Privacy
While privacy is not one of my primary research interests, I do have some past and ongoing projects on it, particularly with regards to fair privacy and AI to help people make privacy-related decisions. Our fair privacy paper examines what is involved in making sure that privacy guarantees are provided in a fair and equitable manner, that vulnerable people are not at greater risk of privacy failures 2018. Privacy for All: Ensuring Fair and Equitable Privacy Protections. In Proceedings of the 1st Conference on Fairness, Accountability and Transparency (FAT* 2018). PMLR, Proceedings of Machine Learning Research 81:35–47. Acceptance rate: 24%. Cited 104 times. Cited 78 times. 2018. Do Different Groups Have Comparable Privacy Tradeoffs?. In Moving Beyond a ‘One-Size Fits All’ Approach: Exploring Individual Differences in Privacy, a workshop at CHI 2018. NSF PAR 10222636. Cited 4 times. Cited 4 times. This line of work examines how people make privacy decisions and how we might build tools that support them in that process. 2021. Privacy as a Planned Behavior: Effects of Situational Factors on Privacy Perceptions and Plans. In Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization (UMAP ’21). ACM. DOI 10.1145/3450613.3456829. arXiv:2104.11847 [cs.SI]. NSF PAR 10223377. Acceptance rate: 23%. Cited 23 times. Cited 15 times.Fair Privacy
Privacy Decision-Making