Accepted Paper:

Data science / science studies  

Author:

Cathryn Carson (University of California, Berkeley)

Paper short abstract:

Inside universities, data science is practically co-located with science studies. How can we use that proximity to shape how data science gets done? This paper reports on experiments in data science research and organizational/strategic design.

Paper long abstract:

Inside universities, data science is practically co-located with science studies. How can we use that proximity to shape how data science gets done? Drawing on theorizations of collaboration as a research strategy, embedded ethnography, critical technical practice, and design intervention, this paper reports on experiments in data science research and organizational/strategic design. It presents intellectual tools for working on data science (conceptual distinctions such as data science as specialty, platform, and surround; temporal narratives that capture practitioners' conjoint sense of prospect and dread) and explores modes of using these tools in ways that get uptake and do work. Finally, it draws out possible consequences of the by now sometimes well-anchored situation of science studies/STS inside universities, including having science studies scholars in positions of institutional leverage.

Panel T113
Critical data studies