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Discrimination in Online Ad Delivery: Google ads, black names and white names, racial discrimination, and click advertising

Author:

Latanya SweeneyAuthors Info & Claims

Queue, Volume 11, Issue 3

Pages 10 - 29

https://doi.org/10.1145/2460276.2460278

Published: 01 March 2013 Publication History

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Abstract

Do online ads suggestive of arrest records appear more often with searches of black-sounding names than white-sounding names? What is a black-sounding name or white-sounding name, anyway? How many more times would an ad have to appear adversely affecting one racial group for it to be considered discrimination? Is online activity so ubiquitous that computer scientists have to think about societal consequences such as structural racism in technology design? If so, how is this technology to be built? Let’s take a scientific dive into online ad delivery to find answers.

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Digital Library

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Schneider, J. http://www.lehigh.edu/bio/jill.html (Archived at http://foreverdata.org/onlineads).

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Sweeney, L. 2013. Discrimination in online ad delivery. (For detailed results and analysis, see full technical report archived at http://ssrn.com/abstract=2208240. Data, including Web pages andads, archived at http://foreverdata.org/onlineads).

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Cited By

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https://doi.org/10.4018/979-8-3693-2695-4.ch008
Li SAprahamian HNouiehed MEl-Amine H(2024)An Optimization-Based Order-and-Cut Approach for Fair Clustering of Data SetsINFORMS Journal on Data Science10.1287/ijds.2022.00053:2(124-144)Online publication date: Oct-2024
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Index Terms

Discrimination in Online Ad Delivery: Google ads, black names and white names, racial discrimination, and click advertising
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
      1. Web-based interaction
2. Information systems
  1. Information retrieval
  2. Information storage systems

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cover image Queue

Queue Volume 11, Issue 3

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March 2013

38 pages

ISSN:1542-7730

EISSN:1542-7749

DOI:10.1145/2460276

Issue’s Table of Contents

Copyright © 2013 ACM.

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Publication History

Published: 01 March 2013

Published in QUEUE Volume 11, Issue 3

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Cited By

Kapoor SBommasani RKlyman KLongpre SRamaswami ACihon PHopkins ABankston KBiderman SBogen MChowdhury REngler AHenderson PJernite YLazar SMaffulli SNelson APineau JSkowron ASong DStorchan VZhang DHo DLiang PNarayanan ASalakhutdinov RKolter ZHeller KWeller AOliver NScarlett JBerkenkamp F(2024)PositionProceedings of the 41st International Conference on Machine Learning10.5555/3692070.3692998(23082-23104)Online publication date: 21-Jul-2024
https://dl.acm.org/doi/10.5555/3692070.3692998
(2024)Ethical Leadership in the Age of AIHolistic Approach to AI and Leadership10.4018/979-8-3693-2695-4.ch008(193-231)Online publication date: 28-Jun-2024
https://doi.org/10.4018/979-8-3693-2695-4.ch008
Li SAprahamian HNouiehed MEl-Amine H(2024)An Optimization-Based Order-and-Cut Approach for Fair Clustering of Data SetsINFORMS Journal on Data Science10.1287/ijds.2022.00053:2(124-144)Online publication date: Oct-2024
https://doi.org/10.1287/ijds.2022.0005
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Cheong MAbedin EFerreira MReimann RChalson SRobinson PByrne JRuppanner LAlfano MKlein C(2024)Investigating Gender and Racial Biases in DALL-E Mini ImagesACM Journal on Responsible Computing10.1145/36498831:2(1-20)Online publication date: 1-Mar-2024
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