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Language Model Interpretability and Empirical Legal Studies

Author

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  • Michael A. Livermore
  • Felix Herron
  • Daniel N. Rockmore

Abstract

Large language models (LLMs) now perform extremely well on many natural language processing tasks. Their ability to convert legal texts to data may offer empirical legal studies (ELS) scholars a low-cost alternative to research assistants in many contexts. However, less complex computational language models, such as topic modeling and sentiment analysis, are more interpretable than LLMs. In this paper we highlight these differences by comparing LLMs with less complex models on three ELS-related tasks. Our findings suggest that ELS research will - for the time being - benefit from combining LLMs with other techniques to optimize the strengths of each approach.

Suggested Citation

  • Michael A. Livermore & Felix Herron & Daniel N. Rockmore, 2024. "Language Model Interpretability and Empirical Legal Studies," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 180(2), pages 244-276.
    • Handle: RePEc:mhr:jinste:urn:doi:10.1628/jite-2024-0009
    DOI: 10.1628/jite-2024-0009
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    More about this item

    Keywords

    empirical legal studies; natural language processing; interpretability; language models; computational analysis of law; law-as-data;
    All these keywords.

    JEL classification:

    • K10 - Law and Economics - - Basic Areas of Law - - - General (Constitutional Law)
    • K40 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - General
    • K49 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Other

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