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Balanced Filtering via Disclosure-Controlled Proxies

Authors Siqi Deng, Emily Diana, Michael Kearns, Aaron Roth

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Siqi Deng
  • Amazon AWS AI, Palo Alto, CA, USA
Emily Diana
  • Toyota Technological Institute at Chicago, IL, USA
Michael Kearns
  • University of Pennsylvania, Philadelphia, PA, USA
  • Amazon AWS AI, Palo Alto, CA, USA
Aaron Roth
  • University of Pennsylvania, Philadelphia, PA, USA
  • Amazon AWS AI, Palo Alto, CA, USA

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Siqi Deng, Emily Diana, Michael Kearns, and Aaron Roth. Balanced Filtering via Disclosure-Controlled Proxies. In 5th Symposium on Foundations of Responsible Computing (FORC 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 295, pp. 4:1-4:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/LIPIcs.FORC.2024.4

Abstract

We study the problem of collecting a cohort or set that is balanced with respect to sensitive groups when group membership is unavailable or prohibited from use at deployment time. Specifically, our deployment-time collection mechanism does not reveal significantly more about the group membership of any individual sample than can be ascertained from base rates alone. To do this, we study a learner that can use a small set of labeled data to train a proxy function that can later be used for this filtering or selection task. We then associate the range of the proxy function with sampling probabilities; given a new example, we classify it using our proxy function and then select it with probability corresponding to its proxy classification. Importantly, we require that the proxy classification does not reveal significantly more information about the sensitive group membership of any individual example compared to population base rates alone (i.e., the level of disclosure should be controlled) and show that we can find such a proxy in a sample- and oracle-efficient manner. Finally, we experimentally evaluate our algorithm and analyze its generalization properties.

Subject Classification

ACM Subject Classification
  • Theory of computation → Design and analysis of algorithms
  • Security and privacy → Human and societal aspects of security and privacy
Keywords
  • Algorithms
  • Sampling
  • Ethical/Societal Implications

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