Abstract
With the emergence of digital platforms such as Uber, GrubHub, TaskRabbit, and Amazon Mechanical Turk, there has been a dramatic shift in the options available to workers. Often referred to as the gig economy, on the surface, the rise of digital platforms appears to be ushering in flexibility and independence, enabling workers the ability to work wherever and whenever suits them best. However, there also seems to be an insidious effect arising from the popularization and proliferation of these platforms: widespread exploitation, discrimination, and the loss of worker autonomy as a result of technological oversight. In Your Boss Is an Algorithm: Artificial Intelligence, Platform Work and Labour, authors Aloisi and De Stefano call this effect “algorithmic governance,” where labor forces are managed not by a traditional human manager, but by the anonymous and faceless information technology that buttresses gig economy platforms. The negative outcomes of this algorithmic governance are manifested in myriad ways, including excessive surveillance, a loss of privacy, underemployment, the inability to negotiate or unionize, and a parcelization of higher skill jobs into sundry, routinized tasks.
Near the start of the book, the authors identify the typical arguments in favor of continued automation and an expansion of algorithmically driven management, which include a need to promote and encourage technological innovation, a reduction of human biases and market failures in traditional human management, and the ability to mitigate short-term increases in unemployment using universal basic income. The common sentiment of this discourse is that we should accept the worsening conditions of gig economy workers as inevitable, and therefore deprioritize any effort to ameliorate them given the inexorable progress of automation and artificial intelligence (AI).
Aloisi and De Stefano vehemently disagree with this notion. Throughout the book, they contend that the use of these algorithmic platforms and tools should be curtailed to protect human rights and freedoms. To make this argument, the authors start by first offering a geopolitical and technical explanation of how the platform and gig economies developed. They then move into an exposition on how such digital platforms have largely become a detriment to worker prosperity and well-being. The book then centers on the role of regulation and legal statutes on blunting the damaging effects of algorithmic management, supported with examples of regulatory precedents from the United States, United Kingdom, and European member states. The authors then conclude by musing upon societal considerations and measures that may help in finding a better balance between technological progress and human well-being. Across these sections, the book offers several enriching insights relevant to organizational studies in the context of technology management and reshaping labor.
First, a large, unexpected, and exogenous event can accelerate the reconfiguration of how organizations view and manage work. While food delivery, ride sharing platforms, and remote work options existed long before Covid-19, it wasn’t until the full effects of lockdowns were seen that there was a fundamental shift in societal acceptance for alternate service options. Salaried workers who enjoyed stable employment and benefits were laid off, many of whom subsequently took up precarious gig economy jobs that offer little employee protection. Remote work, which was previously viewed as a fringe arrangement used in exceptional circumstances, became the norm. This paradigm shift led to the inevitable expansion of data-driven and algorithmic oversight, where information technology became the de facto managers of platform and remote workers. A notable consequence of this restructuring is that algorithmic evaluations of worker performance can be rife with its own biases, which can be persisting and harmful to worker rights and dignity, given the black-boxed nature of many AI-based platforms (Newlands, 2021).
Furthermore, advances in robotics and big data processing have led to a hollowing out of middle skill jobs, resulting in a rapid expansion of low skill, repetitive work where employees and workers can be easily governed by algorithms and readily replaced. In terms of remote work, employees are often subject to heightened surveillance through data capture and tracking tools that record when an employee logs on and is working. These tools include communication platforms such as Slack, and others that are much more intrusive, such as HubStaff and Sneek, which monitor keystrokes and observe workers in real time through webcams. The authors argue that tools such as these have led to the dehumanization and datafication of employees. The potential for such surveillance practices reminds us of how data is rapidly transforming how organizations operate, reorienting structural norms and undermining employee safety (Alaimo, 2022).
Second, an in-depth explanation is provided on how platforms and algorithms have distorted the traditional balance of power between management and workers, which has been harmful to human well-being. For instance, while human governance of workers was constrained by the physical limitations of a single manager overseeing multiple employees, algorithmic management has no such limits. It is pervasive, real-time, and never turns off. Furthermore, human data can now be collected and collated across a multitude of sources, including individuals’ creative and written outputs, financial information, biometric data (e.g., fingerprints), webcam videos, and health information captured by wearables. This expansion of data collection has led to humans becoming digital artifacts for firms to commodify (Demetis & Lee, 2018). In other words, organizations are equipped with greater opportunities to exploit human labor because of the ability to capture sensitive human data.
