“I Don't Want Someone to Watch Me While I'm Working”: Gendered Views of Facial Recognition Technology in Workplace Surveillance
Luke Stark,
Amanda Stanhaus and
Denise L. Anthony
Journal of the Association for Information Science & Technology, 2020, vol. 71, issue 9, 1074-1088
Abstract:
Employers are increasingly using information and communication technologies to monitor employees. Such workplace surveillance is extensive in the United States, but its experience and potential consequences differ across groups based on gender. We thus sought to identify whether self‐reported male and female employees differ in the extent to which they find the use of workplace cameras equipped with facial recognition technology (FRT) acceptable, and examine the role of privacy attitudes more generally in mediating views on workplace surveillance. Using data from a nationally representative survey conducted by the Pew Research Center, we find that women are much less likely than men to approve of the use of cameras using FRT in the workplace. We then further explore whether men and women think differently about privacy, and if perceptions of privacy moderate the relationship between gender and approval of workplace surveillance. Finally, we consider the implications of these findings for privacy and surveillance via embedded technologies, and how the consequences of surveillance and technologies like FRT may be gendered. Note: We recognize evaluations based on a binary definition of gender are invariably partial and exclusionary. As we note in our discussion of the study's limitations, we were constrained by the survey categories provided by Pew.
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
https://doi.org/10.1002/asi.24342
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bla:jinfst:v:71:y:2020:i:9:p:1074-1088
Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=2330-1635
Access Statistics for this article
More articles in Journal of the Association for Information Science & Technology from Association for Information Science & Technology
Bibliographic data for series maintained by Wiley Content Delivery ().