Exploring consequences of statutory law through lightweight modeling

The complexity of statutory legislation can generate confusion and disagreement in interpretation even among experts and can leave ordinary citizens disempowered. Technological “solutions”, even with stakeholders’ best interests in mind, can exacerbate this sense of estrangement from the law. We are exploring an alternative application of technology in this area: a digital “sandbox” environment for legislators, lawyers, judges, and citizens to define and explore the consequences of legislation. Our approach employs a “lightweight” method to computational modeling, using automated analysis to uncover hidden assumptions and unintended consequences. As a case study, we are focusing on a number of U.S. statutes that define conditions under which prior convictions can be expunged from an individual’s public record. We use the Alloy modeling language and analyzer to explore consequences of expungement statutes. Starting with the State of Michigan’s Clean Slate Law and then extending to similar statutes in Utah and Arizona, we can model varying interpretations of the law in terms of modular changes to a base model, and then use the Alloy analyzer to explore the consequences of these interpretations. We have developed a user interface for the model that is tuned to the needs of individuals seeking expungement and their legal assistants, determining which convictions within the individual’s record can be expunged under varying interpretations, and explaining why some convictions may not be expunged. This application not only serves as a proof of concept for our larger sandbox vision but also has promise as a useful tool for individuals navigating the complexities of expungement.

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Publication Details

Published
2024-09-02
DOI
https://doi.org/10.1109/vl/hcc60511.2024.00045
Primary Topic
Artificial Intelligence in Law
Type
article
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article

Exploring consequences of statutory law through lightweight modeling

Charles Wallace, Ali Ebnenasir, Joshua Alele-Beals, Nathan Englehart et al.
Artificial Intelligence in Law
article

Exploring consequences of statutory law through lightweight modeling

Charles Wallace, Ali Ebnenasir, Joshua Alele-Beals, Nathan Englehart, Ishaq Kothari
article en

Abstract

The complexity of statutory legislation can generate confusion and disagreement in interpretation even among experts and can leave ordinary citizens disempowered. Technological “solutions”, even with stakeholders’ best interests in mind, can exacerbate this sense of estrangement from the law. We are exploring an alternative application of technology in this area: a digital “sandbox” environment for legislators, lawyers, judges, and citizens to define and explore the consequences of legislation. Our approach employs a “lightweight” method to computational modeling, using automated analysis to uncover hidden assumptions and unintended consequences. As a case study, we are focusing on a number of U.S. statutes that define conditions under which prior convictions can be expunged from an individual’s public record. We use the Alloy modeling language and analyzer to explore consequences of expungement statutes. Starting with the State of Michigan’s Clean Slate Law and then extending to similar statutes in Utah and Arizona, we can model varying interpretations of the law in terms of modular changes to a base model, and then use the Alloy analyzer to explore the consequences of these interpretations. We have developed a user interface for the model that is tuned to the needs of individuals seeking expungement and their legal assistants, determining which convictions within the individual’s record can be expunged under varying interpretations, and explaining why some convictions may not be expunged. This application not only serves as a proof of concept for our larger sandbox vision but also has promise as a useful tool for individuals navigating the complexities of expungement.

Vol. 101
Michigan Technological University (US), Oberlin College (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 72%
Artificial Intelligence in Law
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Exploring consequences of statutory law through lightweight modeling — Charles Wallace, Ali Ebnenasir, et al. · (2024) | TGRS Research Map | TGRS