Aloisi and De Stefano argue that expanded data collection has also enabled organizations to predict employee behaviors (e.g., their probability of quitting) based on the massive datasets that are available to them, which has worrying potential for discrimination. The continued infusion of algorithms into data-driven organizational decision-making means that managerial decisions will be increasingly influenced, or even overtly made, by automated systems, and we are reaching a point in which this infusion will be almost impossible to undo (Alaimo & Kallinikos, 2021).
Finally, the authors place the primary responsibility for protecting the rights and well-being of workers in the hands of government, focusing a large part of their book on regulatory interventions and precedents that can inform the design of new laws to protect individuals. The regulatory insights provided are mostly in the context of gig economy platform workers, such as Uber and Lyft drivers and delivery workers for apps such as Foodora. The number of these workers has risen dramatically in recent years, especially since the Covid-19 pandemic. The authors argue that this rise is not necessarily conducive to societal and economic prosperity, given that these workers have fewer rights and avenues of recourse in the face of mistreatment, and their remuneration is paltry and unreliable. In most jurisdictions they are self-employed, and thus platform owners can avoid the costs and responsibilities of employment, but still exert substantial influence through algorithmic management. The European Pillar of Social Rights took a step in resolving this unfairness by establishing a directive where gig workers would receive equal treatment to their direct employee counterparts. However, its implementation has been somewhat open to interpretation; there is a large variation in actual worker protection even within European Union member states.
Aloisi and De Stefano urge regulatory agencies, particularly those in advanced countries, to continue to develop legal frameworks that protect workers. They are emphatic that the cornerstone of modern organizations and societies is the balance between managerial power and employee rights, an idea that is receiving renewed attention in the management literature in light of the rapid proliferation of AI (Varma, Dawkins, & Chaudhuri, 2023). The authors conclude the book by criticizing the idea that universal basic income would solve mass unemployment and the displacement of workers by automation. Regardless of whether a worker has this basic threshold of income, Aloisi and De Stefano suggest that workers will still need to work to supplement it. Thus, they will be subject to the same practical and existential risks posed by algorithm-based management. The authors reiterate the importance of developing nuanced regulations that allow for workers to self-organize, to be treated with dignity, and to seek gainful and reliable employment.
We find these insights to be a novel and important step in not only identifying the near-term threats posed by algorithm-based platforms, but in suggesting methods by which these threats can be mitigated. We were convinced that there is a crucial need for government intervention to protect the rights of workers from algorithmic mismanagement. We also appreciated that the book devoted space to recognizing that algorithms are not inherently “bad.” In contrast to other Kafkaesque depictions of AI, the authors advocate for a balanced approach to harnessing algorithms for economic achievement and the protection of human autonomy. Finally, we laud the authors’ accessible writing style and personal anecdotes amid the rigorous research-oriented analysis. This made the book compelling and coherent, which we believe will elicit useful insights for scholars and practitioners alike.
Despite the valuable lessons readers will glean from the book, we offer one critique. Notwithstanding the importance of the role of government regulation, we felt there emphasis was lacking on the responsibility of the organization to protect and promote worker dignity and well-being. By focusing the book so heavily on the responsibility of government to establish legal structures that curtail the managerial power of algorithm-based platforms, it deemphasizes the agency and responsibility of the organization itself. The organization that leverages algorithmic governance is not an innocent bystander that simply has no choice but to adopt surveillance tools that disempower and disenfranchise the working class in order to remain competitive. The organization bears substantial responsibility not only to abide by jurisdictional laws, but to design managerial practices that protect and promote worker dignity, a sentiment that is well supported in the field of business ethics (Pirson, 2019).
We do not dismiss the importance of government regulation and, when necessary, intervention for preventing harms from algorithmic governance. Indeed, some government programs have proven to be successful in promoting societal outcomes alongside economic prosperity, such as financial incentives for start-ups in university incubators to pursue applications that produce societal benefits (Park, Goudarzi, Yaghmaie, Thomas, & Maine, 2022). However, we would be remiss to neglect the role that organizations play in preventing harms from algorithms that they create or adopt. Leaders must act as stewards of human well-being creation before investing in initiatives for wealth creation (Pirson, 2019). We feel that organizational scholars are well positioned to clarify the responsibility of firms to protect human dignity in an era of increasing algorithmic governance.
In closing, Your Boss Is an Algorithm: Artificial Intelligence, Platform Work and Labour is a well-written call to avoid complacency as digital platforms transform traditional forms of management. The future of work is ever changing and unpredictable, but it is within our control to change. Aloisi and De Stefano offer an important contribution to prevent the displacement of labor and prioritize the well-being of the worker in an era of rapid technological change.
