Please check out this publication and its public qualitative data set from some OOW members:
Vertesi, J. A., Goldstein, A., Enriquez, D., Liu, L., & Miller, K. T. (2020). Pre-Automation: Insourcing and Automating the Gig Economy. Sociologica, 14(3), 167–193. https://doi.org/10.6092/issn.1971-8853/11657
This paper examines a strategic configuration in the technology, logistics, and robotics industries that we call “pre-automation”: when emerging platform monopolies employ large, outsourced labor forces while simultaneously investing in developing the tools to replace these workers with in-house machines of their own design. In line with socioeconomic studies of imagined futures, we elaborate pre-automation as a strategic investment associated with a firm’s ambitions for platform monopoly, and consider Uber, Amazon Flex and Amazon Delivery Services Partnership Program drivers as paradigmatic cases. We attempt detection of firms’ pre-automation strategies through analysis of patenting, hiring, funding and acquisition activity and highlight features of certain forms of gig work that lay the infrastructural foundations for future automation. We argue that certain forms of platform labor may be viewed dynamically as an intermediate arrangement that stages outsourced tasks for subsequent insourcing through automated technologies, and discuss the implications of this configuration for existing theories of outsourcing and technology-driven job displacement.
PUBLIC DATA: Diana Enriquez recently made the qualitative data from this study public for use here on Princeton’s Open Data project.