Daniel S. Schiff
| Daniel S. Schiff | |
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| 🌐 Website | danielschiff |
Daniel S. Schiff is an American technology policy scholar. He is an associate professor of technology policy at Purdue University, where he co-directs the Governance and Responsible AI Lab (GRAIL).[1][2] His research concerns how governments and firms regulate artificial intelligence: how AI reaches the policy agenda, how companies turn ethics principles into internal practice, and how the public responds to government use of automated systems.[2]
Schiff is known for work on the "liar's dividend", the finding that politicians can deflect genuine scandals by falsely attributing the evidence to AI.[3] Before returning to academia he was the founding Responsible AI Lead at JPMorgan Chase.[1]
Early life and education
Schiff read philosophy at Princeton University, where courses with Peter Singer and Victoria McGeer turned his interest toward ethics while he was separately reading about robotics.[4] He graduated in 2012 with a bachelor's degree and a certificate in Values and Public Life, having written a senior thesis on the ethics of artificial intelligence — a topic that was not then an established field.[4]
A master's degree in social policy from the University of Pennsylvania followed in 2013.[4] He did not begin doctoral work immediately; the PhD in public policy, from the Georgia Institute of Technology, came in 2022.[5]
Career
The decade between Schiff's master's degree and his doctorate was spent in Philadelphia's education nonprofit sector, working on college access, dropout prevention, teacher preparation and school funding.[4] He rose to director of research, evaluation and planning at the Philadelphia Education Fund before returning to graduate school.[4][5]
While a doctoral student he served as secretary of IEEE 7010-2020, one of the first international standards addressing the social and ethical impact of autonomous and intelligent systems.[6][4]
After completing the PhD in 2022 he spent a year at JPMorgan Chase as its first Responsible AI Lead, building the bank's internal ethics review and governance processes.[7] He joined Purdue's department of political science the same year as an assistant professor and, with the political scientist Kaylyn Jackson Schiff, founded GRAIL.[7][8] He was promoted to associate professor by 2026.[2]
Research
The liar's dividend
Schiff's most widely reported work, written with Kaylyn Jackson Schiff and Natália Bueno, concerns what the authors call the liar's dividend: the advantage politicians gain by dismissing authentic damaging material as AI-generated. Their experiments found that false claims of misinformation outperformed both apology and silence as a response to scandal, and could rally a politician's existing supporters.[3][9]
The paper was published in the American Political Science Review and drew attention from journalists and policy institutions during the 2024 United States election cycle, including an expert brief by the Brennan Center for Justice and coverage in Political Science Now.[9] Schiff also commented on political deepfakes in a PolitiFact retrospective on the election, which concluded that AI's practical effect had been smaller than anticipated.[10]
GRAIL maintains the Political Deepfakes Incidents Database, a catalogue of politically salient synthetic media, which received a best paper award at the 2024 AAAI Conference on Innovative Applications of Artificial Intelligence.[11]
AI policy and ethics in practice
A second strand examines how AI reaches the policy agenda and how competing actors frame it, drawing on the multiple streams and narrative policy frameworks.[12]
Schiff has also studied whether stated AI ethics principles translate into organisational behaviour. A 2021 survey of AI ethics documents from public, private and NGO sources found that public and NGO documents engaged more with law and regulation and were produced through more participatory processes than corporate ones.[13] A later interview study of 34 practitioners across seven countries found that AI ethics audits broadly follow the stages of financial auditing but tend to lack stakeholder involvement, success measurement and external reporting, and concentrate narrowly on bias, privacy and explainability.[14]
With Kaylyn Jackson Schiff and Patrick Pierson, he ran a survey experiment on 1,460 American adults testing public reaction to government use of automated decision systems in child welfare and criminal justice. Failures of fairness and transparency produced substantial negative effects on how respondents evaluated government.[15]
Selected publications
- Schiff, Kaylyn Jackson; Schiff, Daniel S.; Bueno, Natália S. (2025). "The Liar's Dividend: Can Politicians Claim Misinformation to Evade Accountability?". American Political Science Review. 119 (1): 71–90. doi:10.1017/S0003055423001454.
