I am an empirical computer scientist, looking at questions of AI and economic inequality. My work falls under Responsible AI & Computing, and spans human-computer interaction (HCI), applied machine learning, and science & technology studies (STS).
I envision AI as a vehicle for creating equitable economic opportunities in society. To support this goal, I develop sociotechnical approaches for AI innovation. This includes: 1) Designing human-AI interaction models based on the lived experiences of low income communities, 2) Creating situated accountability infrastructures for AI projects, and 3) Expanding the methodological toolkit of responsible AI to involve community-centered perspectives. My research combines in-depth qualitative case studies (i.e., with low income communities), and quantitative & computational approaches (i.e., machine learning, reinforcement learning and crowdsourcing) with theories from critical social sciences.
I am on the job market for 2024-25! I am exploring roles within academic departments, think tanks, and/or corporate teams, where interdisciplinary thinking is sought as a means to bridge technology design and public policy.
I expect to graduate with a PhD in Computer Science and Engineering and a certificate in Science, Technology, and Public Policy from the University of Michigan, Ann Arbor in 2025. My dissertation develops a socio-economically situated framework for algorithmic accountability by drawing on the experiences of financially constrained communities and AI-based economic inclusion technologies in India and the US.
My work has appeared in premier HCI and AI venues such as ACM CHI, FAccT, DIS, TOCHI and AAMAS, where I have received a Best Paper nomination, and a Pragnesh Jay Modi Best Student Paper award. My work has contributed to public conversations via popular media outlets such as CNBC TV18 and Techcrunch Perceptron, one of which shaped the course of policy outcomes for Google in 2023. I was recognized as a Quad Fellow by the governments of Australia, India, Japan and the US for 2023-24, and as a Barbour Scholar by the University of Michigan for 2024-25. My work has received generous support from the Schmidt Futures Foundation, Google, and the Rackham Graduate School.
Before starting my PhD, I led the R&D efforts in Computer Vision at CloudSight Inc. At Cloudsight, I architected the company's first human-AI interaction pipeline for analyzing visual content in real-time, powering many visual recognition apps including the award-winning accessibility app, TapTapSee.
Please feel free to reach out to me by email if you would like to hear more about my work! My pronouns are she/her.
*Alphabetical ordering of authors
Pragnesh Jay Modi Best Student Paper Award