Bossware at Work: Psychology, AI, and the Regulatory Gap in Workplace Surveillance

In Speaking of Psychology, host Kim Mills talks with Dr. Tara Behrend about the rising use of bossware and workplace surveillance technologies across industries. The discussion covers why companies monitor workers, how surveillance can alter behavior and safety, and the stark differences in regulatory frameworks between the US and regions like the EU, Canada, and Australia. The episode also considers the evolving role of AI in monitoring and the steps workers can take to protect privacy while seeking stronger protections.

• Surveillance is broad and often data driven, aimed at efficiency and automation, sometimes without clear questions guiding data use.
• Being watched can distract workers, especially in high vigilance jobs, and can lead to micromanagement for employees with less power.
• US regulation lags behind Europe and other regions that require disclosure and restrict monitoring to work-related behaviors.
• AI in surveillance raises concerns about privacy and whether new data signals actually reflect meaningful job performance.

Overview

In this episode of Speaking of Psychology, host Kim Mills speaks with Dr. Tara Behrend, an industrial organizational psychologist at Michigan State University, about the rapid expansion of electronic surveillance in the workplace. They discuss the range of technologies—from keystroke trackers and webcams to fatigue-detection analytics and employee location tracking—as well as the claims employers make about productivity and safety. Behrend notes that the push toward automation reinforces the incentive to collect large amounts of data, often without a clear research question guiding its use. She contrasts the current US regulatory landscape, which offers limited federal guidance, with the EU, Canada, and Australia where disclosures are mandated and monitoring is restricted to work-related behaviors.

How Common and How It Is Used

The guest emphasizes that digital surveillance is increasingly common across occupations and is often intertwined with automation. Examples include monitoring software engineers at large tech firms and systems intended to optimize routes, warehouse movements, or airport security screening. The overarching idea is that more information about how work is performed enables better automation design. Yet Behrend cautions that organizations frequently collect data without a specific question, which can lead to misguided or unsafe applications as metrics take on outsized influence.

Behavioral Effects and Safety

Behrend describes surveillance as a source of distraction that can reallocate cognitive resources away from tasks requiring vigilance. For roles such as drivers or security screeners, even small attentional drains can elevate risk. The discussion includes ongoing studies of police officers with body cameras, highlighting how constant monitoring can impede decompression and sustain high adrenaline levels in non-call times, potentially impacting decision-making and safety.

Power Dynamics and Employee Sentiment

The analysis shows that surveillance power dynamics matter dramatically. Employees with the least power tend to experience more negative effects, including autonomy loss and punitive supervision. In contrast, in highly skilled roles like surgery, monitoring may be framed as safety feedback and is less likely to be used for punishment. The legal and ethical implications of data ownership and access remain unsettled in the United States, complicating workers' ability to understand or contest monitoring practices.

AI, Data, and the Future of Monitoring

AI tools increasingly extract incidental data from workers, such as facial expressions or movements, which can be used to infer illness or performance. Behrend argues that sophistication does not necessarily translate into better measures of job-relevant performance. She warns that more invisible surveillance can inadvertently shape behavior toward machine-like conformity, a trend that could be accelerated by automation but may not reflect actual productivity or safety gains.

Regulation and Policy Implications

The episode points to the Government Accountability Office (GAO) report on best practices for organizational monitoring and calls for integration of monitoring guidelines into broader worker-safety protocols by agencies like OSHA, NIOSH, and the CDC. Behrend advocates for federal protections to address power imbalances and for collective action to push for stronger privacy standards, given the current patchwork of transparency requirements across states and regions.

Advice for Workers

Behrend offers practical guidance for individuals and teams, including being aware of what data devices capture, maintaining boundaries, and using real-time feedback for improvement without reacting defensively to surveillance. She also encourages teams and organizations to engage in conversations about camera use and privacy protocols and to pursue policy changes that protect workers’ rights and wellbeing.

Closing Reflections

The podcast closes with reflections on the likely persistence of some level of monitoring as automation expands. Behrend remains skeptical about the assumption that more surveillance will reliably improve work outcomes and emphasizes the need for protections that balance productivity with workers’ autonomy and privacy.