Varun Rao is Ph.D. candidate in the Department of Computer Science and the Center for Information Technology Policy at Princeton University. Rao recently sat down with Princeton undergraduate student Tsion Kergo ‘26 for an interview to discuss his research interests, academic background, and the importance of responsible technology in society. Their conversation has been edited for clarity and brevity.
TK: Can you tell us a little bit about your educational and research background?
VR: I’m a Ph.D. student of computer science. I focus on studying the impacts of AI on society in general and on labor platforms in particular. And I study social media platforms, rideshare platforms, and more recently, crowd work.
I study existing platforms and also design platforms to make things better for workers. Before I came to Princeton, I used to be an applied scientist at Amazon in Seattle. Before Amazon, I used to be a master’s student at CMU [Carnegie Mellon University] in Pittsburgh, again studying computer science and machine learning.
TK: What made you decide to transition from your more applied work at Amazon to the more theoretical work that you’re doing now at Princeton? Or, if it’s not theoretical, what made you decide to make that switch?
VR: Yes, for sure. So I guess rephrasing that question to why I did a Ph.D. I used to do a lot of cool machine learning work at Amazon, and it was where I would build and train a lot of machine learning models. But, based on some of the coursework that I took at CMU and my general interest, I realized that not a lot of pressing challenges in computer science have a purely technical solution anymore, and they deserved interdisciplinary approaches. I was interested in bringing perspectives from different disciplines to my research, and I think that was one main reason for the transition to academia. And, I think, my interest in teaching at some point in my career.
TK: Can you tell us a little bit about what you’re currently working on?
VR: In the last year and a half, I’ve been focusing more on rideshare platforms and questions of transparency, discrimination, and, broadly, accountability in these platforms—how opaque algorithmic decisions don’t actually benefit workers. This is part of a broad, collaborative project called the Workers’ Algorithm Observatory, and we’ve built a tool as part of this initiative called “FairFare.”
The goal of the tool is to highlight what the take rate of the platform is. The take rate is defined as the percentage of the customer’s charge that the platform keeps. We built this tool to crowdsource data from workers across the US and actually estimate what that rate is. Some of the data we collected from this tool was helpful in influencing a bill in Colorado. It was Senate Bill 2475—the rideshare transparency bill, one of the first in the nation. That was a big transparency win. It was also really nice to see that the policy impact was evident in a relatively short time, since these policy timelines are typically very long and influenced by many different factors.
So while take rate was one important question, we moved on to studying different types of issues—one around wage loss or wage theft.
[The Center recently wrote about this body of research on the CITP Blog – “Revolutionizing Rideshare: Researchers Develop FairFare App to Empower Workers”]
TK: What can we do to get more young people involved in this kind of interdisciplinary work?
VR: Yeah, I think that’s a good question. I don’t know if I have the perfect answer, but one way is to get involved with researchers who are working on interdisciplinary projects. For example, at Princeton, you could reach out to folks at CITP. They’re tackling lots of pressing problems—from rideshare issues and labor aspects of platforms to content moderation, AI policy, and foundation models— and they’re always open to having undergraduates collaborate with them.
So, I think taking courses offered by CITP faculty would give you a great footing to get started in this space. Another suggestion is to keep in touch with the work of nonprofits and industry in these areas. For undergrads, another opportunity is to look for policy-relevant fellowships. One example is the Google Policy Fellowship. It’s a great opportunity to get familiar with the space, understand the types of problems people work on, and get immersed in the tech policy environment.
TK: Going back to when you were discussing how your data was used in Colorado—can you talk a little bit about the relationship between the research you’re doing here and actual policy? How does it translate to policy, given that you do a lot of work related to that?
VR: Pointing to the exact impact is tricky and nuanced, but I can describe the process we followed. Most of our outreach efforts were with workers and organizers on the ground in Colorado, as well as with think tank partners and nonprofits in the state. It was a policy question that gained a lot of traction in Colorado, so we built our tool in response to the questions and demands of local organizers. Right from the design stage, the tool was guided by a specific policy question that was already being debated.
The second issue we’re studying is what we call algorithmic wage discrimination. This legal term was coined by a legal professor, Veena Dubal, at UC Irvine. It refers to situations where different workers get paid differently for similar work. We’re using some of the data we’ve collected through FairFare to see if there is indeed evidence of differences in pay for similar work and to understand what might be causing this difference.
There was legislation in the pipeline, and our tool was tailored to address that legal question.
TK: Do you have any final thoughts about your work or its impact on society?
VR: Yes – I think we need more work in this space. There’s a lot of potential for technical people—people with a technical background—to actually contribute here. For example, the Center for Democracy and Technology—where I’m a part-time Google Policy Fellow—releases a lot of memos, policy documents, and white papers on topics related to the role of technology in society.
So, yes, definitely try to get involved in any way you can.
Tsion Kergo is a Princeton University junior majoring in Computer Science, pursuing minors in Machine Learning & Statistics and African-American Studies. She works at the Center for Information Technology Policy as a Student Associate, along with fellow undergrad Jason Persaud. Together they are piloting a new series called Meet the Researcher.
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