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Thomas Krendl Gilbert
Thomas Krendl Gilbert
New York Academy of Sciences
Verified email at nyas.org - Homepage
Title
Cited by
Cited by
Year
Toward trustworthy AI development: mechanisms for supporting verifiable claims
M Brundage, S Avin, J Wang, H Belfield, G Krueger, G Hadfield, H Khlaaf, ...
arXiv preprint arXiv:2004.07213, 2020
3252020
Open problems and fundamental limitations of reinforcement learning from human feedback
S Casper, X Davies, C Shi, TK Gilbert, J Scheurer, J Rando, R Freedman, ...
arXiv preprint arXiv:2307.15217, 2023
1412023
To explain or not to explain?—Artificial intelligence explainability in clinical decision support systems
J Amann, D Vetter, SN Blomberg, HC Christensen, M Coffee, S Gerke, ...
PLOS Digital Health 1 (2), e0000016, 2022
652022
A broader view on bias in automated decision-making: Reflecting on epistemology and dynamics
R Dobbe, S Dean, T Gilbert, N Kohli
arXiv preprint arXiv:1807.00553, 2018
552018
Hard choices in artificial intelligence
R Dobbe, TK Gilbert, Y Mintz
Artificial Intelligence 300, 103555, 2021
542021
Co-design of a trustworthy AI system in healthcare: deep learning based skin lesion classifier
RV Zicari, S Ahmed, J Amann, SA Braun, J Brodersen, F Bruneault, ...
Frontiers in Human Dynamics 3, 688152, 2021
362021
Reward reports for reinforcement learning
TK Gilbert, N Lambert, S Dean, T Zick, A Snoswell, S Mehta
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 84-130, 2023
282023
On assessing trustworthy AI in healthcare. Machine learning as a supportive tool to recognize cardiac arrest in emergency calls
RV Zicari, J Brusseau, SN Blomberg, HC Christensen, M Coffee, ...
Frontiers in Human Dynamics 3, 673104, 2021
282021
Toward trustworthy AI development: mechanisms for supporting verifiable claims (2020)
M Brundage, S Avin, J Wang, H Belfield, G Krueger, G Hadfield, H Khlaaf, ...
arXiv preprint arXiv:2004.07213, 2020
162020
Hard choices in artificial intelligence: Addressing normative uncertainty through sociotechnical commitments
R Dobbe, TK Gilbert, Y Mintz
arXiv preprint arXiv:1911.09005, 2019
152019
Epistemic therapy for bias in automated decision-making
TK Gilbert, Y Mintz
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 61-67, 2019
142019
Axes for sociotechnical inquiry in AI research
S Dean, TK Gilbert, N Lambert, T Zick
IEEE Transactions on Technology and Society 2 (2), 62-70, 2021
122021
Toward trustworthy AI development: Mechanisms for supporting verifiable claims. arXiv 2020
M Brundage, S Avin, J Wang, H Belfield, G Krueger, G Hadfield, H Khlaaf, ...
arXiv preprint arXiv:2004.07213, 2004
112004
Choices, risks, and reward reports: Charting public policy for reinforcement learning systems
TK Gilbert, S Dean, T Zick, N Lambert
arXiv preprint arXiv:2202.05716, 2022
92022
Designing Technology and Policy Simultaneously: Towards A Research Agenda and New Practice
Q Yang, RY Wong, T Gilbert, MD Hagan, S Jackson, S Junginger, ...
Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing …, 2023
82023
Subjectifying objectivity: Delineating tastes in theoretical quantum gravity research
TK Gilbert, A Loveridge
Social Studies of Science 51 (1), 73-99, 2021
72021
AI development for the public interest: From abstraction traps to sociotechnical risks
MK Andrus, S Dean, TK Gilbert, N Lambert, T Zick
2020 IEEE International Symposium on Technology and Society (ISTAS), 72-79, 2020
72020
How to assess trustworthy AI in practice
RV Zicari, J Amann, F Bruneault, M Coffee, B Düdder, E Hickman, ...
arXiv preprint arXiv:2206.09887, 2022
62022
Sociotechnical Specification for the Broader Impacts of Autonomous Vehicles
TK Gilbert, AJ Snoswell, M Dennis, R Mcallister, C Wu
arXiv preprint arXiv:2205.07395, 2022
62022
Mapping the Political Economy of Reinforcement Learning Systems: The Case of Autonomous Vehicles
TK Gilbert
Simons Institute Newsletter, 2021
52021
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