Ho, Daniel E.

MatchIt : Nonparametric Preprocessing for Parametric Causal Inference

Ho, D. E., Imai, K., King, G., & Stuart, E. A. (2011) · Journal of Statistical Software

Advanced Causal Inference TechniquesData Analysis with R

Cited by 4,385

On the Opportunities and Risks of Foundation Models

Bommasani, R., Hudson, D. A., Adeli, E., Altman, R., Arora, S., von Arx, S., Bernstein, M. S., Bohg, J., Bosselut, A., Brunskill, E., et al. (2021) · arXiv

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 2,676

How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals

Wu, E., Wu, K., Daneshjou, R., Ouyang, D., Ho, D. E., & Zou, J. (2021) · Nature Medicine

Artificial Intelligence in Healthcare and EducationHealthcare Regulation

Cited by 494

Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies

Engstrom, D. F., Ho, D. E., Sharkey, C. M., & Cuéllar, M.-F. (2020) · SSRN Electronic Journal

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 262

Hallucination‐Free? Assessing the Reliability of Leading AI Legal Research Tools

Magesh, V., Surani, F., Dahl, M., Suzgun, M., Manning, C. D., & Ho, D. E. (2025) · Journal of Empirical Legal Studies

Artificial Intelligence in LawEthics and Social Impacts of AI

Cited by 182

Legalbench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models

Guha, N., Nyarko, J., Ho, D. E., Ré, C., Chilton, A., Narayana, A., Chohlas-Wood, A., Peters, A., Waldon, B., Rockmore, D., et al. (2023) · SSRN Electronic Journal

Artificial Intelligence in LawTopic Modeling

Cited by 154

Outsider Oversight: Designing a Third Party Audit Ecosystem for AI Governance

Raji, I. D., Xu, P., Honigsberg, C., & Ho, D. (2022) · Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 122

An automated framework for assessing how well LLMs cite relevant medical references

Wu, K., Wu, E., Wei, K., Zhang, A., Casasola, A., Nguyen, T., Riantawan, S., Shi, P., Ho, D., & Zou, J. (2025) · Nature Communications

Artificial Intelligence in Healthcare and EducationInformation Retrieval and Search Behavior

Cited by 72

Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset

Henderson, P., Krass, M., Zheng, L., Guha, N., Manning, C. D., Jurafsky, D., & Ho, D. (2022) · Advances in Neural Information Processing Systems 35

Artificial Intelligence in LawEthics and Social Impacts of AI

Cited by 62

Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset

Henderson, P., Krass, M. S., Zheng, L., Guha, N., Manning, C. D., Jurafsky, D., & Ho, D. E. (2022) · arXiv

Artificial Intelligence in LawEthics and Social Impacts of AI

Cited by 49

How well do LLMs cite relevant medical references? An evaluation framework and analyses

Wu, K., Wu, E., Cassasola, A., Zhang, A., Wei, K., Nguyen, T., Riantawan, S., Riantawan, P. S., Ho, D. E., & Zou, J. (2024) · arXiv

Artificial Intelligence in Healthcare and EducationTopic Modeling

Cited by 41

Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Magesh, V., Surani, F., Dahl, M., Suzgun, M., Manning, C. D., & Ho, D. E. (2024) · arXiv

Artificial Intelligence in LawTopic Modeling

Cited by 37

Considerations for governing open foundation models

Bommasani, R., Kapoor, S., Klyman, K., Longpre, S., Ramaswami, A., Zhang, D., Schaake, M., Ho, D. E., Narayanan, A., & Liang, P. (2024) · Science

Research, Science, and AcademiaLaw, AI, and Intellectual Property

Cited by 31

Implications of predicting race variables from medical images

Zou, J., Gichoya, J. W., Ho, D. E., & Obermeyer, Z. (2023) · Science

Race, Genetics, and SocietyArtificial Intelligence in Healthcare and Education

Cited by 30

LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models

Guha, N., Nyarko, J., Ho, D. E., Ré, C., Chilton, A., Narayana, A., Chohlas-Wood, A., Peters, A., Waldon, B., Rockmore, D. N., et al. (2023) · arXiv

Artificial Intelligence in LawTopic Modeling

Cited by 30

Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy

Coston, A., Guha, N., Ouyang, D., Lu, L., Chouldechova, A., & Ho, D. E. (2021) · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency

Human Mobility and Location-Based AnalysisEthics and Social Impacts of AI

Cited by 21

Belief in the Machine: Investigating Epistemological Blind Spots of Language Models

Suzgun, M., Gur, T., Bianchi, F., Ho, D. E., Icard, T., Jurafsky, D., & Zou, J. (2024) · arXiv

Logic, Reasoning, and KnowledgeTopic Modeling

Cited by 3