STEM and Teens: An Algorithmic Bias on a Social Media

35 Pages Posted: 23 May 2018 Last revised: 30 May 2019

See all articles by Grazia Cecere

Grazia Cecere

Institut Mines Telecom, Business School, LITEM

Clara Jean

Université Paris XI Sud

Fabrice Le Guel

Université Paris-Sud

Matthieu Manant

Université Paris XI Sud

Date Written: May 28, 2019

Abstract

Evidence of algorithmic bias has recently raised questions about their fairness. In a field experiment, we evaluate the algorithm of a social media platform by prompting it to reduce its advertising distribution bias against women. We ran advertising campaigns targeting high schools in France on behalf of an engineering school. One ad was gender-neutral (control) and the other ad had women-specific content (treatment). Women-specific content reduced the advertising distribution gap between women and men. However, the treatment also had a crowding-out effect, such that the ad with women-specific content was displayed fewer times to users overall. The treatment reduced the number of impressions of ad for high schools with more women in science track. The treatment also reduced the advertising distribution gap between low-income and high-income high schools.

Keywords: Advertising, Algorithm, Machine Learning, Field experiment

JEL Classification: J16, I24

Suggested Citation

Cecere, Grazia and Jean, Clara and Le Guel, Fabrice and Manant, Matthieu, STEM and Teens: An Algorithmic Bias on a Social Media (May 28, 2019). Available at SSRN: https://ssrn.com/abstract=3176168 or http://dx.doi.org/10.2139/ssrn.3176168

Grazia Cecere (Contact Author)

Institut Mines Telecom, Business School, LITEM ( email )

9, rue Charles Fourier
Évry, Ile de France 91011
France

Clara Jean

Université Paris XI Sud ( email )

15, rue Georges Clemenceau
Orsay cedex, 91405
France

Fabrice Le Guel

Université Paris-Sud ( email )

Faculté Jean-Monnet, 54, bd Desgranges
Sceaux, 92331
France

Matthieu Manant

Université Paris XI Sud ( email )

15, rue Georges Clemenceau
Orsay cedex, 91405
France

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