Published jointly for Work in Progress and Power at Work
Employers are increasingly using algorithms and digital devices to control workers. As a new Human Rights Watch report puts it, “Workers around the world are increasingly hired, compensated, disciplined, and fired by algorithms that can be opaque, error-prone, and discriminatory; their faces, office badge swipes, email exchanges, browsing histories, keystrokes, driving patterns, and rest times are scanned to monitor performance and productivity.”
My research shows how this “algorithmic management” does not only affect working conditions; it expands the capacity of employers to subvert the efforts of workers to organize for better treatment.
It details just how they can do so by studying an early battle in the current labor upsurge: the first large union election at an Amazon warehouse, which took place in Bessemer, Alabama in early 2021. Drawing on interviews with 42 Amazon workers and court records obtained through a FOIA request, my investigation reveals that Amazon weaponized aspects of algorithmic management against the union drive by: A) repurposing tracking devices, workstation displays and a mobile app to stoke fear and doubt; B) engaging in “algorithmic slack-cutting” to curry favor; and C) exploiting patterns of social media activity encouraged by algorithmic management.
These findings highlight a vital but underexplored consequence of algorithmic management. They also underline the value of exploring how control techniques can shape counter-organizing opportunities for employers, not just organizing opportunities for workers.
Five ways employers weaponize algorithmic management
1. Weaponizing tracking devices: Algorithmic management often involves the use of digital devices to monitor and discipline workers. For example, ride-hailing apps leverage mobile apps to direct drivers and automatically terminate them if their ratings fall below a certain level. In Amazon’s case, scanners, badges and computers play a similar role. Beyond tracking productivity and administering write-ups, these tracking tools also aid employers’ anti-union tactics. Amazon theatrically deployed tracking devices in mandatory anti-union meetings where supervisors and human resource officers scanned attendees and watched workers with open laptops as the meetings unfolded, according to my interviews and court testimony by workers. The same sources suggested that Amazon even publicly singled out employees whose questions or comments appeared to indicate support for the union by scanning their badges as other workers looked on.
2. Repurposing workstation displays: Employers have long polled workers during anti-union campaigns, but algorithmic management greatly expands the capacity of employers to identify union partisans and effectively campaign against them. Amazon used workstation displays to beam workers with anti-union messages, such as “vote ASAP and vote No,” and to ask questions to gauge their union sympathies. Several interviewees said they abstained from voting because they believed Amazon could find out if they voted for the union and then fire them.
3. Algorithmic slack-cutting: Employers habitually improve working conditions to peel off votes during anti-union campaigns. But thanks to the flexibility and dehumanizing effects of algorithmic management, employers can turbocharge this tactic through what I call “algorithmic slack-cutting.” To explain this technique further, I need to specify two components of Amazon’s algorithmic management system.
The first component is what Jamie McCallum calls the “electronic whip.” This is a drive system that uses algorithms and digital devices to intensify the pace, monitoring and discipline of work, often resulting in high stress and injury rates among workers. Amazon’s electronic whip tracks the minutes workers are not working, enforces algorithmically-generated quotas, and automatically fires workers if they deplete their allotted unpaid time off. The second component is automated HR management. This typically involves using a mobile app to handle HR-related issues and questions, resulting in the elimination of the “interpersonal and empathetic aspects of people management.”
Ironically, the degrading effects of these aspects of Amazon’s algorithmic management also gave it the capacity to engage in slack-cutting to quickly gain favor with some workers. Confronted with the union drive, Amazon softened the “electronic whip,” such that Time Off Task, quotas and automatic termination for unpaid time off depletion went largely unenforced during the campaign. Simultaneously, it temporarily reintroduced the human touch missing from its automated HR management. It did so by flooding the floor with human resource officers, out-of-town managers and consultants to solicit grievances, express empathy and offer to help solve problems.
4. Leveraging a mobile app: Employers often deliver anti-union messages through letters, phone calls and text messages, but mobile apps significantly expand the capacity of employers to reach into the private lives of workers. Amazon workers are all but captive to “A to Z.” Workers are supposed to use the app to correct punches, request time off and file HR reports. They also receive important notifications through A to Z that they can ill afford to ignore, including schedule-change alerts and offers of overtime or “voluntary time off.” During the campaign, Amazon leveraged workers’ dependency on the app to reinforce its warnings to workers through captive audience meetings and other communication channels.
