Auditing Algorithms: On Lessons Learned and the Risks of DataMinimization
(AIES) A practical audit for a well-being recommendation app developed by Telefónica (mostly on bias).
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Auditing: Active Learning with Outcome-Dependent Query Costs cs.bgu.ac.il
(NIPS) Learns from a binary classifier paying only for negative labels.
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Active Fairness Auditing proceedings.mlr.press
(ICML) Studies of query-based auditing algorithms that can estimate the demographic parity of ML models in a query-efficient manner.
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Auditing Black-Box Prediction Models for Data Minimization Compliance cs.bu.edu
(NeurIPS) Measures the level of data minimization satisfied by the prediction model using a limited number of queries.
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The Fair Game: Auditing & debiasing AI algorithms over time cambridge.org
Jouarnal of Cambridge Forum on AI: Law and Governance
Audit Algorithms › Papers > 2020: “(AIES) A practical audit for a well-being recommendation app developed by Telefónica (mostly on bias).”