Public Interest Technology Initiative Announces 2025-26 PIT Faculty Fellows in Responsible AI

Clockwise from top left: Chaitra Gopalappa, Mohammad Derakhshi, Youngbin Kwak, Mohammad Atari, Zhenhau Liu, Virginia Partridge, Torrey Trust, Robert Maloy, Monideepa Tarafdar, Omer Yalcin, Douglas Rice, Andrew Lan and Joe Pater (center)-.

The Public Interest Technology (PIT) Initiative at UMass has announced the recipients of its 2025-26 Faculty Fellowship. 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:

College of Education
Project Lead: Torrey Trust, Professor, Teacher Education and School Improvement

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 Engineering
Project Lead: Chaitra Gopalappa, Associate Professor, Mechanical and Industrial 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 Humanities and Fine Arts and College of Information and Computer Sciences
Project Lead: Joe Pater, Professor of Linguistics and Co-Director of the Computational Phonology Laboratory

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.

College of Natural Sciences
Project Lead: Youngbin Kwak, Associate Professor, Psychological and Brain Science

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 Social and Behavioral Sciences
Project Lead: Douglas Rice, Associate Professor of Political Science

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.

Isenberg School of Management
Project Lead: Monideepa Tarafdar, Charles J. Dockendorff Endowed Professor of Operations and Information 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?"

School of Public Health & Health Sciences and the College of Information and Computer Sciences
Project Lead: Zhenhua Liu, Professor of Nutrition

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.