Public Interest Technology Initiative Announces 2025-26 PIT Faculty Fellows in Responsible AI
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The Public Interest Technology (PIT) Initiative at UMass has announced the recipients of its 2025-26 Faculty Fellowship, including Manning College of Information and Computer Sciences (CICS) Undergraduate Program Director and Associate Professor Andrew Lan and Center for Data Science and Artificial Intelligence Research Fellow Virginia Partridge. Fellows will receive seed funding to support research, scholarly writing, or curriculum development on the theme of Responsible AI – how we create, use, and manage AI responsibly to promote the common good and public interest.
Throughout 2025-26, the PIT Fellows will meet monthly with Ethan Zuckerman, Fran Berman, and Donna Baron from the PIT leadership team to present and discuss their work in progress. They will work across campus and with the broader PIT network to advance PIT and their projects. They will also work together to develop a visiting speaker series, inviting outside speakers to campus for public events on Responsible AI.
Fellows will explore PIT-related questions and integrative solutions by:
- Addressing a complex problem with public interest impacts (privacy, safety, security, equity, sustainability, ethical behavior, etc.)
- Engaging the responsible use of artificial intelligence
- Reducing cultural, economic, and other societal disparities
The following faculty members and their respective projects and teams were selected for this year’s fellowship:
Project Lead: Torrey Trust (College of Education)
This project critically analyzes AI-generated lessons for Advanced Placement (AP) U.S. History, Government and Politics, and African American Studies standards to identify what role, if any, AI should play in aiding teachers’ instructional design process. Based on their findings, they plan to create an open educational resource to help teachers make informed decisions about using GenAI technologies for teaching and learning. Project member: Robert Maloy (College of Education)
Project Lead: Chaitra Gopalappa (College of Engineering)
The goal of this project is to integrate social determinants of health (SDH) into epidemic decision-analytic tools, for joint evaluation of structural, behavioral, and pharmaceutical interventions to inform public health strategies. This PIT project will lay the groundwork for a research plan to combine unstructured text data with aggregated-level quantitative survey data to infer mechanistics between SDH and HIV risk behaviors, input to an interpretable dynamic simulation for epidemiological validation. Project member: Mohammad Derakhshi (College of Engineering)
Project Lead: Joe Pater (College of Humanities and Fine Arts)
This project is developing a method for automatic transcription into the International Phonetic Alphabet, which leverages the technology underlying modern speech recognition systems. Project member: Virginia Partridge (Manning CICS)
Project Lead: Youngbin Kwak (College of Natural Sciences)
The overarching goal of this research program is to advance personalized and culturally aligned human-AI collaboration. To this end, the work investigates human-AI collaboration across cultures, examining how trust, communication, and decision-making styles shape AI-assisted interactions. Project member: Mohammad Atari (College of Natural Sciences)
College of Social and Behavioral Sciences
Project Lead: Douglas Rice (College of Social and Behavioral Sciences)
This project utilizes a dual-pronged approach to improve the interdisciplinary data analytics and computational social science curriculum by, first, integrating key considerations–both practical and ethical–in the use of AI tools throughout the curriculum and, second, introducing a new graduate course on responsible AI for social scientists. Project member: Omer Yalcin (College of Social and Behavioral Sciences)
Project Lead: Monideepa Tarafdar (Isenberg School of Management)
Human-Generative AI collaboration (HGAI) is defined as humans and GAI applications (e.g., ChatGPT) working together to accomplish a wide variety of knowledge-based tasks. This project addresses the research question: “How can humans maintain their cognitive primacy in HGAI collaboration?”
Project Lead: Zhenhua Liu (School of Public Health)
This project was originally inspired by a high-school student’s curiosity about AI’s accuracy and seeks to explore how AI can be leveraged to provide accurate dietary recommendations for public health. Project member: Andrew Lan (Manning CICS)
This story was originally published by the UMass Amherst Office of News & Media Relations.
