Search Results
Search Results
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Algorithmic Management in the Food Delivery Sector – a Contested Terrain?
Forms of algorithmic management (AM) play an essential role in organizing food-delivery work by deploying artificial intelligence-based systems to coordinate driver routes. Given the risks of precarity and threats posed by AM, which are typically related to (migrant) platform work, the question arises to what extent structures of co-determination can positively shape this type of work and the technologies involved. Based on an in-depth case study within a large food-delivery company, this article is guided by two questions: (1) How do companies use algorithm-based management and performance control, and how do the couriers perceive them? (2) What priorities, strategies, resources, and achievements do works councils and trade unions have with regard to co-determination practices? Our analyses indicate that algorithmic management poses problems of non-transparency and information asymmetry, which in turn call for new forms of and procedures for co-determination. Our study does not find evidence that AM practices aim to individually profile and discipline couriers. The main challenges for the works council and trade unions arise from the couriers’ generally precarious working and employment conditions; data- and AM-related issues do not represent the central area of conflict. However, our study identifies new demands regarding the co-determination of AM and underlines the importance of institutional regulation at the legal and sectoral level.
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International Regulation of Platform Labor: A Proposal for Action
Platform-mediated work is a source of livelihood for millions of workers worldwide. However, because platforms typically classify workers as ‘independent contractors’, those workers are generally excluded from the scope of labor rights. This has a corrosive effect on working standards of platform workers, creating the need for an international regulatory framework to prevent a race to the bottom. To address this situation, the article proposes an outline for an International Labor Organization (ILO) Convention for the regulation of platform work going beyond the employee/independent contractor dichotomy. It identifies five core issues in the platform economy – low pay, poor working conditions, inaccessible and unreasonable contracts, unfair management, and a lack of representation – and demonstrates how existing ILO standards could be adapted to address these issues. The proposals are informed by the evidence collected by the Fairwork project through its participatory and multidisciplinary research.
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Trapped in the Matrix: Algorithmic Control and Worker Dispossession in the African Platform Economy
Digital labor platforms are reshaping the work landscape in Sub-Saharan Africa, promising enhanced productivity and empowerment. Yet, this study reveals a more complex reality, particularly in Rwanda, South Africa, and Zimbabwe. Based on 41 in-depth interviews, it exposes how algorithmic management systems deeply erode worker autonomy, highlighting significant financial, task, and behavioral dispossession. This research, grounded in neo-Marxist and postcolonial theories, scrutinizes the nuanced limitations of autonomy and the pervasive control exerted by algorithmic management, reflecting the lived experiences of workers. The findings illuminate enduring patterns of accumulation that echo historical exploitation, maintaining asymmetric power dynamics and dependence. Despite this, the study captures the agency of workers as they navigate and resist these systemic constraints, challenging the dominant techno-optimistic narrative. It underscores the critical need for contextually informed empirical research to shape policies that champion equity and elevate marginalized voices during transformative economic shifts.
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The Automation of Management and the Multiplication of Labor: On the Role of Algorithmic Management in the Recomposition of Labor
Digital technologies are increasingly used to automatically organize, measure, and control labor in many sectors and industries. This article offers an analysis of how digital technologies, particularly algorithmic management, not only reshape the ways in which work is done and controlled but also drive profound transformations in the division and composition of labor. Drawing on qualitative and ethnographic studies of the gig economy, this research article demonstrates how the digital automation of management serves as a prerequisite for efficiently and flexibly incorporating highly heterogeneous workforces into production processes. This is first demonstrated by an analysis of the online gig economy and its capacity to integrate a wide range of geographically dispersed workers into digital production processes. Then, the paper examines the role of migrant labor in the urban gig economy, contending that in this context too, digital technologies and algorithmic management play a crucial role in the flexible and efficient inclusion of highly diverse workforces. This ultimately illustrates how digital technologies for automated management are integral to a multifaceted process of workforce heterogenization, a phenomenon that can be conceptualized within the framework of the multiplication of labor.
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Commodification and Disruption: Theorizing Digital Capitalism
There is little disagreement that digital technologies are transforming contemporary economies and societies. However, scholars have only begun to systematically think about how digitalization – the process whereby more and more of what we say, think, and do becomes mediated by digital technologies – is both driven by and transformative of capitalism. This paper argues that when one speaks about digitalization, one cannot be silent about capitalism. It reconstructs commodification and disruption as key features of capitalist development. It then shows how three digital revolutions – the platform, (big) data, and artificial intelligence revolutions – have ushered in a new wave of commodification and disruption, giving rise to digital capitalism. Finally, it discusses the challenges commodification and disruption pose in the form of redistribution of resources, rebalancing of power, rule adaption, and market re-embedding. The paper brings together a wide range of scholarship to offer a historically and theoretically grounded framework for how to think about and study the rise of digital capitalism.
