Science Talks with Bailey Kacsmar: Human-Centred Privacy in a Digital Society

Data isn't just a collection of numbers—it's something deeply connected to real people, whose lives can be affected by how companies use their information. Privacy-enhancing technologies (PETs) are designed to mitigate privacy risks in digital systems. When applied to data analysis, PETs can help strike a balance between protecting individual privacy rights and supporting companies' economic interests. However, for PETs to truly improve the landscape of corporate data-sharing practices, they must also foster trust among those whose data is being shared.  Hear from Bailey Kacsmar on the development of privacy enhanced data analysis techniques, the implications on user perspectives of the space, and the ongoing work towards the development of accessible human-centred private data analysis techniques and protocols.

Space is limited. Registration will close when the event reaches capacity, or on April 22, 2025.

Speaker Info 

Bailey Kacsmar’s research centers on the privacy implications and potential of machine learning and artificial intelligence. She develops human-centred privacy technology through the parallel study of technical solutions for private data analysis alongside the corresponding user perceptions, concerns, and comprehension of these developments. Prior to joining the University of Alberta, she received her PhD in Computer Science and her Masters of Mathematics, both from the University of Waterloo.