Ryan Steed, Carnegie Mellon University
In theory, techniques for privacy-preserving analytics (PPA) offer organizations an opportunity to maintain and expand access to valuable data without compromising individuals' privacy. In practice, the adoption of these techniques is not straightforward---small differences in engineering and design can have great impacts on the kind of privacy realized---and little work examines what leads organizations to pursue PPA. Applying grounded theory to interviews of 25 practitioners and decision-makers at data-focused corporations, startups, non-profits, and government agencies, we outline the drivers and processes determining whether and how organizations adopt privacy-preserving analytics. Our participants describe how their organizations pursue PPA techniques to preempt regulation and gain an edge over competitors. In particular, these practitioners describe their role in interpreting legal requirements and promises to consumers into technical designs. We explore how this contested process of interpretation---influenced by managerial interests and personal ethics---shapes privacy-preserving analytics and privacy regulation.
Authors: Ryan Steed, Alessandro Acquisti
Ryan Steed, Carnegie Mellon University
![](https://www.usenix.org/sites/default/files/styles/speaker_photo/public/steed_ryan_200x230.jpg?itok=ecUvdUlj)
Ryan Steed is a PhD student at Carnegie Mellon's Heinz College of Information Systems and Public Policy. His research leverages empirical methods to examine privacy and equity in algorithmic systems, especially in relation to tech policy and governance. His current work examines the practical applications and impacts of algorithmic techniques for privacy-preserving analytics.
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author = {Ryan Steed},
title = {{Privacy-Preserving} Analytics on the Ground},
year = {2023},
address = {Santa Clara, CA},
publisher = {USENIX Association},
month = sep
}