- Schiff, Daniel S. (2024). "Framing contestation and public influence on policymakers: Evidence from US artificial intelligence policy discourse". Policy & Society. 43 (3): 255–288. doi:10.1093/polsoc/puae007.
- Schiff, Daniel S.; Schiff, Kaylyn Jackson; Pierson, Patrick (2022). "Assessing public value failure in government adoption of artificial intelligence". Public Administration. 100 (3): 653–673. doi:10.1111/padm.12742.
- Schiff, Daniel (2022). "Education for AI, not AI for Education: AI, Education, and Ethics in National AI Policy Strategies". International Journal of Artificial Intelligence in Education. 32: 527–563. doi:10.1007/s40593-021-00270-2.
- Schiff, Daniel; Borenstein, Jason; Biddle, Justin; Laas, Kelly (2021). "AI Ethics in the Public, Private, and NGO Sectors: A Review of a Global Document Collection". IEEE Transactions on Technology and Society. 2 (1): 31–42. doi:10.1109/TTS.2021.3052127.
References
- ↑ 1.0 1.1 "Daniel Schiff". Purdue University College of Liberal Arts. Retrieved 16 August 2026.
- ↑ 2.0 2.1 2.2 "Does Responsible AI Pay? How Ethics Commitments Build Public Trust with Daniel Schiff, Purdue University". Quello Center, Michigan State University. Retrieved 16 August 2026.
- ↑ 3.0 3.1 Schiff, Kaylyn Jackson; Schiff, Daniel S.; Bueno, Natália S. (2025). "The Liar's Dividend: Can Politicians Claim Misinformation to Evade Accountability?". American Political Science Review. 119 (1): 71–90. doi:10.1017/S0003055423001454.
- ↑ 4.0 4.1 4.2 4.3 4.4 4.5 "Shaping the future of responsible AI: A Q&A with Daniel S. Schiff, MSSP'13". University of Pennsylvania School of Social Policy & Practice. 9 March 2026. Retrieved 16 August 2026.
- ↑ 5.0 5.1 "Curriculum Vitae". danielschiff.com. 13 July 2026. Retrieved 16 August 2026.
- ↑ "IEEE 7010-2020 — IEEE Recommended Practice for Assessing the Impact of Autonomous and Intelligent Systems on Human Well-Being". IEEE Standards Association. 2020.
- ↑ 7.0 7.1 "Daniel S. Schiff". Governance and Responsible AI Lab (GRAIL). Retrieved 16 August 2026.
- ↑ "People – GRAIL". Purdue University Department of Political Science. Retrieved 16 August 2026.
- ↑ 9.0 9.1 "Research on the "Liar's Dividend" Gains Attention". Purdue University College of Liberal Arts. Retrieved 16 August 2026.
- ↑ "U.S. election officials prepared for an artificial intelligence-influenced campaign season". PolitiFact. 19 December 2024. Retrieved 16 August 2026.
- ↑ Walker, Christina P.; Schiff, Daniel S.; Schiff, Kaylyn Jackson (2024). "Merging AI Incidents Research with Political Misinformation Research: Introducing the Political Deepfakes Incidents Database". Proceedings of the AAAI Conference on Artificial Intelligence. 38 (21). doi:10.1609/aaai.v38i21.30349.
- ↑ Schiff, Daniel S. (2023). "Looking through a policy window with tinted glasses: Setting the agenda for U.S. AI policy". Review of Policy Research. doi:10.1111/ropr.12535.
- ↑ Schiff, Daniel; Borenstein, Jason; Biddle, Justin; Laas, Kelly (2021). "AI Ethics in the Public, Private, and NGO Sectors: A Review of a Global Document Collection". IEEE Transactions on Technology and Society. 2 (1): 31–42. doi:10.1109/TTS.2021.3052127.
- ↑ Schiff, Daniel S.; Kelley, Stephanie; Camacho Ibáñez, Javier (2024). "The emergence of artificial intelligence ethics auditing". Big Data & Society. 11 (4). doi:10.1177/20539517241299732.
- ↑ Schiff, Daniel S.; Schiff, Kaylyn Jackson; Pierson, Patrick (2022). "Assessing public value failure in government adoption of artificial intelligence". Public Administration. 100 (3): 653–673. doi:10.1111/padm.12742.
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