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Labor-atories of Digital Economies: Latin America as a Site of Struggles and Experimentation
This article argues that the digital labor developments and struggles are labor-atories of digital economies, with special focus in Latin America. This means that, on the one hand, capital is experimenting and updating forms of control and exploitation - through the long trajectory of informality and dependency and, on the other hand, workers are trying and experimenting forms of organizing and collectivities, also updating Latin American rich histories of organizing, solidarity economies and community technologies. The emphasis on “labor” means that these laboratories are products of class struggles and capital-labor relationships. The paper unpacks the argument with four short insights from ongoing research: 1) Latin America as not only of research site; 2) The updating of informality in the Latin American AI context; 3) Global implications of data work, AI value chains, and the cultural sector; 4) Digital solidarity economies as a Latin American response to the current digital labor scenario, including digital sovereignty and autonomy.
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Algorithmic Management: From Technology to Politics and Theory
This article provides an overview of the concept of ‘algorithmic management’. This concept has played an important role as an organizing frame for empirical research seeking to demystify the role of labor platforms in intermediating paid work. More recently, this concept has helped shed light on the increasing use of computer algorithms to automate managerial tasks in conventional work settings. However, beyond platform work, most research is confined to warehousing, with only a few notable studies in manufacturing and retail. Moreover, most empirical investigations highlight the conditional nature of algorithmic management, with human managers retaining important functions. Only recently have studies begun to go beyond technical functions and consider how human elements (worker, manager, and technologist) shape such systems. Relatedly, the contingencies, moderations, and variations in algorithmic management have received insufficient consideration. These weaknesses result from a tendency to generalize from single case studies without adequately extending out from the case to theory, history, and geography, and not situating empirical research within a broader theoretically motivated research program. Workplace regime theory, with its focus on technology, power, and embeddedness, is presented as a remedy that enables algorithmic management research to account for variations while explaining regularities.
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The Politics of Risk in the Digital Services Act: A Stakeholder Mapping and Research Agenda
The EU’s 2022 Digital Services Act requires large online platforms to regularly assess and mitigate ‘systemic risks’ to various public-interest goals, including fundamental rights, civic discourse, public health and security. Drawing on social constructionist understandings of risk, this article theorizes systemic risk management under the DSA as an arena for political power and contestation, since translating its broadly-defined abstract principles into actionable risk management procedures will entail making many contestable political decisions about how online platforms should be governed. This raises the question: who will exercise power in these decision-making processes? Providing some first answers to this question, this article makes three key contributions. First, it maps the key stakeholder groups involved, and the legal and institutional mechanisms through which they can participate in DSA systemic risk management. Second, it critically analyzes the power dynamics and unequal resources that will structure stakeholder participation. Third, this stakeholder mapping provides a foundation for future research on the politics of DSA systemic risks. The article concludes with reflections on directions for future research on the political agendas, priorities and strategies that shape platform governance.
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Counter-Hegemonic Neoliberalism: Making Sense of EU Platform Regulation
The platforms that hold the power in the digital economy, and the politics that surround them, are a central topic in contemporary political economy. The EU is widely perceived as a digital laggard, as it is home to very few leading digital corporations, and it is exposed to the market hegemony of the Big Tech platforms. Moreover, the EU is often considered the pioneer of digital regulation, and its platform politics have gained momentum as the EU Commission has unleashed a swathe of new regulatory initiatives, ranging from competition policies to governance of digital content, data flows and platform work. In this essay, we treat platform control and regulation as a matter of contested market design. We offer an analysis of the recent stream of EU platform regulation, questioning how it relates to the historical trajectory of the platform economy and established path dependencies within the EU. We argue that it is characterized by a critical approach to the power of digital platforms and a continuation of negative integration in the EU, and we suggest that it should be understood as a manifestation of counter-hegemonic neoliberalism, as it essentially enforces market-based governance of society through political market design.
