Numerous statutes and common law doctrines conceive of a dividing line between work time and nonwork time and delineate the activities that must be compensated as work. While technological innovations and increasing desires for workplace flexibility have begun to erode this divide, it persists, in part, because of the ways in which the division protects employers and employees alike. Nonetheless, the explosion of data analytics programs that allow employers to monitor and rely upon a worker's off‐duty conduct will soon weaken the dividing line between work and nonwork in dramatically greater and more troubling ways than ever before. The emergence of programs allowing employers to track, predict, rely upon, and possibly control nonwork activities, views, preferences, and emotions represents a major blurring of the line between work and nonwork. This article contends that these advances in data analytics suggest a need to reexamine the notion of work versus nonwork time and to question whether existing protections adequately consider a world in which these lines are so significantly muddled. As a society, we need to acknowledge the implications of the availability of massive quantities of employees’ off‐duty data and to decide whether and how to regulate its use by employers. Whether we, as a society, decide to allow market forces to dictate acceptable employer behavior, choose to regulate and restrict the use of off‐duty data for adverse employment decisions, or find some middle ground that requires disclosure and consent, we should choose our own course rather than allowing the technology to be the guide.

中文翻译：

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数据分析与工作/非工作鸿沟的侵蚀

许多法规和普通法学说都设想了工作时间与非工作时间之间的界限，并划定了必须作为工作补偿的活动。尽管技术创新和对工作场所灵活性的日益增长的期望已开始消除这种鸿沟，但这种鸿沟之所以持续，部分原因是该部门保护雇主和雇员的方式相同。尽管如此，数据分析程序的爆炸式发展使雇主能够监控和依靠工人的休假行为，将很快以比以往任何时候都更大，更麻烦的方式削弱工作与非工作之间的界限。允许雇主跟踪，预测，依赖并可能控制非工作活动，观点，喜好和情绪的程序的出现，代表了工作与非工作之间的界限的重大模糊。本文认为，数据分析的这些进步表明，有必要重新审视工作时间与非工作时间的概念，并质疑现有保护措施是否充分考虑了这些界限如此混乱的世界。作为一个社会，我们需要承认大量员工下班数据的可用性，并决定是否以及如何规范雇主对数据的使用。无论是作为一个社会，我们是决定允许市场力量来决定可接受的雇主行为，还是选择规范和限制将休班数据用于不利的就业决定，还是找到需要披露和同意的中间立场，我们都应该选择自己的路线，而不是让技术作为指导。