Algorithmic Bias? An Empirical Study of Apparent Gender-Based Discrimination in the Display of STEM Career Ads

被引：377

作者：

Lambrecht, Anja ^{[1
]}

Tucker, Catherine ^{[2
]}

机构：

[1] London Business Sch, Mkt, London NW1 4SA, England

[2] MIT, Mkt, Cambridge, MA 02142 USA

来源：

MANAGEMENT SCIENCE | 2019年 / 65卷 / 07期

基金：

美国国家科学基金会;

关键词：

algorithmic bias; online advertising; algorithms; artificial intelligence; FEMALE; WOMEN; TECHNOLOGY; MODELS;

D O I：

10.1287/mnsc.2018.3093

中图分类号：

C93 [管理学];

学科分类号：

12 ; 1201 ; 1202 ; 120202 ;

摘要：

We explore data from a field test of how an algorithm delivered ads promoting job opportunities in the science, technology, engineering and math fields. This ad was explicitly intended to be gender neutral in its delivery. Empirically, however, fewer women saw the ad than men. This happened because younger women are a prized demographic and are more expensive to show ads to. An algorithm that simply optimizes cost-effectiveness in ad delivery will deliver ads that were intended to be gender neutral in an apparently discriminatory way, because of crowding out. We show that this empirical regularity extends to other major digital platforms.

引用

页码：2966 / 2981

页数：16

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