Latanya Sweeney
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.
- Barker R. 2003. The Social Work Dictionary (5th ed.). Washington, DC: NASW Press.Google Scholar
- Bertrand, M., Mullainathan, S. 2003. Are Emily and Greg more employable than Lakisha andJamal? A field experiment on labor market discrimination. NBER Working Paper No. 9873;.Google Scholar
- Central Hudson Gas & Electric Corp. v. Public Service Commission of New York. 1980. Supreme Courtof the United States, 447 U.S. 557.Google Scholar
- Dwork, C., Hardt, M., Pitassi, T., Reingold, O., Zemel, R. 2011. Fairness through awareness.arXiv:1104.3913 {cs.CC}; http://arxiv.org/abs/1104.3913.Google Scholar
- Equal Employment Opportunity Commission. 2012. Consideration of arrest and convictionrecords in employment decisions under Title VII of the Civil Rights Act of 1964. Washington,DC. 915.002; http://www.eeoc.gov/laws/guidance/arrest_conviction.cfm.Google Scholar
- Equal Employment Opportunity Commission. 1978. Uniform guidelines on employee selectionprocedures. Washington, DC.Google Scholar
- Fryer, R., Levitt, S. 2004. The causes and consequences of distinctively black names. The Quarterly Journal of Economics 59(3); http://pricetheory.uchicago.edu/levitt/Papers/FryerLevitt2004.pdf.Google Scholar
- Glover, E; http://www.physiology.emory.edu/FIRST/ebony2.htm (archived at http://foreverdata.org/onlineads).Google Scholar
- Google AdSense; http://google.com/adsense.Google Scholar
- Google. Google announces first quarter 2011 financial results; http://investor.google.com/earnings/2011/Q1_google_earnings.html.Google Scholar
- Harris, P., Keller, K. 2005. Ex-offenders need not apply: the criminal background check in hiringdecisions. Journal of Contemporary Criminal Justice 21(1): 6-30.Google ScholarCross Ref
- Panel on Methods for Assessing Discrimination, National Research Council. 2004. Measuringracial discrimination. Washington, DC: National Academy Press.Google Scholar
- Pang, B., Lee, L. 2004. A sentimental education: sentiment analysis using subjectivitysummarization based on minimum cuts. Proceedings of the 42nd Annual Meeting on Association forComputational Linguistics. Google ScholarDigital Library
- Schneider, J. http://www.lehigh.edu/bio/jill.html (Archived at http://foreverdata.org/onlineads).Google Scholar
- 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).Google Scholar
- U.S. Commission on Civil Rights. 1970. Racism in America and how to combat it. Washington,DC.Google Scholar
- WebShot Command Line Server Edition. Version 1.9.1.1; http://www.websitescreenshots.com/.Google Scholar
Index Terms
- Discrimination in Online Ad Delivery: Google ads, black names and white names, racial discrimination, and click advertising
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Discrimination in online ad delivery
Google ads, black names and white names, racial discrimination, and click advertising.
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