Gendered language and employment Web sites: How search algorithms can cause allocative harm

Authors

  • Karin van Es Utrecht University
  • Daniel Everts Utrecht University
  • Iris Muis Utrecht Data School

DOI:

https://doi.org/10.5210/fm.v26i8.11717

Keywords:

employment websites, search algorithms, gendered language, allocative harm, bias and discrimination

Abstract

Research on algorithms and artificial intelligence in the hiring process tends to focus on applicant screening and is often centered on the employer perspective. The role played by intermediaries, such as employment Web sites in the distribution of information about employment opportunities, tends to be overlooked. This paper examines the role of search algorithms on employment Web sites and their retrieval of employment opportunities for job seekers based on gendered search terms. Through a basic algorithm audit of the search engines used by three major employment Web sites active in the Dutch job market, we explore whether their search algorithms neutralize or reinforce gendered language, in case of the latter thereby naturalizing stigmas and pre-existing bias. According to our findings, employment Web sites can cause allocative harm if they repeatedly fail to show all opportunities relevant to job seekers.

Author Biographies

Karin van Es, Utrecht University

Assistant professor of Media and Culture Studies at Utrecht University and lead researcher at Utrecht Data School.

Iris Muis, Utrecht Data School

Project manager at Utrecht Data School.

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Published

2021-07-16

How to Cite

van Es, K., Everts, D. ., & Muis, I. (2021). Gendered language and employment Web sites: How search algorithms can cause allocative harm. First Monday, 26(8). https://doi.org/10.5210/fm.v26i8.11717