5. Exploiting social media: Workers create and cluster in social media groups to decipher, gripe and learn tricks for coping with the opaque processes and dehumanizing effects of algorithmic management. In Amazon Facebook groups, members commonly complain and ask questions about issues like quotas, UPT and automated terminations, with discussion sometimes turning to unionization as a partial solution to their grievances.
To deter unionization, Amazon used three techniques to exploit workers’ social media activity. First, it infiltrated such groups to “capture” and categorize posts of interest for potential investigation. Second, it paid employees through an “ambassador program” to counter “all posts and comments” questioning the “FC [fulfillment center] associate experience” and leave “no lie unchallenged,” so the public can learn that Amazon workers “love their jobs,” according to a leaked internal document. Third, it used a high volume of social media ads and communications to campaign directly against the union. The incentive structure and fear these techniques generated appeared to bias the social media discussion in an anti-union direction and cause anti-union rumors to spread like wildfire.
Research frontiers for journalists and academics
These counter-organizing opportunities arising from algorithmic management are just the tip of the iceberg.
Among other tools that can be used to suppress worker organizing are automatic censorship of union-related terms on internal communication platforms; polling software and data analysis to generate real-time unionization scores to guide prevention efforts; role-playing AI bots to train supervisors how to question, persuade and surveil workers to great effect; and AI analysis of “feedback, Slack messages, and even subtle trends in workplace chatter to figure out what workers are feeling and what issues are about to pop off.
Another avenue through which counter-organizing efforts have been expanded is the weaponization of DEI management. This includes the rebranding of anti-union consultants as diversity experts, the use of employee resource groups and DEI officers to detect and campaign against organizing, and the manipulation of social justice and wellness tropes to counter unions. These efforts alert us to the tensions and synergies between identity politics and class politics. Indeed, concerns around diversity, inclusion and equity animate organizing campaigns, such as the Starbucks union drive, and anti-union consultants are defending DEI initiatives on the grounds that their potential removal could encourage unionization.
Seeing algorithmic management for what it is, means recognizing that nearly all employers are authoritarian governments or as Elizabeth Anderson puts it, most employers are “communist dictatorships.” Indeed, scholars should answer the long-neglected call of famed democratic theorist, Robert Dahl, and apply political science concepts to firms. This could involve subjecting employers to the conceptual framework that posits repression, co-optation, performance legitimation and ideological legitimation as the primary authoritarian control strategies. Consider how this framework may improve on the coercion-control analytical binary that sociologists normally use as a starting point for unpacking workplace authoritarianism. Likewise, developing a “political theory of the firm” could also involve applying the concept of “boundary control” to highlight how employers influence the external economic and political environment to fortify their capacity to control workers internally.
The synthesis of political science with the sociology of work promises to expand our understanding of not just the technical concerns of labor control mechanisms, but also their “political imperatives” – which Steve Vallas suggests deserves renewed attention. The statisticians among us might take inspiration from political science indices that measure authoritarian state regimes along the dimensions of repression (see Human Rights Protection Scores, The Political Terror Scale and Varieties of Democracy) co-optation, performance legitimation and ideological legitimation, and then do the same for authoritarian workplace regimes. We can then better gauge just how authoritarian (or in select cases, democratic) one workplace is compared to another – very practical information for workers.
Researchers should also make efforts to collaborate with the many “organic intellectuals” who are actively involved in trying to organize and strike the country’s pace-setting employers. Talk to them, and you will learn they may have research wish lists. In the case of Amazon, items on the list include: How much slack and flexibility are in Amazon’s delivery system? What is the degree to which Amazon can redirect orders and union-avoidance staff in response to labor actions? What are the tensions between roving union-avoidance specialists, HR professionals, facility managers and low-level supervisors (who are being deskilled and controlled by algorithmic management sometimes as intensely as production workers)? How could these tensions be exploited? Surely, the answers to such questions are rife with theoretical insight, as well as actionable data.
Read More
Wiggin, T. (2025). Weaponizing the Workplace: How Algorithmic Management Shaped Amazon’s Antiunion Campaign in Bessemer, Alabama. Socius, 11. https://doi.org/10.1177/23780231251318389
Image: Joe Piette via Wikimedia Commons (CC BY-SA-2.0)
Author
Teke Wiggin is a Ph.D. student in the Department of Sociology at Northwestern University, specializing in labor movements, economic inequality, economic sociology, neoliberalization, political sociology and financialization. His work has also appeared in The Nation and CNBC.