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 an...
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| creator | Padhye, Rohan |
| description | 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. |
| doi_str_mv | 10.48550/arxiv.2404.09868 |
| format | Article |
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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
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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.</description><subject>Computer Science - Computation and Language</subject><subject>Computer Science - Computers and Society</subject><subject>Computer Science - Software Engineering</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNpjYJA0NNAzsTA1NdBPLKrILNMzMjEw0TOwtDCz4GRwCc5PKylPLEpVcM1Lz8xLTS3KzEtX8E0tychPKVZwyy9ScPTUdSnKLEvNU3BJTSlNLgEyFXxS0xNzFIJSE4vz84DqeRhY0xJzilN5oTQ3g7yba4izhy7YvviCoszcxKLKeJC98WB7jQmrAAC9sDfL</recordid><startdate>20240415</startdate><enddate>20240415</enddate><creator>Padhye, Rohan</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20240415</creationdate><title>Software Engineering Methods For AI-Driven Deductive Legal Reasoning</title><author>Padhye, Rohan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-arxiv_primary_2404_098683</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Computer Science - Computation and Language</topic><topic>Computer Science - Computers and Society</topic><topic>Computer Science - Software Engineering</topic><toplevel>online_resources</toplevel><creatorcontrib>Padhye, Rohan</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Padhye, Rohan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Software Engineering Methods For AI-Driven Deductive Legal Reasoning</atitle><date>2024-04-15</date><risdate>2024</risdate><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.</abstract><doi>10.48550/arxiv.2404.09868</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Computer Science - Computation and Language Computer Science - Computers and Society Computer Science - Software Engineering |
| title | Software Engineering Methods For AI-Driven Deductive Legal Reasoning |
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