Issues

Privacy and Security

Information technology lets people learn about one another on a scale previously unimaginable. Information in the wrong hands can be harmful. Scholars on this site consider problems of privacy, fraud, identity, and security posed by the digital age.

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TAP Academics

Sonia Katyal
University of California, Berkeley
Intellectual Property, Privacy and Security, Artificial Intelligence

Deirdre Mulligan
University of California, Berkeley
Privacy and Security, Artificial Intelligence

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TAP Blog

danah boyd Advocates for Responsible Data Science

Microsoft Partner Researcher danah boyd shared insights from her multi-year ethnographic study of the U.S. census. She discussed how the U.S. 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.

TAP Staff Blogger

November 29, 2022

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Upcoming Events

Data Driven: Truckers, Tech, & the New Workplace Surveillance

December 7, 2022, Boston MA

Karen Levy, Data Driven: Truckers, Technology and the New Workplace Surveillance

December 13, 2022,

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Fact Sheets

Social Networking

Social networking websites are places on the Internet where people can connect with those who share their interests. Additionally, they can function as economic “platforms” that serve different groups of many users, including consumers, advertisers, game developers, and others.

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Quote

California Passes Bill Aimed at Making the Internet Safer for Kids

“The bill's [California Age-Appropriate Design Code Act (AB 2273)] requirements that platforms seek to assess users’ ages to offer them appropriate content, while well intentioned, could be overly intrusive and undermine efforts to provide these users more privacy.” — Eric Goldman, Professor of Law, Santa Clara University

Eric Goldman
CNBC
August 30, 2022

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Algorithmic Bias? An Empirical Study of Apparent Gender-Based Discrimination in the Display of STEM Career Ads

The use of algorithms to make decisions can lead to bias; one algorithm displayed a “gender neutral” ad to more men than women. The algorithm was designed to be cost-effective; because advertisers pay more to display ads to young women, the ad was shown to fewer women.

By: Catherine Tucker, Anja Lambrecht

March 9, 2018

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