[acc-cca-l] CFP - Disrupting Algorithms: Innovating Work and Life in the Digital Economy

Alessandro Delfanti a.delfanti at utoronto.ca
Tue Dec 18 14:39:52 MST 2018

CFP for an open panel at the 4S Conference (Society for Social Studies of Science, September 2019, New Orleans). Deadline for abstract submission: February 1, 2019. Apply at https://www.4s2019.org/accepted-open-panels/

Open panel 37: Disrupting Algorithms: Innovating Work and Life in the Digital Economy

Alessandro Delfanti, University of Toronto
Yujie Chen, University of Leicester

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.

Studies on technology and workers have well-documented workers’ resistance to the introduction of new technologies on the shop floor from manufacturing to call centers. Building on this scholarly tradition, we aim to discuss how algorithmic power is confronted, negotiated, and disrupted by workers in today’s booming sectors of logistics, online crowdwork, or the so-called gig economy. The field of STS offers crucial concepts and tools to challenge the assumption of technology as an external force that single-handedly configures and controls the workforce. STS shed lights on how both the materiality and ideology of innovation are contested and practiced by specific actors.

We are interested in papers that deal with workers’ creative means of counteracting algorithmic control, from strikes and refusal to everyday resistance and coping, as well as new forms of worker-led organizations, in different geographical, social and cultural contexts. Perspectives rooted on user theory, political economy of technology, feminist theory of technology, and labour process theory are welcome among others. We also aim to solicit papers that document and study how workers alter, redefine, and regenerate meanings, opportunities, risks, and rewards other than those imposed by system algorithms and other technologies.

Alessandro Delfanti
University of Toronto
a.delfanti at utoronto.ca

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