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Identification of Legislative Errors

Authors:

Michał Araszkiewicz,

Enrico Francesconi,

Tomasz ZurekAuthors Info & Claims

ICAIL '23: Proceedings of the Nineteenth International Conference on Artificial Intelligence and Law

Pages 2 - 11

https://doi.org/10.1145/3594536.3595172

Published: 07 September 2023 Publication History

Abstract

We present an approach designed to support the process of legislative drafting by helping to detect errors in a normative text. It is based on a framework allowing for representation and comparison of structure and semantic content of legal provisions. Such comparison serves as a starting point for detection of (potential) legislative errors. The approach provides in particular criteria to select provisions to be compared, related to the phenomenon of provisions overlapping. We show that specific cases of such an overlap may amount to legislative errors. The presented framework enables a precise and transparent account of these errors. We also acknowledge that textual provisions enable various interpretations, while the error methodology detection assumes that the semantic representation of provisions is a result of a specific interpretation. We introduce the notion of Constraining Interpretive Rules which are used to evaluate the acceptability of specific interpretations of legal provisions. We discuss the features of the model on a real example and we present an implementation of the approach by using semantic technologies.

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Cited By

Schumann GGómex J(2024)Detection of Conflicts, Contradictions and Inconsistencies in Regulatory Documents: A Literature Review2024 Fifth International Conference on Intelligent Data Science Technologies and Applications (IDSTA)10.1109/IDSTA62194.2024.10747003(81-88)Online publication date: 24-Sep-2024
https://doi.org/10.1109/IDSTA62194.2024.10747003

Index Terms

Identification of Legislative Errors
1. Applied computing
  1. Law, social and behavioral sciences
    1. Law
2. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
      1. Reasoning about belief and knowledge

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cover image ACM Other conferences

ICAIL '23: Proceedings of the Nineteenth International Conference on Artificial Intelligence and Law

June 2023

499 pages

ISBN:9798400701979

DOI:10.1145/3594536

Conference Chair:
Francisco Andrade
University of Minho, Portugal
,
Program Chair:
Matthias Grabmair
Technical University of Munich, Germany

Copyright © 2023 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGAI: ACM Special Interest Group on Artificial Intelligence
AAAI: Am Assoc for Artifical Intelligence

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New York, NY, United States

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Published: 07 September 2023

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ICAIL 2023

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ICAIL 2023: Nineteenth International Conference on Artificial Intelligence and Law

June 19 - 23, 2023

Braga, Portugal

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Cited By

Schumann GGómex J(2024)Detection of Conflicts, Contradictions and Inconsistencies in Regulatory Documents: A Literature Review2024 Fifth International Conference on Intelligent Data Science Technologies and Applications (IDSTA)10.1109/IDSTA62194.2024.10747003(81-88)Online publication date: 24-Sep-2024
https://doi.org/10.1109/IDSTA62194.2024.10747003

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