When AI Gets the Law Wrong: A Tale of Hallucinations and Hubris
The introverted bully, Law, is on the fence about artificial intelligence. Here's why.
Picture a courtroom in Chicago, where a seasoned attorney stands before a judge, citing a precedent-setting case from the Seventh Circuit. The only problem? The case doesn't exist. It never did. The citation, pulled from an AI legal research tool, is a ghost - a digital hallucination spawned from the neural networks of machine learning.
This isn't fiction. Just two weeks ago, a lawyer faced threats of sanctions after including an AI-hallucinated court opinion in a settlement demand. The mistake wasn't one of legal knowledge, but rather a cautionary tale of modern legal practice: multiple browser windows open, various drafts in progress, and the fatal error of copying the wrong version into a final document.
The Tension of Tradition and Technology
The legal profession finds itself at a crossroads. On one side stands centuries of tradition, where precision and precedent reign supreme. On the other, the crushing weight of archaic procedures that make legal services increasingly unaffordable for many Americans. As one Chicago attorney who recently launched a legal tech startup puts it, "The cost of task completion easily outstrips the benefit of ever getting something done."
A recent Stanford study illuminates this dilemma. Researchers tested over 200 legal queries across major platforms including Lexis+ AI, Westlaw's AI-Assisted Research, and Thomson Reuters' Ask Practical Law AI. The results were sobering: even the best-performing tool, Lexis+ AI, hallucinated 17% of the time. Westlaw's system fared worse, with errors in one-third of its responses.
The Anatomy of a Legal Hallucination
Why do these sophisticated systems struggle so particularly with case citations? The answer lies in the nature of legal language itself. Consider a standard case citation: Brown v. Board of Education of Topeka, 347 U.S. 483 (1954). To a lawyer, this is a precise identifier - as specific as a person's Social Security number. But to an AI, it's just another pattern of words and punctuation, similar to any other structured text.
"The difference to lawyers is that one is a noun, the other isn't," explains our Chicago attorney. "The Brown decision is to legal reasoning what an object is in programming. Both exist as intangible things in the non-physical universe."
Patterns of Failure
The Stanford study identified several common types of AI hallucinations:
- Complete fabrication of nonexistent cases
- Misattribution of real holdings to wrong courts
- Confusion between party arguments and court holdings
- Incorrect claims about one court overturning another's decision
These aren't random errors. They reveal fundamental limitations in how AI processes legal information. When an AI encounters phrases like "versus" near terms like "civil rights" and "9th Circuit," it sometimes treats them as conversational elements rather than precise legal identifiers.
The Human Factor
But technology isn't the only culprit. Human nature plays its part too. Lawyers, traditionally risk-averse and under constant pressure, find themselves caught between their professional duty of accuracy and the allure of AI's efficiency. The Stanford researchers found that even experienced attorneys could be misled by AI's confident presentation of incorrect information.
A Path Forward
The solution isn't to abandon AI entirely, but to understand its limitations and implement safeguards. Some legal tech developers are already taking steps to verify citations automatically, similar to how Perplexity has demonstrated with general knowledge queries.
Conclusion
The legal profession stands at an inflection point. The promise of AI to democratize legal services by making them more efficient and affordable is real. But so too are the risks of hallucinated case law undermining the very foundation of legal reasoning. The path forward requires a delicate balance: embracing innovation while maintaining the profession's core commitment to accuracy and truth.
Perhaps the greatest lesson from the Stanford study isn't about AI at all, but about human judgment. In a profession where being wrong can have profound consequences, the ability to verify, question, and think critically becomes more important than ever. As one attorney in the study noted, "AI is very sycophantic, a total goody two-shoes that really really wants to help. Being accurate isn't always helping."
The future of legal practice will belong to those who can harness AI's capabilities while maintaining the critical thinking and judgment that have always been at the heart of good lawyering. After all, the law has been making up intangible objects for thousands of years - we just need to make sure AI knows which ones are real.