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- ItemAlgorithmic Management in the Food Delivery Sector – a Contested Terrain?(Weizenbaum Institute, 2024-10-04) Wotschack, Philip; Hellbach, Leon; Butollo, FlorianForms 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.
- ItemOn Algorithmic Management: The Importance of Debate on Future Research(Weizenbaum Institute, 2024-07-24) Woodcock, JamieA 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.
- ItemToo Far Away from the Job Market – Says Who? Linguistically Analyzing Rationales for AI-based Decisions Concerning Employment Support(Weizenbaum Institute, 2024-07-03) Berman, AlexanderThis paper describes an AI-based decision-support system deployed by the Swedish Public Employment Service to assist decisions concerning jobseekers’ enrolment in an employment support initiative. Informed by previous research concerning explanations in relation to trust, appealability, and procedural fairness, as well as jobseekers’ needs and interests in relation to algorithmic decision-making, the study linguistically analyses the extent to which the system enables affected jobseekers to understand the basis of decisions and to appeal or take other actions in response to automated assessments. The study also analyses the degree to which rationales behind decisions accurately reflect the actual decision-making process. Several weaknesses in these regards are highlighted, largely resulting from the opacity of the statistical model and the linguistic choices behind the design of explanations. Potential strategies for increasing the explainability of the system as a means to meet the needs and interests of affected jobseekers are also discussed. More broadly, the study contributes to a better understanding of how the linguistic design of AI explanations can affect normative dimensions, such as trust and appealability.
- ItemUnveiling ‘Algorithm Governance’: Shaping Labour Platforms’ Strategies and Working Conditions in the Digital Era(Weizenbaum Institute, 2024-07-02) Pulignano, ValeriaResearch 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.
- ItemThe Automation of Management and the Multiplication of Labor: On the Role of Algorithmic Management in the Recomposition of Labor(Weizenbaum Institute, 2024-05-14) Altenried, MoritzDigital 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.