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Work is increasingly shaped by algorithms and automated technologies that standardize and organize the labor process, incorporate managerial tasks, and contribute to new forms of value generation. While this is depicted as a smooth process of innovation, the field is ripe with frictions and tensions. Disrupting Algorithms: Innovating Work and Life in the Digital Economy consists of three panels. Altogether, they discuss how algorithmic power is confronted, negotiated, and disrupted by workers in today’s booming sectors of logistics, online crowdwork, service work, and the gig economy. The papers document how workers in different geographical, social and political contexts redefine the meanings, opportunities, risks, and rewards imposed by system algorithms and other technologies. Building on STS, political economy of technology, feminist theory of technology, and labor process theory, they study how algorithmic control is met with strikes and refusal, new forms of worker-led organizations, as well as everyday resistance and coping. The aim is to challenge the assumption of technology as an external force that single-handedly configures and controls the workforce, and to shed lights on how both the materiality and ideology of innovation are contested and practiced outside of corporate control.
Disrupting Algorithms: Innovating Work and Life in the Digital Economy III includes papers that explore affective, emotional, spatial and temporal dimensions of work and living in the digital economy.
Radical Space in the Midst of Algorithms: Machinic Labor Interruptions against Digital Spatial Abstractions - Marco Briziarelli, University of New Mexico; Emiliana Armano, University of Milan
Re-Configure and Resist Temporal Boundaries in the Gig Economy: Time, Digital Platforms, and Urban Space for Online Food-Delivery Workers - Yujie Chen, Faculty of Information, University of Toronto; Ping Sun, Institute of Journalism and Communication, Chinese Academy of Social Sciences
Collaborative Disruption: Creative Dissidents on China’s Ridesharing Platforms - Shuang Frost, Harvard University