SI 2020 Methods Lectures - Differential Privacy for Economists
James M. Poterba, Organizer
July 17, 2020
Supported by the Alfred P. Sloan Foundation
on Zoom.us
| Friday, July 17 | ||
| 1:00pm | Differential Privacy for Economists | |
| 1:30pm |
Daniel Goroff, Alfred P. Sloan Foundation Differential Privacy: Observations for Economists (background paper) (slides) (video) |
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| 1:45pm |
Daniel Kifer, Pennsylvania State University Introduction to Differential Privacy (slides) (video) |
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| 2:30pm |
Ian Schmutte, University of Georgia Decisions with Privacy-Protected Data (slides) (background paper) (video) |
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| 3:30pm |
Daniel Kifer, Pennsylvania State University Basic Statistics with Differential Privacy (slides) (video) |
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| 4:15pm |
Ian Schmutte, University of Georgia Formal Privacy in Census Data (slides) (video) |
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| 5:00 pm |
Frauke Kreuter, University of Maryland Implications of Data Privacy Concerns for Empirical Social Science (background paper) (video) |
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| 6:00pm | The extent to which individual responses to household surveys are protected from discovery by outside parties depends on the summary information released by the collecting government or firm, and on the broader data environment. Rapid decline in the cost of computation, along with a rising number of publicly available data sets, often from private vendors, have increased the risk that a determined party could combine public and private data resources and identify the survey responses of small groups or even individual respondents. Differential privacy is a tool for assessing the trade-off between releasing more granular information based on survey responses and protecting the privacy of survey respondents. These lectures offer an introduction to differential privacy along with examples of its application in settings that range from the collection of data on a small group to the US census. | |