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Black-Box Access is Insufficient for Rigorous AI Audits:

, In: Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency,

Casper, Stephen ; Ezell, Carson ; Siegmann, Charlotte... - p. 2254-2272 , 2024

Link: https://dl.acm.org/doi/10.1145/3630106.3659037

RT 
T1 <cTitle>Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency</cTitle>: T1 <Title>Black-Box Access is Insufficient for Rigorous AI Audits</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3659037&Exemplar=1&LAN=DE
				
A1 Casper, Stephen
A1 Ezell, Carson
A1 Siegmann, Charlotte
A1 Kolt, Noam
A1 Curtis, Taylor Lynn
A1 Bucknall, Benjamin
A1 Haupt, Andreas
A1 Wei, Kevin
A1 Scheurer, Jérémy
A1 Hobbhahn, Marius
A1 Sharkey, Lee
A1 Krishna, Satyapriya
A1 Von Hagen, Marvin
A1 Alberti, Silas
A1 Chan, Alan
A1 Sun, Qinyi
A1 Gerovitch, Michael
A1 Bau, David
A1 Tegmark, Max
A1 Krueger, David
A1 Hadfield-Menell, Dylan
PB ACM
YR 2024
K1 Adversarial Attacks
K1 Auditing
K1 Black-Box Access
K1 Evaluation
K1 Explainability
K1 Fairness
K1 Fine-Tuning
K1 Governance
K1 Interpretability
K1 Policy
K1 Regulation
K1 Risk
K1 White-Box Access
K1 Social and professional topics
K1 Computing/technology policy
K1 Government technology policy
K1 Governmental regulations
K1 Security and privacy
K1 Human and societal aspects of security and privacy
K1 Social aspects of security and privacy
SP 2254
OP 2272
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3630106.3659037
DO https://dl.acm.org/doi/10.1145/3630106.3659037
SF ELIB - SuUB Bremen

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