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Unveiling ‘Algorithm Governance’: Shaping Labour Platforms’ Strategies and Working Conditions in the Digital Era
Research on platform work has primarily focused on analyzing how algorithmic management influences working conditions by empowering platforms to govern digitally-delivered services. However, prior research has overlooked the crucial aspect of how algorithmic management underlies platforms’ use of diverse contractual forms of employment available in the labor markets from where they source their workforces. Bridging this gap is vital to understanding how labor platforms integrate algorithm management, which employs digitally programmed procedures for coordinating and governing labor input, with various contractual employment structures influenced by regulations and collective actors such as trade unions. Coined as algorithm governance, this phenomenon represents the fusion of algorithm management with contractual employment frameworks, emanating from labor market regulations and policies. This essay pioneers the concept of algorithm governance, illuminating its ontological capacity to enrich debates on algorithm management. Algorithm governance thus explains how algorithm management intricately shapes working conditions by influencing the use of diverse contractual employment forms within the labor market.
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On Algorithmic Management: The Importance of Debate on Future Research
A surge of research interest in platform work and the gig economy has seen debates around worker resistance and algorithmic management frequently come to the forefront. Many researchers will now be accustomed to reviewing journal submissions and taking in conference papers that cover these issues. The breadth of the emerging literature means that it builds upon various starting points, theoretical approaches, and histories. Pleasingly, research on work over the past decade has transformed from a relatively marginal pursuit to a highly popular focus across many disciplines, deepening and extending our collective understanding of the topic. This has the potential to introduce fresh ideas and new approaches. However, it does risk research failing to relate to and build upon historical debates in the field. This short article first presents some of the key arguments that have emerged in the research on algorithmic management and considers how knowledge has developed in relation to platform work. It examines some of the strengths and weaknesses of the literature in this area, especially the lack of theoretical debate in an exponentially expanding body of literature. The article finishes by suggesting some key areas in which future research needs to be directed, particularly interrogating the production, practice, and limits of algorithmic management.
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The Emergence of Platform Regulation in the UK: An Empirical-Legal Study
Online platforms have emerged as a new kind of regulatory object. In this article, we empirically map the emergence of the field of platform regulation in one country: the United Kingdom (UK). We focus on the 18-month period between September 2018 and February 2020 when an upsurge of regulatory activism reflected increasing sensitivity to national sovereignty in the context of Brexit. Through an empirical–legal content analysis of eight official reports issued by the UK government, parliamentary committees, and regulatory agencies, we code the online harms to which regulation is being asked to respond; identify relevant subject domains of law (such as data protection and privacy, competition, education, media and broadcasting, consumer protection, tax law and financial regulation, intellectual property law, security law); and analyze the agencies referred in the reports for their centrality in the regulatory network and their regulatory powers. Drawing on Bourdieu’s notion of “field,” we observe the emergence of regulators with investigatory and enforcement powers that stand in mutually unstable power relations to each other as well as vis-à-vis shifting executive and legislative interventions. Online platforms appear to acquire authority to exercise state powers.
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Making Arguments with Data: Resisting Appropriation and Assumption of Access/Reason in Machine Learning Training Processes
This article presents an approach to practicing ethics when working with large datasets and designing data representations. Inspired by feminist critique of technoscience and recent problematizations of digital literacy, we argue that machine learning models can be navigated in a multi-narrative manner when access to training data is well articulated and understood. We programmed and used web-based interfaces to sort, organize, and explore a community-run digital archive of radio signals. An additional perspective on the question of working with datasets is offered from the experience of teaching image synthesis with freely accessible online tools. We hold that the main challenge to social transformations related to digital technologies comes from lingering forms of colonialism and extractive relationships that easily move in and out of the digital domain. To counter both the unfounded narratives of techno-optimism and the universalizing critique of technology, we discuss an approach to data and networks that enables a situated critique of datafication and correlationism from within.
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Is Authenticity an Effective Antidote to Misinformation?
The growing impact of false and misleading information is a cause for concern. Some have suggested an authenticity crisis as the cause, namely, the fact that we can no longer be certain of the source and integrity of a particular piece of information. To fix this, the ubiquitous use of digital signatures has been proposed to (re)establish the authenticity of information. We argue that this is unlikely to curb the impact of misinformation for several reasons. First, little evidence suggests that more authenticity could theoretically solve part of the misinformation problem. In fact, the implied use of signatures as a proxy for veracity is fundamentally problematic. Second, there are significant barriers to the practical implementation of ubiquitous signing. Lastly, we point out potential negative side effects. We conclude that authenticity is not effective in countering misinformation.
