License: Creative Commons Attribution 3.0 Unported license (CC-BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.ITCS.2019.33
URN: urn:nbn:de:0030-drops-101269
URL: https://drops.dagstuhl.de/opus/volltexte/2018/10126/
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Dwork, Cynthia ; Ilvento, Christina

Fairness Under Composition

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LIPIcs-ITCS-2019-33.pdf (0.6 MB)


Abstract

Algorithmic fairness, and in particular the fairness of scoring and classification algorithms, has become a topic of increasing social concern and has recently witnessed an explosion of research in theoretical computer science, machine learning, statistics, the social sciences, and law. Much of the literature considers the case of a single classifier (or scoring function) used once, in isolation. In this work, we initiate the study of the fairness properties of systems composed of algorithms that are fair in isolation; that is, we study fairness under composition. We identify pitfalls of naïve composition and give general constructions for fair composition, demonstrating both that classifiers that are fair in isolation do not necessarily compose into fair systems and also that seemingly unfair components may be carefully combined to construct fair systems. We focus primarily on the individual fairness setting proposed in [Dwork, Hardt, Pitassi, Reingold, Zemel, 2011], but also extend our results to a large class of group fairness definitions popular in the recent literature, exhibiting several cases in which group fairness definitions give misleading signals under composition.

BibTeX - Entry

@InProceedings{dwork_et_al:LIPIcs:2018:10126,
  author =	{Cynthia Dwork and Christina Ilvento},
  title =	{{Fairness Under Composition}},
  booktitle =	{10th Innovations in Theoretical Computer Science  Conference (ITCS 2019)},
  pages =	{33:1--33:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-095-8},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{124},
  editor =	{Avrim Blum},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2018/10126},
  URN =		{urn:nbn:de:0030-drops-101269},
  doi =		{10.4230/LIPIcs.ITCS.2019.33},
  annote =	{Keywords: algorithmic fairness, fairness, fairness under composition}
}

Keywords: algorithmic fairness, fairness, fairness under composition
Collection: 10th Innovations in Theoretical Computer Science Conference (ITCS 2019)
Issue Date: 2018
Date of publication: 08.01.2019


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