Daniel E. Ho
William Benjamin Scott & Luna M. Scott Professor of Law, Professor of Political Science, Senior Fellow at the Stanford Institute for Economic Policy Research, at the Stanford Institute for HAI
Studies AI for law and government through the RegLab, including LLM-based analysis of statutes and evaluation of legal AI tools.
Daniel E. Ho's lab at Stanford works on large language models and interpretability, evaluation & safety of LMs. 56 papers since 2023, 11 at top venues, mostly FAccT and Nature Machine Intelligence. Applications close .
At a glance
- papers, 2023–2026
- 15/ year
- at T1 venues
- 20%
- PhD students
- 0
- MS students
- 0
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 19 papers2026 · T1 2 · collecting
- 13 papers2025 · T1 4
- 12 papers2024 · T1 4
- 12 papers2023 · T1 1
T1 venuesOtherVenues: FAccT, Nature Machine Intelligence, ACL, Nature Communications, AAAI/ACM AIES
Research focuspaper titles that use each topic's words
- Large language models10 papers
- legal8 papers
- law5 papers
- Interpretability, evaluation & safety of LMs2 papers
- llm-based0 papers
Paper list
From the lab homepage.
202619 papers
- Journal of Legal AnalysisAI for Scaling Legal Reform: Mapping and Redacting Racial Covenants in Santa Clara County (opens in a new tab)
- Law, Behavior and DecisionAI in the Judiciary: Practice and Policy (opens in a new tab)
- EpidemiologyAssociation Between Proximity to Animal Agriculture During Pregnancy and Spontaneous Preterm Birth Among Nulliparous Women in a California Cohort (opens in a new tab)
- CSLAW '26: Proceedings of the Symposium on Computer Science and LawBenchmarking Legal RAG: The Promise and Limits of AI Statutory Surveys (opens in a new tab)
- Environmental ChallengesBlind Spots in Environmental Permitting: An AI-Assisted Assessment of Coverage Gaps and Environmental Risk amoung Large Dairy Farms in Wisconsin (opens in a new tab)
- AxivEstimating Near-Verbatim Extraction Risk in Language Models with Decoding-Constrained Beam Search (opens in a new tab)
- CSLAW '26: Proceedings of the Symposium on Computer Science and LawEvaluating Generative AI in Benefits Administration: A Demonstration Project (opens in a new tab)
- PLOS Digital HealthEvaluating the impact of discordant and missing demographic information on population health assessments using linked electronic health records and Census Bureau microdata (opens in a new tab)
- Harvard Data Science ReviewExplainability in the Wild, or Wild Explanations? Evidence From Predicting Tax Evasion (opens in a new tab)
- ICAILHidden in Plain Text: LLM-Assisted Detection of Discriminatory Municipal Laws (opens in a new tab)
- Nature Communications (T1)How Defining ‘Disadvantaged’ Shaped Bipartisan Infrastructure Law Drinking Water Funding (opens in a new tab)
- Political AnalysisMonotone Ecological Inference (opens in a new tab)
202513 papers
- ICAILAI for Statutory Simplification: A Comprehensive State Legal Corpus and Labor Benchmark (opens in a new tab)
- Nature Communications (T1)An automated framework for assessing how well LLMs cite relevant medical references (opens in a new tab)
- HAI White PaperAssessing the Implementation of Federal AI Leadership and Compliance Mandates (opens in a new tab)
- FAccTBias Delayed is Bias Denied? Assessing the Effect of Reporting Delays on Disparity Assessments (opens in a new tab)
- The Oxford Handbook of the Foundations and Regulation of Generative AIBuilding GenAI Benchmarks: A Case Study in Legal Applications (opens in a new tab)
- PLOS WaterDo mandatory minimum penalties and penalty relief work? Evidence from California’s clean water program (opens in a new tab)
- Nature Scientific DataEnabling disaggregation of Asian American subgroups: a dataset of Wikidata names for disparity estimation (opens in a new tab)
- Administrative Law ReviewEvaluation as Due Process: Civil Service in an Automated Age (opens in a new tab)
