Privacy, Antitrust, and Algorithmic Bias; Working at the Intersections with Caitlin Chin [S3E26]

Tech Policy Grind

Welcome back to the Tech Policy Grind! Today, Reema chats with Caitlin Chin, a Class 4 Fellow at the Foundry and a a fellow at the Center for Strategic and International Studies (CSIS), on her work at the intersection of privacy, antitrust, and algorithmic bias.

At CSIS, Caitlin researches technology regulation in the United States and abroad. She previously worked as a research analyst at the Brookings Institution, where her projects centered around U.S. federal and state legislation related to information privacy, antitrust, and algorithmic bias. At Brookings, Chin coauthored “Bridging the gaps: A path forward to federal privacy legislation” (with Cameron Kerry, John Morris Jr., and Nicol Turner Lee), which put forward a comprehensive framework for national commercial privacy standards in the United States.

In addition, she has published over two dozen other reports or commentaries on public policy issues including “Addressing Big Tech’s power over speech” (with Bill Baer) and “Why Democrats and Republicans would benefit from hate crime protections for Asian Americans.”

She’s also spoken on C-SPAN, WOSU/NPR, and France 24, and her work has been cited by the Washington Post, the Wall Street Journal, and the Future of Privacy Forum, among other organizations. She has a BA in government and Spanish from the University of Maryland and an MPP from Georgetown University’s McCourt School of Public Policy.

Her master’s thesis, “Examining national privacy laws in the context of international trade,” won a student paper award at the 48th Research Conference on Communications, Information, and Internet Policy (TPRC48) in 2020. She was also a recipient of Public Knowledge’s 20/20 Visionaries award in 2021.

Coming soon from the Foundry: keep an eye out for the next round of applications to become a Foundry Fellow!

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