Data & Society

Conversations on the Datafied State – Part Two: The Automated State


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Ranjit Singh, Researcher at D&S, in conversation with Joanna Redden, Assistant Professor at the Faculty of Information & Media Studies at the University of Western Ontario and the co-director of the Data Justice Lab, and Michele E. Gilman, Venerable Professor of Law and Associate Dean for Faculty Research and Development at the University of Baltimore School of Law and director of the Civil Advocacy Clinic.
The automated state is one that seeks to replace human workers with machines. There are three general motivations. One, the desire to leverage computational speed to handle rote and routine work more efficiently. Two, the desire to improve the accuracy, fairness, or consistency of decision-making in light of human fallibility. Three, the desire to depoliticize decision-making (or appear to) by placing it out of reach of human discretion. These motivations, however, raise distinctive concerns about oversight and the ability to seek recourse in the case of errors or bugs in decision-making. What does interacting with systems, interfaces, and datasets require of people interfacing with the Datafied State? What literacies are necessary? What room is there for voice? What does automation look like in practice? Who is rendered invisible when showcasing success in automating state practices?
About Data & Society
Data & Society is an independent nonprofit research organization. We believe that empirical evidence should directly inform the development and governance of new technology. We study the social implications of data and automation, producing original research to ground informed, evidence-based public debate about emerging technology.
About the Series
The Datafied State is an emerging research agenda that seeks to explore the relationship between datafication and public administration. It is concerned with the proliferation of data sources, infrastructures, and computational techniques adopted across the public sector. The processes through which governments procure, develop, implement, and legally mandate the use of digital and computational systems are increasingly blurring the boundaries between what is considered public and private. So, how datafied is the state today? How can we find out?
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