Bossware and the Workplace: How Digital Surveillance Shapes Behavior, Privacy, and Policy

Overview

The podcast explores how employers increasingly monitor employees through various digital tools, the purposes behind data collection, and the psychological and practical implications for workers across industries. Dr. Tara Behrend explains how surveillance can reshape attention, motivation, and safety, while highlighting power dynamics and the need for protections.

Key insights

• Surveillance ranges from keystroke tracking and webcams to location and fatigue-detection tools and is expanding across many jobs.
• Data is often collected with vague questions about purpose, driving efficiency and safety but potentially reducing autonomy and increasing unsafe behaviors.
• Legal protections in the US are limited and uneven, whereas the EU, Canada, and Australia require disclosure and job-related monitoring only.
• AI can make surveillance more sophisticated yet not necessarily more relevant to performance; awareness and boundaries remain essential for workers.

Introduction and Main Theme

The podcast examines contemporary bossware and workplace digital surveillance, linking psychological science to everyday work life. Kim Mills interviews Dr. Tara Behrend, an industrial organizational psychologist at Michigan State University, to understand how being watched influences worker behavior, how common monitoring devices are, how AI is reshaping surveillance, and what laws govern such practices.

Range and Rationale of Surveillance

Behrend notes that these technologies are becoming common across occupations. She cites examples such as tech firms using monitoring in software engineering roles, safety-critical positions like security screening and truck driving, and warehouse operations where movement and routes are tracked. The broader motivation is the perception that data enables automation and efficiency, yet many organizations collect data without a clear question or objective in mind. This data-centric mindset encourages collecting as much as possible so “we’ll figure out what it means later.”

Mechanisms and Potential Harms

The discussion emphasizes that surveillance shapes what is considered important within a role. If speed is measured but safety is not, employees may cut corners to optimize metrics. Behrend argues this can create unsafe conditions, internal competition via leaderboards, and misaligned incentives for productivity. The effect on performance depends on job type and cognitive demands; high vigilance roles (drivers, screeners, police in the field) require sustained attention, and monitoring can divert cognitive resources and raise risk. In contrast, for high-skill professionals like surgeons, monitoring may be framed as safety feedback rather than punitive micromanagement.

Power, Autonomy, and Employee Wellbeing

Power dynamics are central. People with less organizational power experience the surveillance as more controlling and punitive, eroding autonomy and professional judgment. Those with more authority may see surveillance as safety-oriented or feedback-driven. The host and guest discuss the stress of always being “on stage,” which contributes to distraction and burnout, particularly in roles requiring decompression between tasks. There is also concern about data ownership and privacy, especially in healthcare settings where instrument retention or medical errors introduce complex liability questions.

Legal Landscape and Policy Context

Behrend outlines the current U.S. landscape: minimal federal guidance on employee monitoring, with only a handful of states requiring transparency. By comparison, the EU, Canada, and Australia require disclosure of monitoring and limit it to work-related activities. The lack of federal protections creates a power imbalance and raises questions about data ownership, retention, and disclosure. The GAO has issued a report with best-practice recommendations that agencies like OSHA and CDC could adopt to enhance worker safety and rights.

AI and the Future of Workplace Monitoring

The interview addresses how AI technologies can intensify data collection, potentially capturing more incidental or invasive information (facial expressions, illness indicators) that do not necessarily translate to performance improvements. Behrend argues that the allure of more data should be tempered by careful consideration of what actually matters for job performance and safety. She warns that surveillance data can become invisible to workers, with tacit inferences about life outside work or health status that could be misused for termination or discriminatory practices.

Advice for Individuals and Policymakers

For workers, the podcast recommends maintaining boundaries, being mindful of what devices capture, and discussing team-level practices to protect privacy, such as turning off cameras in meetings or limiting personal use on company devices. Behrend also calls for stronger protections at the federal level and references the GAO report as a constructive benchmark for regulators. For organizations, the message is to align monitoring with meaningful job-related metrics, ensure safety benefits, and avoid incentivizing unsafe or unethical behaviors.

Conclusion and Takeaways

The podcast closes with reflections on a future in which workers may feel more replaceable as automation expands. Behrend remains skeptical that many tasks can be fully automated, stressing the need to balance automation with humane, predictable work conditions and robust protections against overreach. The episode emphasizes the importance of thoughtful boundaries, better data governance, and policy action to safeguard workers while embracing the benefits of monitoring when truly beneficial.