Software Engineering Methods for AI-Driven Deductive Legal Reasoning

The recent proliferation of generative artificial intelligence (AI) technologies such as pre-trained large language models (LLMs) has opened up new frontiers in computational law. An exciting area of development is the use of AI to automate the deductive rule-based reasoning inherent in statutory and contract law. This paper argues that such automated deductive legal reasoning can now be viewed from the lens of software engineering, treating LLMs as interpreters of natural-language programs with natural-language inputs. We show how it is possible to apply principled software engineering techniques to enhance AI-driven legal reasoning of complex statutes and to unlock new applications in automated meta-reasoning such as mutation-guided example generation and metamorphic property-based testing.

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Publication Details

Published
2024-10-17
DOI
https://doi.org/10.1145/3689492.3690050
Citations
3
Primary Topic
Software Testing and Debugging Techniques
Type
article
Field-Weighted Citation Impact
1.46
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article

Software Engineering Methods for AI-Driven Deductive Legal Reasoning

Rohan Padhye
3 citations
Software Testing and Debugging Techniques
1.46
article

Software Engineering Methods for AI-Driven Deductive Legal Reasoning

Rohan Padhye
article en
3 citations

Abstract

The recent proliferation of generative artificial intelligence (AI) technologies such as pre-trained large language models (LLMs) has opened up new frontiers in computational law. An exciting area of development is the use of AI to automate the deductive rule-based reasoning inherent in statutory and contract law. This paper argues that such automated deductive legal reasoning can now be viewed from the lens of software engineering, treating LLMs as interpreters of natural-language programs with natural-language inputs. We show how it is possible to apply principled software engineering techniques to enhance AI-driven legal reasoning of complex statutes and to unlock new applications in automated meta-reasoning such as mutation-guided example generation and metamorphic property-based testing.

Carnegie Mellon University (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 15%
Software Testing and Debugging Techniques
1.46
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