Abstract
The rise of biometric security changes how users make decisions about their privacy. As passwords give way to faces and fingerprints, the algorithmic nature of these processes creates new cognitive labor for users. When biometrics are used in spaces of algorithmic management, workers must negotiate tradeoffs between security, privacy, fairness, and their livelihood. A mixed-methods, human-centered research design paired with theory frameworks from algorithmic management, usable security, and algorithmic fairness illuminates how workers navigate facial recognition at the level of local practice. As AI/ML technologies for management and security become increasingly interwoven, the implications of this research are significant.
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CITATION STYLE
Watkins, E. A. (2020). Took a pic and got declined, vexed and perplexed: Facial recognition in algorithmic management. In Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW (pp. 177–182). Association for Computing Machinery. https://doi.org/10.1145/3406865.3418383
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