Full Description
This volume contains Open Access chapters.
Bringing together cutting-edge papers, this edited volume examines the growing phenomenon of algorithmic organizing—the embedding of powerful data-driven tools into organizational structures, routines, and social practices. These technologies are fundamentally transforming organizational landscapes, raising a critical question: How are algorithmic systems reshaping work, decision-making, and the broader social order?
Charting a holistic perspective on algorithmic organizing, this volume draws on multimodal inquiry and "data work", examining both the technical and sociopolitical dimensions of how organizations adopt, adapt to, and govern algorithmic tools in practice. From data scientists' improvisational craftwork and organizational readiness for algorithmic deployments, to user encounters with opaque platform logics and extreme humanitarian settings, the papers collectively illuminate how algorithms become interwoven with human expertise, professional identities, and institutional demands. Several contributions highlight the tensions that arise when algorithmic systems challenge existing norms—such as professional autonomy and regulatory compliance—underscoring the need for continuous negotiation and re-scripting of roles and responsibilities. The studies also reveal new ethical quandaries related to transparency, fairness, and accountability, pointing to complex trade-offs between efficiency gains and potential harms such as worker surveillance or bias amplification.
Deepening our understanding of how algorithmic organizing is enacted and contested across diverse settings, Algorithmic Organizing offers a roadmap for future research that bridges disciplinary boundaries and highlights the social, technical, and ethical ramifications of an increasingly data-driven world.
Contents
Chapter 1. Introduction: Algorithmic Organizing; Vern L. Glaser, Christine Moser, Deborah A. Anderson, and P. Devereaux Jennings OPEN ACCESS
Section A. Algorithmic Organizing and Data Scientists
Chapter 2. Data-Based Craft: How Data Scientists Craft Their Data, Models, and Products; Konstantin Hopf, Mayur Joshi, Arisa Shollo, and Marta Stelmaszak
Chapter 3. Assembling Frankensteins: How Data Scientists Stitch Together Provisional Artifacts to Generate Novel Insights; Rodrigo Valadão, Vern L. Glaser, and Timothy R. Hannigan
Section B. Transforming Organizations for Algorithmic Readiness
Chapter 4. Making Organizations Algorithm-Ready: Algorithmic Organizing Through Techno-Organizational Scripts; Ursula Plesner and Lise Justesen
Chapter 5. Machine-Readable Legitimacy: An Ethnography of Regulatory Technology; Anne L. Washington
Section C. Opening Up Algorithmic Encounters
Chapter 6. Making Sense of Glitches? Exploring Cultural Producers' Understandings of and Interactions With the Instagram Algorithm; Lena Kostuj and Hannah Trittin-Ulbrich
Chapter 7. Human-AI Coordination in Extreme Contexts: Overcoming Trust and Agency Concerns; Shivaang Sharma and Angela Aristidou
Section D. Advancing Methodologies for the Study of Algorithmic Organizing
Chapter 8. Interpreting the Inscrutable: Ethnographic Approaches to Studying the Development of Machine Learning Models; Bryan Spencer and Bomi Kim
Chapter 9. Exploring Algorithmic Assemblages Through Multimodal Inquiry; Verena Timmer, Thomas Wrona, and Pauline C. Reinecke
Chapter 10. Epilogue: Designing and Performing the Editorial Assemblage; Christine Moser, Deborah A. Anderson, P. Devereaux Jennings, and Vern L. Glaser OPEN ACCESS
