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Accepted Paper:

Data Science and the Security State  
Lauren Di Monte (North Carolina State University)

Paper short abstract:

This paper studies the relationship between data science and the American security state. It examines exchanges between data science and federal intelligence agencies, and describes how work in this field is enabled by particular infrastructures and regimes of data collection.

Paper long abstract:

This paper will study the relationship between the American security state and the technologies, practices and networks of data science. It will demonstrate how and why data science relies on surveillance and inscription technologies borrowed from intelligence agencies and will show how the work of data science is enabled by particular infrastructures and regimes of data collection. By describing the technological and organizational origins of data science this paper will provide an enriched context for understanding contemporary state-sponsored data science projects, like the NSA's MARINA database, which logs and analyses data culled from millions of web browsers to predict emerging threats, as well as relationships between state and industry data science projects grounded in predictive analytics, like Amazon's "anticipatory package shipping" model (Speigel, McKenna, Lakshman, & Nordstrom, 2013). Moreover, by describing how state-sponsored data science tools and processes migrate into new domains, like industry and academia, this paper will help expose possible trajectories for the future development of the data science profession.

Panel T164
The Potential Futures of Data Science: A Roundtable Intervention
  Session 1 Thursday 1 September, 2016, -