Large Legal Fictions: Profiling Legal Hallucinations in Large Language Models
Center for Economic and Policy Research · Yale University · +3 more institutions
Abstract
Abstract Do large language models (LLMs) know the law? LLMs are increasingly being used to augment legal practice, education, and research, yet their revolutionary potential is threatened by the presence of “hallucinations”—textual output that is not consistent with legal facts. We present the first systematic evidence of these hallucinations in public-facing LLMs, documenting trends across jurisdictions, courts, time periods, and cases. Using OpenAI’s ChatGPT 4 and other public models, we show that LLMs hallucinate at least 58% of the time, struggle to predict their own hallucinations, and often uncritically accept users’ incorrect legal assumptions. We conclude by cautioning against the rapid and…
Citation impact
- FWCI
- 371.73
- Percentile
- 100%
- References
- 158
Authors
4- MDMatthew DahlCorresponding
Center for Economic and Policy Research, Yale University, Stanford Medicine, Stanford University
- VMVarun Magesh
Institute on Governance
- MSMirac Suzgun
Center for Economic and Policy Research, Yale University, Stanford Medicine, Stanford University
- DEDaniel E. Ho
Center for Economic and Policy Research, Yale University, Stanford Medicine, Stanford University
Topics & keywords
- Typology
- Hallucinating
- Profiling (computer programming)
- Psychology
- Criminology
- Law
- Political science
- Social psychology
- Peace, Justice and strong institutions