People Analytics and Individual Autonomy: Employing Predictive Algorithms as Omniscient Gatekeepers in the Digital Age Workplace

Main Article Content

Erica Pedersen

Abstract

People Analytics is a powerful tool with immense promise for enhancing organizational insights. However, this Note argues that employers’ unfettered use of opaque predictive algorithms, which are trained on behavioral data to profile workers and guide employment outcomes, represents a significant threat to individual autonomy. Part II explores the emergence of People Analytics as a continuation and merger of historical approaches to scientific management in the American workplace. Part III contrasts the organizational benefits of predictive analytics against the uniquely intrusive, non-transparent, and sometimes arbitrary manner in which they are currently deployed against workers. Part IV discusses how People Analytics may hasten the erosion of employees’ normative rights in the workplace. It then discusses the insufficiency of existing regulatory and common law mechanisms to protect workers from arbitrary or discriminatory decisionmaking based on algorithmic profiling. Finally, Part V reviews some proposed solutions, emphasizing the importance of employee voice and the need for proactive regulations to enforce algorithmic transparency and protect individuals’ rights to privacy and autonomy.

Article Details

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Notes
How to Cite
Pedersen, E. (2021). People Analytics and Individual Autonomy: Employing Predictive Algorithms as Omniscient Gatekeepers in the Digital Age Workplace . Columbia Business Law Review, 2020(3). Retrieved from https://journals.library.columbia.edu/index.php/CBLR/article/view/7814