewkowicz & Hugues Bersini - forthcoming - Artificial Intelligence and Law:1-36.
    Accurate data annotation is essential to successfully implementing machine learning (ML) for regulatory compliance. Annotations allow organizations to train supervised ML algorithms and to adapt and audit the software they buy. The lack of annotation tools focused on regulatory data is slowing the adoption of established ML methodologies and process models, such as CRISP-DM, in various legal domains, including in regulatory compliance. This article introduces Ant, an open-source annotation software for regulatory compliance. Ant is designed to adapt to complex organizational (...)
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  • Thirty years of Artificial Intelligence and Law: the first decade. [REVIEW]Guido Governatori, Trevor Bench-Capon, Bart Verheij, Michał Araszkiewicz, Enrico Francesconi & Matthias Grabmair - 2022 - Artificial Intelligence and Law 30 (4):481-519.
    The first issue of _Artificial Intelligence and Law_ journal was published in 1992. This paper provides commentaries on landmark papers from the first decade of that journal. The topics discussed include reasoning with cases, argumentation, normative reasoning, dialogue, representing legal knowledge and neural networks.
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