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Downstream Effects of Affirmative Action

Kannan, Sampath and Roth, Aaron and Ziani, Juba (2019) Downstream Effects of Affirmative Action. In: Proceedings of the Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery (ACM) , New York, NY, pp. 240-248. ISBN 978-1-4503-6125-5. http://resolver.caltech.edu/CaltechAUTHORS:20190111-074555981

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Abstract

We study a two-stage model, in which students are 1) admitted to college on the basis of an entrance exam which is a noisy signal about their qualifications (type), and then 2) those students who were admitted to college can be hired by an employer as a function of their college grades, which are an independently drawn noisy signal of their type. Students are drawn from one of two populations, which might have different type distributions. We assume that the employer at the end of the pipeline is rational, in the sense that it computes a posterior distribution on student type conditional on all information that it has available (college admissions, grades, and group membership), and makes a decision based on posterior expectation. We then study what kinds of fairness goals can be achieved by the college by setting its admissions rule and grading policy. For example, the college might have the goal of guaranteeing equal opportunity across populations: that the probability of passing through the pipeline and being hired by the employer should be independent of group membership, conditioned on type. Alternately, the college might have the goal of incentivizing the employer to have a group blind hiring rule. We show that both goals can be achieved when the college does not report grades. On the other hand, we show that under reasonable conditions, these goals are impossible to achieve even in isolation when the college uses an (even minimally) informative grading policy.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1145/3287560.3287578DOIArticle
Additional Information:© 2019 ACM. Kannan’s research was supported in part by NSF grant AF-1763307 and a grant from the Quattrone Center for the Fair Administration of Justice. Roth’s research was supported in part by NSF grants CNS-1253345, AF-1763307, and a grant from the Quattrone Center for the Fair Administration of Justice. Ziani’s research was supported in part by NSF grants CNS-1331343 and CNS-1518941, and the Linde Graduate Fellowship at Caltech. We thank Mallesh Pai and Jonathan Ullman for helpful discussions at an early stage of this work.We thank Jonathan Roth for pointing out an economic interpretation of our sIGM condition.
Funders:
Funding AgencyGrant Number
NSFAF-1763307
Quattrone Center for the Fair Administration of JusticeUNSPECIFIED
NSFCNS-1253345
NSFCNS-1331343
NSFCNS-1518941
Ronald And Maxine Linde Institute for Economic and Management Sciences, CaltechUNSPECIFIED
Subject Keywords:Long-term fairness; affirmative action; college admissions; job market
Record Number:CaltechAUTHORS:20190111-074555981
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20190111-074555981
Official Citation:Sampath Kannan, Aaron Roth, and Juba Ziani. 2019. Downstream Effects of Affirmative Action. In FAT* ’19: Conference on Fairness, Accountability, and Transparency, January 29–31, 2019, Atlanta, GA, USA. ACM, New York, NY, USA, 9 pages. https://doi.org/10.1145/3287560.3287578
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:92208
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:11 Jan 2019 17:41
Last Modified:29 Jan 2019 23:48

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