- Nature Machine Intelligence (T1)Language models cannot reliably distinguish belief from knowledge and fact (opens in a new tab)
- Journal of the Royal Statistical SocietyModeling Spatial Heterogeneity in Exposure Buffers and Risk: A Hierarchical Bayesian Approach (opens in a new tab)
- NeurIPS (T1)Near-Exponential Savings for Mean Estimation with Active Learning (opens in a new tab)
- ACL (T1)Not Your Typical Government Tipline: LLM-Assisted Routing of Environmental Protection Agency Citizen Tips (opens in a new tab)
202412 papers
- Science (T1)Considerations for governing open foundation models (opens in a new tab)
- Minnesota Journal of Law, Science & TechnologyCorpus Enigmas and Contradictory Linguistics: Tensions Between Empirical Semantic Meaning and Judicial Interpretation (opens in a new tab)
- Journal of the Association of Environmental and Resource EconomistsDrop a Line, Submit on Time? Randomized Tailored Reminders Improve Pollution Reporting Timeliness (opens in a new tab)
- Penn Law ReviewGoverning by Assignment (opens in a new tab)
- Journal of Environmental ManagementIntegrating Water Quality Data with a Bayesian Network Model to Improve Spatial and Temporal Phosphorus Attribution: Application to the Maumee River Basin (opens in a new tab)
- Journal of Legal AnalysisLarge Legal Fictions: Profiling Legal Hallucinations in Large Language Models (opens in a new tab)
- Environmental Health PerspectivesLimitations of Reporting Requirements under California’s Livestock Antimicrobial Restriction Law (opens in a new tab)
- Nature Machine Intelligence (T1)Mitigating allocative tradeoffs and harms in an environmental justice data tool (opens in a new tab)
- ACL (T1)MultiLegalPile: A 689GB Multilingual Legal Corpus (opens in a new tab)
- Journal of the American Planning AssociationNot (Officially) in My Backyard: Characterizing Informal Accessory Dwelling Units and Informing Housing Policy With Remote Sensing (opens in a new tab)
- Science AdvancesRemote sensing and computer vision for marine aquaculture (opens in a new tab)
- EMNLP (T1)Statistical Uncertainty in Word Embeddings: GloVe-V (opens in a new tab)
202312 papers
- Lancet: eClinicalMedicineAutomated vs. manual case investigation and contact tracing for pandemic surveillance: Evidence from a stepped wedge cluster randomized trial (opens in a new tab)
- Conference on Secure and Trustworthy Machine LearningEstimating and Implementing Conventional Fairness Metrics With Probabilistic Protected Features (opens in a new tab)
- Working PaperEstimating Racial Disparities When Race is Not Observed (opens in a new tab)
- FAccTHow Redundant are Redundant Encodings? Blindness in the Wild and Racial Disparity when Race is Unobserved (opens in a new tab)
- PLOS ONEIntegrating social services with disease investigation: A randomized trial of COVID-19 high-touch contact tracing (opens in a new tab)
- NeurIPS D&BLegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models (opens in a new tab)
- iScienceLeveraging genomic sequencing data to evaluate disease surveillance strategies (opens in a new tab)
- Working PaperMeasuring and Mitigating Racial Disparities in Tax Audits (opens in a new tab)
- Nature Machine Intelligence (T1)Potential for allocative harm in an environmental justice data tool (opens in a new tab)
- AAAI/ACM AIESThe Bureaucratic Challenge to AI Governance: An Empirical Assessment of Implementation at U.S. Federal Agencies (opens in a new tab)
- FAccTThe Privacy-Bias Tradeoff: Data Minimization and Racial Disparity Assessments in U.S. Government (opens in a new tab)
- ACM Conference on Equity and Access in Algorithms, Mechanisms, and OptimizationToward Operationalizing a Pipeline-aware Approach to ML Fairness: A Research Agenda for Developing Practical Guidelines and Tools (opens in a new tab)
Where alumni went
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Apply to StanfordFall 2027
Stanford Computer Science PhD
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