Source: Yale Journal on Regulation
In her article, Susan Azarndyar explores the limitations of generative AI tools in the context of administrative law research. While AI is increasingly being used to assist legal professionals with research tasks, Azarndyar argues that generative AI tools like GPT-3 have significant shortcomings, particularly when applied to complex areas such as administrative law.

Azarndyar notes that while generative AI can process vast amounts of data and generate legal text quickly, it struggles with the nuances and intricacies of administrative law. AI-generated content often lacks the depth and contextual understanding required for thorough legal analysis. This can lead to errors in interpretation, misrepresentation of legal principles, or the omission of critical information that would be readily apparent to a trained legal expert.

Moreover, the use of AI in administrative law research raises ethical concerns, particularly around accountability. With AI tools generating legal content, it can be difficult to trace back and verify the original sources of information, increasing the risk of inaccurate or misleading outputs. The article also points out that generative AI is not yet adept at identifying the evolving nature of legal precedents and regulatory changes, which are common in administrative law.

Azarndyar emphasizes that while AI can be a valuable tool for streamlining repetitive tasks, such as document review or data extraction, it should not replace the nuanced judgment and expertise of human legal professionals. For now, AI in administrative law research is best viewed as a supplementary tool, rather than a primary resource for legal analysis.

The article calls for further development of AI tools that can better understand legal contexts and for clear ethical frameworks to govern their use in legal research. As AI continues to evolve, there is potential for it to assist more meaningfully in areas like administrative law, but human oversight will remain crucial.