Latanya Sweeney, Ph.D.
Prior success
Historically, I have made numerous cross-disciplinary contributions to privacy technology having significant scientific influence and real-world impact. Scientific American profiled my earlier work (profile). My greatest impact has been in medical privacy ( medical informatics, policy and law). My most cited statistic is "87% of the U.S. population is uniquely identified by {date of birth, gender, postal code}" [cite]. My most cited academic work is k-anonymity. An index of my work, across disciplines and scientific areas, appears here and a brief summary appears below. Also, here is my bio and CV.
Timeline
In my earliest academic work, I created systems that automatically learn strategic and sensitive information from data, and the converse, I created systems that control what can be learned. Most often, this related personal identity to seemingly innocents facts (re-identification and de-identification). The broader goal is to create systems that give guarantees that identity cannot be learned ("anonymity") while still making sure the results remain useful.
In the 2000's, I worked with computer scientists who pioneered privacy-invasive technologies and scholars who designed related policy, believing these groups were in the best positions to solve privacy-technology clashes through design. My approach was to identify a privacy-technology clash within a community, formulate a privacy problem statement, and then offer a solution to the problem as an exemplar to seed privacy-preserving work within the originating community. In computer science, these were: medical informatics, database security, surveillance, vision, and biometrics. Related communities outside computer science were: policy and law, and public education.
As part of an extended sabbatical from Carnegie Mellon, I began my "privacy rethink" at Harvard in 2009. The goal is to replace the 3 historical pillars of privacy (consent, notice, and de-identification) with new technology-powered mechanisms that jointly provide a privacy fabric appropriate for today's setting. We want society to reap the benefits of emerging technologies while enjoying privacy protection. Testbeds for these new systems (MyDataCan, theDataMap, and more) are rolling out over the next months, so stay tuned.
Keywords:
Gov 2.0, technology policy, learning,
data anonymity, privacy technology, re-identification, data linkage
Academic Positions
Corporate Affiliations
No issued licenses limit my access to these technologies
for academic purposes.
Research Interest
View old
Research Projects
or see old
Research Artifacts.
Contact Information for Latanya Sweeney
Fall 2012.