Spotlight: SCAI Graduate Affiliate Jessie Cao on Data Control

Hi Jessie! Tell us about your research. What problem are you working on, and why does it matter?

My research lies at the intersection of human-computer interaction (HCI) and usable security and privacy. I study how security and privacy transparency and control, or their absence, shape whether and how people adopt, use, and trust emerging data-intensive consumer technologies. I focus particularly on AI systems with opaque data practices and risks that vary across contexts. Through mixed-methods research, I aim to develop usable and trustworthy transparency tools, frameworks, and evaluation methods that address the security and privacy needs of diverse stakeholders, including end users, domain experts, and other actors across the AI ecosystem.

Outside of your research, what is something about you that people might be surprised to learn?

Outside of research, I love being a cat parent (YAY, I have two cats!). Whenever I travel, I send them postcards.

Why did you decide to join the Society-Centered AI IGEC?

I joined the Society-Centered AI IGEC because it closely aligns with my research interests that span computer science, human behavior, technology ethics, and policy. I enjoyed multiple SCAI events such as the annual conference on SCAI, where I got the chance to present our research and converse with people who shared interests.

Where do you hope your research goes next, and what kind of impact would you like it to have?

I hope to translate what we learn about people’s needs into privacy information and controls that we can design, test, and improve in everyday AI use. This could include helping people understand when their information is saved or reused and giving them more control across different conversations and contexts. I’m also interested in connecting users’ expectations with practitioners’ technical capabilities, organizational practices, and legal responsibilities. Ultimately, I want my research to offer practical guidance for AI developers and evidence that informs policy, helping people make informed choices about AI and have those choices respected.

What is one question about Society-Centered AI that you find yourself thinking about a lot right now?

How can we give people meaningful control over their data in AI systems without placing the burden of protecting their privacy entirely on them?