Embedded Reproduction in Platform Data Work

This talk focuses on the experiences of Latin American data workers who annotate data for machine learning algorithms through labor platforms. It introduces the notion of ‘embedded reproduction’: the relationship between embeddedness, the degree to which non-economic institutions and their social environment constrain socioeconomic activity, and social reproduction, or the activities that nurture, maintain, and regenerate the workforce. Building on an analysis of 38 interviews with platform workers, I suggest that they are situated in a highly disembedded market due to the lack of regulations on the data production process, giving free rein to platforms to set rules to their detriment. This talk, and the article upon which it is based, explores how this disembeddedness shapes social reproduction by studying three forms of collective social support received by workers: from family members, neighbors and local communities, and online groups. The support of these networks is primarily local, depends on high levels of trust, and is gendered. These findings suggest that platform data work is unsustainable from an embedded reproductive perspective since platform intermediation leads workers and local communities to carry out the social and economic risks associated with this form of gig work. This research invites a dialogue between the embeddedness framework with social reproduction as well as a consideration of the importance of nature and natural resources in the study of social environments.

Julian Posada is an incoming Assistant Professor of American Studies at Yale University (starting in July 2023). His research integrates theories and methods from information studies, sociology, and human–computer interaction to study technology and society. He is currently exploring how the artificial intelligence industry perpetuates coloniality by focusing on the relationship between human labor and data production. This research focuses on the experiences of outsourced workers in Latin America employed by digital platforms, primarily from the United States, to produce machine learning data and verify algorithmic outputs. Posada recieved his Ph.D. in Information from the University of Toronto in 2022.

The event is part of the Seminar Series “Platform Politics and Policy”.

Researchers from outside the WZB who would like to attend may email the organizer, robert.gorwa [at] wzb.eu, to be put onto the seminar series mailing list.