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Compliance checking on first-order knowledge with conflicting and compensatory norms: a comparison among currently available technologies

Livio Robaldo Orcid Logo, Sotiris Batsakis, Roberta Calegari, Francesco Calimeri, Megumi Fujita, Guido Governatori, Maria Concetta Morelli, Francesco Pacenza, Giuseppe Pisano, Ken Satoh, Ilias Tachmazidis, Jessica Zangari

Artificial Intelligence and Law

Swansea University Author: Livio Robaldo Orcid Logo

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DOI (Published version): 10.1007/s10506-023-09360-z

Abstract

This paper analyses and compares some of the automated reasoners that have been used in recent research for compliance checking. Although the list of the considered reasoners is not exhaustive, we believe that our analysis is representative enough to take stock of the current state of the art in the...

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Published in: Artificial Intelligence and Law
ISSN: 0924-8463 1572-8382
Published: Springer Science and Business Media LLC 2023
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URI: https://cronfa.swan.ac.uk/Record/cronfa63481
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Abstract: This paper analyses and compares some of the automated reasoners that have been used in recent research for compliance checking. Although the list of the considered reasoners is not exhaustive, we believe that our analysis is representative enough to take stock of the current state of the art in the topic. We are interested here in formalizations at the first-order level. Past literature on normative reasoning mostly focuses on the propositional level. However, the propositional level is of little usefulness for concrete LegalTech applications, in which compliance checking must be enforced on (large) sets of individuals. Furthermore, we are interested in technologies that are freely available and that can be further investigated and compared by the scientific community. In other words, this paper does not consider technologies only employed in industry and/or whose source code is non-accessible. This paper formalizes a selected use case in the considered reasoners and compares the implementations, also in terms of simulations with respect to shared synthetic datasets. The comparison will highlight that lot of further research still needs to be done to integrate the benefits featured by the different reasoners into a single standardized first-order framework, suitable for LegalTech applications. All source codes are freely available at https://github.com/liviorobaldo/compliancecheckers, together with instructions to locally reproduce the simulations.
Keywords: Compliance checking, first-order knowledge, technologies
College: Faculty of Humanities and Social Sciences
Funders: Livio Robaldo has been supported by the Legal Innovation Lab Wales operation within Swansea University’s Hillary Rodham Clinton School of Law. The operation has been part-funded by the European Regional Development Fund through the Welsh Government. Francesco Calimeri, Maria Concetta Morelli, Francesco Pacenza, and Jessica Zangari acknowledge the support of the PNRR project FAIR - Future AI Research (PE00000013), Spoke 9 - Green-aware AI, under the NRRP MUR program funded by the NextGenerationEU, and the support of the project PRIN PE6, Title: “Declarative Reasoning over Streams”, funded by the Italian Ministero dell’Università, dell’Istruzione e della Ricerca (MIUR), CUP:H24I17000080001. The research of Roberta Calegari and Giuseppe Pisano has been partially supported by the “CompuLaw” project, funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant Agreement No. 833647).

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