Title: Perspectives On Data For Good: The Emergence Of Embodied Data Discourses
Program: Doctor of Philosophy in Public Policy and Administration
Advisor: Dr. Jen Schneider, School of Public Service
Committee Members: Dr. Eric Lindquist, School of Public Service; Dr. Stephen Crowley, Philosophy; and Dr. Michael Ekstrand, Computer Science
In policy sciences, data have traditionally been a tool used by scientists and technocrats to guide state policy. Boundaries around what counts as data generally fall along traditional understandings that data are neutral, objective, and abstracted from individual bodies and experiences. Unfortunately, this understanding of data has a history of perpetuating harmful social hierarchies and, especially in the era of “big data”, mirroring our racial and gendered prejudices. In the field of Science and Technology Studies, this is referred to as data colonialism. More recently, however, data have been claimed as a tool by a different kind of actor operating in a unique environment. These new actors, such as police officers and citizen activists, are negotiating and redefining who is considered a data expert and what we understand data to be.
These conversations between traditional and novel understandings of data can be seen within the data for good movement, where actors from a broad range of backgrounds and training come together for the purpose of advancing some notion of social good. Given the history of data colonialism, how can these relatively new understandings of data promote the social good while avoiding practices of data colonialism? This research analyzes this question through a qualitative comparative case study of two dissimilar sites: Measure Austin, a non-profit advocacy organization for people of color, and the Big Data Hubs program within the National Science Foundation. Using the theoretical framework of Data Feminism, the data from participant interviews suggests that shifting understandings of data rely on the emergence of the concept of embodiment. This research details how the concept of embodiment maps onto the actors, the environment, the discourses used to understand what data are and understandings of social good. The dissertation suggests that “embodied data” offers an alternative to the predominance of market-driven data approaches.