Algorithmic Control and the Human Cost: The Impact of Technology on Low-Wage Workers

-- By AndreaRuedas - 22 Jan 2025

The Philadelphia Inquirer article, “Hotel housekeeping on demand: Marriott cleaners say this app makes their job harder,” tells the story of hotel housekeepers who are struggling with the introduction of an algorithmic management system. The app, called Rex, forces workers to follow rigid, predetermined routes that leave them with little control over their day. This loss of autonomy not only impacts their physical workload but also threatens their economic stability and self-bargaining power in a fast moving industry. In this essay, I will analyze how algorithmic management erodes workers' autonomy, contributes to economic instability, and increases their physical burden, while considering the larger implications for labor protections in the workplace

Erosion of Autonomy and Economic Instability

Hotel management systems like Rex act as tools of surveillance and control, reducing housekeepers' autonomy and compromising their financial stability. Before the app's implementation, workers could set their own schedules and prioritize tasks based on their knowledge of guests' needs. However, Rex enforces fixed routes, leaving housekeepers with less flexibility to meet guests’ expectations. This rigid scheduling often leads to poor reviews, dissatisfied guests, and the possibility of job loss or lower tips.

This situation aligns with Levy and Barocas’ (2018) theory of refractive surveillance, in which customer data is used to control and evaluate workers. Housekeepers, already in low-wage positions, now find their finances further compromised by the app’s surveillance of their performance. As the data from customer reviews is fed back into the system, it creates a cycle of increasing scrutiny, where workers’ performance is continuously measured against customer satisfaction metrics and relayed to hotel management. In the best scenario, negative reviews or complaints result in lower tips, which affects workers' expected income in an industry whose appeal is the potential for additional cash, but at worst, these reviews and evaluations result in the loss of their jobs.

The app also illustrates another key issue discussed by Levy and Barocas, schedule optimization, which attempts to improve worker efficiency but ultimately reduces autonomy. For housekeepers, this means losing control over how and when they perform their tasks. The app’s algorithm forces workers to follow a fixed schedule designed to increase efficiency, even when this leads to customer dissatisfaction. The inability to personalize service to meet guests' individual needs, such as cleaning rooms when the housekeeper knows guests will be absent, results in standardized service but also makes workers more vulnerable to criticism. This decreases the value of housekeepers, as their once-unique knowledge about guest preferences, scheduling, and the hotel itself becomes irrelevant in the face of data-driven optimization. The outcome is a work environment where “workers [are] more readily substitutable for each other,” since the app’s standardization reduces the need for individual skill or insider knowledge which leads to weaker job security.

In addition to eroding autonomy and economic stability, the app also increases the physical demands of the work. According to the housekeepers interviewed in the article, the app forces them to travel long distances across the hotel, following inefficient and unorganized routes. One worker notes that the app’s scheduling results in housekeepers zigzagging across the building, leading to more time spent hauling carts full of supplies and increasing the physical strain of a job that already demands long hours of physically demanding labor. This makes the job more exhausting without any corresponding increase in compensation.

Power Imbalance and Worker Insecurity

Rex, like other algorithmic management tools, creates a power imbalance between workers and management. Rosenblat and Stark’s (2016) study on Uber illustrates how platforms impose “soft control,” offering workers the illusion of autonomy while controlling critical aspects of their work. Uber drivers, for example, are given the freedom to accept or reject rides, but the app’s design constraints this decision-making process. Similarly, housekeepers may seem to have control over their schedules, but in reality, their routines are tightly regulated by the app's parameters. Hotel managers can adjust settings, but they are more likely to prioritize efficiency and profit over worker needs, leaving housekeepers with little power to influence the app’s operation.

This power imbalance erodes workers’ bargaining power. Traditionally, housekeepers could negotiate better working conditions based on their specialized knowledge of guest needs. The app’s standardization, however, minimizes their individual contributions, making it harder for them to demand better pay or improved conditions. Without flexibility in their work routines, housekeepers lose leverage in negotiations with management, making them more vulnerable to job loss or reduced hours.

A Broader Discussion: Legislative Action and Unionization

While unionization is a vital response to the adverse effects of algorithmic management, it’s crucial to consider broader strategies to protect non-unionized workers. With only a small fraction of private employees currently in unions, much of the workforce remains unprotected. To address this, state or federal legislation could be introduced to safeguard workers from the destabilizing effects of workplace surveillance and algorithmic control. Legislation could limit the extent of surveillance, provide protections against arbitrary performance evaluations, and ensure that workers have a voice in the technologies shaping their work environments. Unions also need to evolve to address technological changes in the workplace. Rather than opposing automation outright, unions should advocate for policies that protect workers’ rights in increasingly digitized environments. This includes ensuring stronger collective bargaining powers to address the negative effects of algorithmic management systems and protect workers’ autonomy in the face of technological advancements.

Conclusion: Moving Forward

This shift toward collective action highlights the growing recognition among workers that algorithmic management systems are not just tools for efficiency, but mechanisms that contribute to the overall insecurity of low-wage jobs. As more industries adopt algorithmic platforms to manage workers, the impact on labor will become increasingly important. The introduction of apps such as Rex serves as an example of a broader trend towards the digitization and standardization of work, which has the potential to reshape labor in service industries in ways that prioritize profit and efficiency at the expense of worker well-being.The challenge for labor advocates, lawmakers, and unions will be to protect workers from the harmful effects of these technological shifts, ensuring that their rights and bargaining power are not eroded by growing workplace surveillance.

Works Cited

Levy, K., & Barocas, S. (2018). Refractive surveillance: Monitoring customers to manage workers. International Journal of Communication, 12, 1166-1188.

Rosenblat, A., & Stark, L. (2016). Algorithmic labor and information asymmetries: A case study of Uber’s drivers.