Artificial Intelligence and Legal Analysis: Implications for Legal Education and the Profession
This addresses the problem of AI's role in legal reasoning for legal education and practice, highlighting incremental insights into LLM limitations.
The study examined how legal and non-legal Large Language Models perform legal analysis using the Issue-Rule-Application-Conclusion framework, finding they can conduct basic IRAC analysis but are limited by brief responses, inability to commit to answers, false confidence, and hallucinations.
This article reports the results of a study examining the ability of legal and non-legal Large Language Models to perform legal analysis using the Issue-Rule-Application-Conclusion framework. LLMs were tested on legal reasoning tasks involving rule analysis and analogical reasoning. The results show that LLMs can conduct basic IRAC analysis, but are limited by brief responses lacking detail, an inability to commit to answers, false confidence, and hallucinations. The study compares legal and nonlegal LLMs, identifies shortcomings, and explores traits that may hinder their ability to think like a lawyer. It also discusses the implications for legal education and practice, highlighting the need for critical thinking skills in future lawyers and the potential pitfalls of overreliance on artificial intelligence AI resulting in a loss of logic, reasoning, and critical thinking skills.