Elliott Ash is an economist at ETH Zurich, adjunct professor at NYU Law, visiting professor at Columbia Law, and scientific lead at the Swiss AI Institute. He holds a PhD in economics and a JD from Columbia, a BA from UT Austin, and an LLM in international criminal law from the University of Amsterdam. His work sits at the intersection of economics, law, and machine learning, with a focus on judicial behavior and AI in the courts.

• Inside the Manne Program (c. 1976–1998): how training federal judges in economics shifted their reasoning and language in judicial opinions.

• Discussion of changes in the field of law and economics since its early beginnings as a field of study.

• Early insight into a nationwide AI rollout to nearly half of Pakistan’s judges: faster opinions, better writing, smaller backlogs — and the risks of bias, hallucination, and mismatched values.

• trace.law: using AI to verify filings rather than generate them, and why almost every case contains at least a minor error.

• Why “the AI is not the judge” — keeping human judgment, agency, and accountability at the center.

Elliott built a court-filing verifier that scans filings and opinions for verifiable errors - from typos and mismatched section numbers to swapped party names and, most seriously, citations to the wrong statute, a case that doesn’t say what’s claimed, or a case that doesn’t exist at all. With hallucinated-citation sanctions hitting even large firms, the pitch is simple: verifying with AI is a different, safer use than generating with it. The tool is available to lawyers at trace.law, with more detail in his Law360 article.

• Trace Law — AI court-filing & citation verifier: trace.law

• Article: Ideas Have Consequences: The Impact of Law and Economics on American Justice — Elliott Ash, Daniel Chen & Suresh Naidu

• Elliott Ash’s Law360 article on AI-assisted filing verification

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