For Work / Against Work
Debates on the centrality of work

"Refractive Surveillance: Monitoring Customers to Manage Workers"

by Levy, Karen; Barocas, Solon (2018)

Abstract

Collecting information about one group can facilitate control over an entirely different group—a phenomenon we term refractive surveillance . We explore this dynamic in the context of retail stores by investigating how retailers’ collection of data about customers facilitates new forms of managerial control over workers. We identify four mechanisms through which refractive surveillance might occur in retail work, involving dynamic labor scheduling, new forms of evaluation, externalization of worker knowledge, and replacement through customer self-service. Our research suggests that the effects of surveillance cannot be fully understood without considering how populations might be managed on the basis of data collected about others.

Key Passage

Refractive surveillance broadens the scope of analysis of data collection to more comprehensively account  for  its  effects  on populations  other  than  its  putative  target.  In  the  retail  context,  customer  data collection  has  the  capacity  to  reshape  managerial  practices—to  the  potential  economic  detriment  of workers—via  several  independent  mechanisms.  Customer  traffic  data  allow  retailers  to  optimize  labor scheduling  dynamically,  creating  the  potential  for  destabilizing  and  unpredictable  work  schedules. Customers’behaviors and interactions in stores give rise to the capacity for greater control over workers’encounters  with  them,  as  well  as  new  forms  of  worker  evaluation.  Clienteling  software  externalizes customer  profiles  and  preferences  to  render  workers  more  easily  substitutable;  sensor-based self-service allows  for  workers  to  be  replaced  altogether  by  data-driven  signage  and  checkout  systems.  Each  case demonstrates   refractive   surveillance   dynamics,   in   which   retailers   leverage   customer  data  in   the management of workers. (p.17)

Keywords

Inequality, Surveilance, Worker Monitoring, Privacy, Data

Themes

Automation

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