Interview with Dora Zhao
Dora completed her BS and MS degree from
Princeton University, majoring in Computer
Science. She has strong interest and experience in the areas of AI ethics, computer vision, and
Can you tell us a little bit about yourself (your background, your hometown, your school)?
My name is Dora, and I originally grew up in a small suburb outside of Philadelphia. I did my undergrad at Princeton where I studied computer science with minors in statistics / machine learning and Asian American Studies. After, I completed my MSE in computer science at Princeton where I focused on AI/ML and HCI.
How did you gain an interest in CS, and what were your first experiences with CS?
I was not always interested in CS and actually started Princeton with the intent on majoring in public policy. However, after hearing Professor Ruha Benjamin’s lecture on the intersection of race and technology, I became compelled to dive deeper into computer science to do work that combat biases in technical systems. While I enjoyed
the intro sequence in computer science during undergrad, my first truly positive experience with CS was when I got to do my junior independent research with Professor Olga Russakovsky.
You seem to be interested in AI ethics, computer vision, and human-computer interaction. Can you please share more about that?
I first was introduced to the field when I read Joy Buolamwini and Timnit Gebru’s foundational work “Gender Shades,” which found intersectional disparities in commercial facial recognition technology. From there I was spurred to pursue research on computer vision and fairness. At Princeton, I was lucky to work in the Visual AI Lab with Professor Olga Russakovsky. During my time at the lab, I worked on projects related to racial biases in vision + language systems and human-in-the-loop techniques for uncovering visual biases. Although my work has been focused on computer vision, I became more interested in human-computer interaction since I felt that much of the work being done from the computer science-side of AI ethics felt almost divorced from people being impacted from these technologies. Thus, my interests are in combining qualitative and quantitative techniques not only to understand how people (not just technologists) think about fairness but also to attempt to build systems that reflect these values.
How can we avoid “unfairness” and “bias” to be embedded in AI?
“Unfairness” and “bias” in AI are products of the systematic inequities present in our society. To truly make fair or unbiased AI, we need to address these issues not just at the technical level but also through community organizing and advocacy. However, as computer scientists within the technical sphere, we can mitigate the presence of biases by (1) acknowledging that tech is not neutral; (2) creating more diverse spaces both in terms of the technologists that make AI but also by engaging with the community that will be impacted by these AI systems; and (3) being cognizant of how bias can appear across any stage of the ML pipeline and being proactive in trying to mitigate these biases.
What are you pursuing professionally after completion of MS degree from Princeton?
Since graduating from Princeton in June, I started working at Sony AI, a research lab at Sony, where I am an AI engineer on their AI ethics team.
What advice would you give to female students concerned about the gender disparities in CS?
First, I cannot underscore the importance of finding a strong community of people to support you as well as to both find and nurture spaces where you feel comfortable.
Second, one of the most reassuring things that I learned from my advisor is that “genius” is a myth. In CS and STEM more broadly, we often think that people must be
“innately brilliant” to succeed, a misconception that often discourages women and other underrepresented groups from pursuing the field.
What are your interests, other than CS?
Outside of my research, I am interested in sports and reading. I played Ultimate Frisbee in college and am a fan of the Tottenham Hotspurs, a Premier League team. For reading, I enjoy Asian American literature, particularly short story anthologies.
What are your interests, other than CS?
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