Algorithmic workplace surveillance: How AI is being used to monitor workers

The rise of algorithmic workplace surveillance has intensified since the pandemic, with companies increasingly deploying software to monitor employee productivity and make automated decisions affecting workers’ livelihoods. This trend extends beyond remote work monitoring to include warehouse workers, gig economy participants, and potentially federal employees.

The evolving landscape of workplace surveillance: Algorithmic monitoring tools have expanded from simple keystroke tracking to comprehensive systems that can make autonomous decisions about worker performance and employment status.

• Companies are implementing opaque algorithms that analyze productivity metrics without providing transparency about their underlying data or decision-making processes
• Remote work skepticism has driven adoption, despite economic research not supporting claims of decreased productivity
• Major organizations like Elon Musk’s companies and the Office of Personnel Management are using productivity concerns to justify rolling back remote work policies

Impact on non-remote workers: While remote work monitoring garners significant attention, algorithmic control systems are increasingly affecting workers across various industries.

• Gig economy workers face potential platform removal by algorithms with limited appeal options
• Amazon’s warehouse productivity systems were implemented despite internal findings indicating increased injury risks
• Labor advocates argue that individual resistance to electronic monitoring is insufficient given the technology’s widespread adoption

Power dynamics and control: The implementation of algorithmic management tools fundamentally alters workplace relationships and authority structures.

• These systems are primarily serving as control mechanisms rather than genuine efficiency tools
• Current laws provide minimal requirements for companies to disclose how their productivity models operate
• Labor organizations are advocating for greater algorithmic transparency to protect worker rights

Public sector implications: The efficiency-driven transformation of private sector management practices is beginning to influence government operations.

• Federal workers are preparing for increased algorithmic oversight of their work
• The transition represents a significant shift in public sector management philosophy
• The expansion into government workplaces could affect millions of additional workers

Future considerations: The rapid proliferation of algorithmic management systems, combined with limited oversight and transparency requirements, raises important questions about worker autonomy and rights in an increasingly automated workplace. The expansion of these tools into the public sector could accelerate their adoption and normalize algorithmic decision-making across all employment sectors.