Latanya Sweeney is a Professor of Government and Technology in Residence at Harvard University, formerly the Chief Technology Officer at the U.S. Federal Trade Commission (FTC)., and the founding Director of the Data Privacy Lab at Harvard. Her work was first to demonstrate discrimination in online algorithms and founded the newly emerging area known as algorithmic fairness. More recently, her work with Ji Su Yoo and Jinyan Zang was first to demonstrate vulnerabilities in voter websites during the 2016 election.
In 2001, Sweeney became director and founder of the Data Privacy Lab, at Carnegie Mellon University. She was a member of the Program Committee for Modeling Decisions for Artificial Intelligence (MDAI) in 2005. In 2004, she founded the Journal of Privacy Technology, later becoming the editor-in-chief in 2006.
In her PhD dissertation at MIT (Computational Disclosure Control: Theory and Practice), Sweeney examines various computational methodologies for the secure dissemination of anonymous data without revealing any identifying, or potentially identifying, information. She proposes novel approaches for secure data disclosure, defining and describing null-map, k-map and wrong-map models of protection. Sweeney then critiques and compares four electronic data-based computational programs on their capacity to protect private information. The systems evaluated are her Scrub System, her Datafly II System, Statistics Netherlands’ u-Argus System, and her k-Similar algorithm – which she concludes as the most effective system in minimizing privacy risks. Prior to her dissertation, Sweeney has already been published numerous times, in topics pertaining to healthcare data security, and she has also completed a Masters Thesis at MIT and an ALB Thesis at Harvard. Currently, Sweeney is a prominent data security researcher and continues ongoing work to advance this field.