Hi! I'm Divya Ramesh.

I am a human-centered AI and design researcher, looking at questions of ethics, governance, and responsibility in AI. I take a holistic approach to designing AI systems that enhance, rather than diminish the agency of underserved communities. To do this, I combine insights from human-computer interaction (HCI) and science and technology studies (STS), iteratively generating designs and socially-engaged critiques of human-AI interactions. I use a wide-range of computational and interpretivist social science methods in my work including crowdsourcing, reinforcement learning from human feedback (RLHF), wizard-of-oz studies, in-depth interviews, and content and discourse analyses. My work speaks to human-computer interaction, responsible and ethical AI, and computer-supported cooperative work (CSCW) research communities.

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. I hold an MS in EE from the University of Southern California, and a BE in ECE from Ramaiah Institute of Technology, India. Between 2014-18, I was a deep learning and computer vision engineer at CloudSight Inc., where I architected the company's human-AI interaction pipeline for real-time image recognition and earned a US patent. I have also had short research stints at Microsoft Research and Google Research.

I am on the job market for 2024-25!


Enhancing economic opportunities for low-income communities amid AI advancements

Each day, over 92 million people from low-income communities come into contact with flawed AI systems in the US alone, risking errors, bias, discrimination, and privacy violations. As an algorithm designer, I think a lot about ways to mitigate these harms and increase economic opportunities.

During my PhD, I investigated to what extent designing human-AI interactions for agency could help mitigate harm to low-income communities. This involved two strands of work: 1) generating human-AI interaction patterns based in theories of HCI and cognitive psychology, and 2) developing socially-engaged critiques of human-AI interaction designs based in STS sensibilities.

Synthesizing computational insights and thick descriptions of low-income individuals’ everyday AI encounters in India and the US, my work establishes that designing AI systems to enhance economic opportunities for low-income communities is simultaneously an interactional design challenge of supporting human agency, and an ecosystem design challenge of ensuring accountability.

My on-going and future work approaches the multifaceted challenge of designing for agency and accountability simultaneously by taking an ecological approach. This includes partnering with communities on the ground and integrating social, historical, and cultural contexts of use into the designs and critiques of human-AI interactions.

Featured Publications

Divya Ramesh, Vaishnav Kameswaran, Ding Wang, Nithya Sambasivan. "How Platform-User Power Relations Shape Algorithmic Accountability: A Case Study of Instant Loan Platforms and Financially Stressed Users in India." In Proceedings of 2022 ACM Conference on Fairness, Accountability and Transparency (FAccT 2022). Seoul, South Korea. [Preprint] [Media Mention]

Divya Ramesh, Caitlin Henning, Nel Escher, Haiyi Zhu, Min Kyung Lee, Nikola Banovic. "Ludification as a Lens for Algorithmic Management: A Case Study of Gig-Workers’ Experiences of Ambiguity in Instacart Work." In Designing Interactive Systems Conference (DIS ’23), July 10–14, 2023, Pittsburgh, PA, USA. [Preprint]

Madison Cutler, Erin Keith, Kleinman Molly, Navarrete Ky, Kaci Pellar, Divya Ramesh, Eric Welsby. "Community Partnerships Playbook: How to Create Equitable Partnerships between Technical and Community Experts." A publication of the University of Michigan Science, Technology, and Public Policy program; Detroit Disability Power; the Detroit Justice Center; and We the People Michigan, February 2024, Ann Arbor, MI, USA. [Playbook]

*Alphabetical ordering of authors

Divya Ramesh, Anthony Liu, Jean Song, Andres Echeverria, Nicholas Waytowich, Walter Lasecki."Yesterday's Reward is Today's Punishment: Contrast Effects in Human Feedback to Reinforcement Learning Agents." In Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020). Auckland, New Zealand. [Preprint] [Talk] [Slides]

Pragnesh Jay Modi Best Student Paper Award

This is a featured list. For some of my other work, please visit my Google Scholar page.

Research Impact

My research has appeared in premier human-computer interaction, AI, and AI ethics 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 first-author work with Google Research has had significant social impact through appearance in media outlets, directly informing Google’s research direction on culturally-inclusive AI and shaping policy. This work ranks in the top 5% of all research outputs scored by Altmetric Explorer for its impact. I have received recognition through the 2023-24 Quad Fellowship, 2024-25 Barbour Scholarship, 2024 CSST Fellowship, and the 2025 Christine Mirzayan Science and Technology Policy Fellowship. I have also mobilized my research findings in externally invited talks, workshops, and panels. Most notably, in June 2023, I was invited to discuss the role of AI and emerging technologies in India-US relationships with President Biden’s top foreign policy officer and National Security Council's Chief of Staff, Curtis Ried. My work has received generous support from the Schmidt Futures Foundation, Rackham Graduate School and Google Research.