Converting copyright legislation into machine-executable code: Interpretation, coding validation and legal alignment
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Huggins, A
Governatori, G
Buckley, J
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São Paulo Brazil
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Abstract
A critical challenge in "Rules as Code"("RaC") initiatives is enhancing legal accuracy. In this paper, we present the preliminary results of a two-week, first of its kind experiment that aims to shed light on how different legally trained people interpret and convert Australian Commonwealth legislation into machine-executable code. We find that coders collaboratively agreeing on key legal terms, or atoms, before commencing independent coding work can significantly increase the similarity of their encoded rules. Participants nonetheless made a range of divergent interpretive choices, which we argue are most likely due to: (1) the complexity of statutory interpretation, (2) encoded provisions having varying levels of granularity, and (3) the functionality of our coding language. Based on these findings, we draw an important distinction between processes for technical validation of encoded rules, which focus on ensuring rules adhere to select coding languages and conventions, and processes of legal alignment, which we conceptualise as enhancing congruence between the encoded provisions and the true meaning of the statutory text in line with the modern approach to statutory interpretation. We argue that these processes are distinct but both critically important in enhancing the accuracy of encoded rules. We conclude by emphasising the need in RaC initiatives for multi-disciplinary expertise across specific legal subject matters, statutory interpretation and technical programming.
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Proceedings of the 18th International Conference on Artificial Intelligence and Law, ICAIL 2021
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Information systems
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Witt, A; Huggins, A; Governatori, G; Buckley, J, Converting copyright legislation into machine-executable code: Interpretation, coding validation and legal alignment, Proceedings of the 18th International Conference on Artificial Intelligence and Law, ICAIL 2021, 2021, pp. 139-148