AI & Technical question
How would you measure the accuracy of Harvey's legal research outputs?
- Harvey
- AI & Technical
- Hard
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What this question tests
Tests AI evaluation design specifically for legal research accuracy, where correctness has a precise, checkable standard.
How to approach it
- Define accuracy precisely for this domain: did the research correctly identify the controlling law, and does every citation actually support the stated proposition.
- Build a gold standard test set: real research questions with attorney verified correct answers and citations, ideally across multiple practice areas.
- Score on multiple dimensions: citation existence, citation relevance to the claim, and completeness, since research can be technically correct but miss a key case.
- Bring in domain experts for evaluation, since only practicing attorneys can reliably judge whether a legal proposition is actually correctly supported.
- Track accuracy over time and by practice area, since performance on tax law may differ meaningfully from performance on employment law.
- Confirm with the interviewer whether the evaluation is for internal quality tracking or for a claim made externally to law firms, since the rigor bar differs.
What a strong answer includes
- Separates citation existence from citation relevance, since a real citation attached to the wrong proposition is a distinct and dangerous failure mode from a fabricated one.
- Uses attorney graders rather than automated scoring alone, since legal correctness often requires domain judgment a generic evaluator cannot make.
- Segments accuracy by practice area, avoiding a single blended score that could hide weak performance in a specific domain.
- Proposes tracking completeness, not just precision, since missing a controlling case is as serious an error as citing a wrong one.
Common mistakes
- Using only citation existence as the accuracy measure, missing the more common and more dangerous failure of a real citation misapplied.
- Relying solely on automated scoring without domain expert review for a field where correctness is nuanced.
- Reporting one blended accuracy number across all practice areas, hiding weak spots.
Likely follow-up questions
- How would you build the gold standard test set without enormous attorney time cost?
- How often would you refresh the evaluation set as case law changes?
- What accuracy threshold would you require before trusting an answer in a client facing draft?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 1: Foundations: the model and the decisions it forces on you
- Chapter 8: Evals: define good and make the number defensible
- Chapter 6: Agents and agentic architecture