Plenary: Statistical Imaginaries: An Ode to Responsible Data Science

Опубликовано 25 января 2022, 1:40

Speakers: 
Ashley Llorens, Vice President and Distinguished Scientist, Microsoft
danah boyd, Partner Researcher, Microsoft Research
John Abowd, Associate Director for Research and Methodology, and Chief Scientist, U.S. Census Bureau

Data science is increasingly being used to ground decision-making in both industry and public life. As data become significant and powerful, people who rely on those data come to expect certain things from the data. All too often, data are expected to be precise, neutral, and objective. Those data are expected to speak with confidence—and not reveal their limitations. Left unchecked, data become illusory in the minds of many.

Drawing on her research into the 2020 US census, danah boyd will discuss how illusions surrounding data can be weaponized. She will highlight how the US Census Bureau's decision to embrace differential privacy as part of its system to protect statistical confidentiality upended what people imagined the work of data to be. She will then turn to discussing the importance of grappling with uncertainty and limitations as a key part of responsible data science.

After this research talk, danah will interview the US Census Bureau's Chief Scientist, John Abowd, about the challenges the government faces in its effort to modernize federal statistics.

This talk builds on the scholarship of others. Those who are interested in learning more about these themes may value the following work:

Bouk, D. (2015). How Our Days Became Numbered: Risk and the Rise of the Statistical Individual. University Of Chicago Press.
Daston, L. & Galison, P. (1992). The Image of Objectivity. Representations, 40, 81-128.
Dwork, C., Kohli, N., & Mulligan, D. (2019). Differential Privacy in Practice: Expose Your Epsilons! Journal of Privacy and Confidentiality, 9(2).
Jasanoff, S., & Kim, S.-H. (Eds.). (2015). Dreamscapes of Modernity. The University of Chicago Press.
Porter, T. M. (1995). Trust in Numbers: The Pursuit of Objectivity in Science and Public Life. Princeton University Press.
Starr, P. (1987). The Sociology of Official Statistics. In W. Alonso & P. Starr (Eds.), The Politics of Numbers (pp. 7–57). Russell Sage Foundation.

Learn more about the 2021 Microsoft Research Summit: Aka.ms/researchsummit