Abstract and Keywords
This chapter argues that the proliferation of automated algorithms in the workplace raises questions as to how they might be used in service of the control of workers. In particular, scholars have noted machine learning algorithms as prompting a data-centric reorganization of the workplace and a quantification of the worker. The chapter then considers ethical issues implicated by three emergent algorithmic-driven work technologies: automated hiring platforms (AHPs), wearable workplace technologies, and customer relationship management (CRM). AHPs are “digital intermediaries that invite submission of data from one party through preset interfaces and structured protocols, process that data via proprietary algorithms, and deliver the sorted data to a second party.” The use of AHPs involves every stage of the hiring process, from the initial sourcing of candidates to the eventual selection of candidates from the applicant pool. Meanwhile, wearable workplace technologies exist in a variety of forms that vary in terms of design and use, from wristbands used to track employee location and productivity to exoskeletons used to assist employees performing strenuous labor. Finally, CRM is an approach to managing current and potential customer interaction and experience with a company using technology. CRM practices typically involve the use of customer data to develop customer insight to build customer relationships.
Keywords: automated algorithms, workplace, machine learning algorithms, algorithmic-driven work technologies, automated hiring platforms, wearable workplace technologies, customer relationship management, hiring process, customer data, customer relationships
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