Legal Minds, Algorithmic Decisions: How LLMs Apply Constitutional Principles in Complex Scenarios

Camilla Bignotti, Carolina Camassa
7/29/2024
cs.CLcs.CY

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Abstract

In this paper, we conduct an empirical analysis of how large language models (LLMs), specifically GPT-4, interpret constitutional principles in complex decision-making scenarios. We examine rulings from the Italian Constitutional Court on bioethics issues that involve trade-offs between competing values and compare model-generated legal arguments on these issues to those presented by the State, the Court, and the applicants. Our results indicate that GPT-4 consistently aligns more closely with progressive interpretations of the Constitution, often overlooking competing values and mirroring the applicants' views rather than the more conservative perspectives of the State or the Court's moderate positions. Our experiments reveal a distinct tendency of GPT-4 to favor progressive legal interpretations, underscoring the influence of underlying data biases. We thus underscore the importance of testing alignment in real-world scenarios and considering the implications of deploying LLMs in decision-making processes.

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@article{bignotti2024legal,
  title  = {Legal Minds, Algorithmic Decisions: How LLMs Apply Constitutional Principles in Complex Scenarios},
  author = {Camilla Bignotti and Carolina Camassa},
  year   = {2024},
  eprint = {2407.19760},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2407.19760v2}
}

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