News

Where Research Meets Reality: HAIL-MCSI Summer Researchers Tackle AI, Sustainability, and the Future of Learning

At a recent lunch gathering hosted by HAIL (the Hub for AI and Data Science Leadership) and the Mascaro Center for Sustainable Innovation, this summer’s MCSI research cohort sat down with faculty advisors and industry-connected guests to share project updates and dig into one of the most pressing questions in higher education today: What does it mean to learn in the age of AI?

Leading Together in the Era of AI: Improving Human Judgment Through Connection

By: Michael Colaresi, PhD | Director, Hub for AI and Data Science Leadership

I know I'm not alone in finding AI dazzling, dizzying, and depressing—sometimes all at once. But sitting in front of my screen, just me against a billion-parameter model and a suite of surveillance tools with a profit motive, the work can feel lonely and the decisions daunting.

HAIL Graduate Awardees Spotlight: Rose Gatfield-Jeffries

Kicking off our HAIL Graduate Awardees Spotlight Series, we have Rose Gatfield-Jeffries (she/her) from the History and Philosophy of Science Department within the Dietrich School of Arts and Sciences. Gatfield-Jeffries, who has spent three years at Pitt and is beginning her dissertation, is interested in the use of AI in scientific research. Specifically, she uses epistemological (differentiating between justified belief or opinion) and ethical lenses when analyzing this use.

RDS Scholars Spotlight: Ethics of Gen AI Intelligence in Research

Students: Akarshana Rajesh, Leila Pridotkas, Sanvi Gandikota, Julian Reinstein

RDS Scholars Spotlight: Framework for Governing Repository Data in AI Training

Students: Tony Hoang, Rachel Amanor, Ashlee Wood

A new problem that has arisen with AI is deciding what data to use when training new models. The more information and data that a model is trained on, and the more diverse that information is, the more accurate and reliable the model will be. When looking at the problem from this perspective only, it does not sound like much of a problem — use as much data as possible to train a model. But is anything ever that simple?

RDS Scholars Spotlight: A Meta-Framework for Frameworks

Students: Elda Solomon, Alisha Sharma

What Does It Really Mean to Prepare Students for an AI World?

What can I teach learners in my classes that will help them lead in the age of AI?

Building Digital Leaders from Skills to Competencies to Attributes

One of the most common mistakes institutions make when approaching AI education is treating it as a single thing to be delivered — a workshop, a module, a certification, a tool. Attend the session, check the box, move on. Provide it and it will be used. 

How Digital Leadership Prepares Pitt for the Age of AI

"AI literacy." "AI fluency." These terms are (and have been) everywhere in higher education. These terms appear in strategic plans, faculty development programs, and institutional reports. And while they point at something real and important, they can also feel frustratingly abstract. What does it actually mean to be "AI literate"? How do you know when you've achieved it?

RDS Scholars Spotlight: Frameworks for Archival Work and Digitization

Students: Lillian Carlson, Aishwarya Khrishnamoorthy, Celeste Stokan

HAIL Participatory Approaches in Data Brownbag Series: Community Engagement in Public Health

Our biggest installment yet of the Participatory Approaches to Data Community of Practice Brownbag Series was held last month in the University Center for Social and Urban Research. Dr. Tina Ndoh, Gabby Gray, and Mariska Goswami built upon the existing conversations within our community of practice by honing in on public health applications of participatory and community engaged work.

RDS Scholars Spotlight: Building AI Frameworks for Public Health Education

Students: Emma Camps, Simon Fisher, Fernando Seanez

HAIL Participatory Approaches in Data Brownbag Series: Data Sharing Practices

HAIL Participatory Approaches in Data Brownbag Series

Welcoming the Inaugural Cohort of HAIL Graduate Student Awardees

We are pleased to introduce the newest members of the HAIL Graduate Student Awardees Program!

Through this program, the following students have the opportunity to explore the questions: "What does responsible data and AI use and development entail in different disciplines or professions?" and "What individual actions can be taken to practice responsible data and AI use and development?"

More information about the program is available here.

A Look at the Growth of Pitt's Data Science and AI Forum

The DataSci+AI Forum brought together the University of Pittsburgh's work at the forefront of promoting responsible AI and data science practices. Building on Pitt Data Science Day in 2025, the 2026 edition drew a substantially larger audience and reflected broader engagement both within and beyond the University of Pittsburgh. We were interested in comparing the two years and it shows that the AI and Data Science Forum is increasing in scale and strengthening its ability to bring together a wider community around data science and artificial intelligence.