RDS Scholars

Ethicality of Generative Artificial Intelligence in Research

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

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?

A Meta-Framework for Frameworks

Students: Elda Solomon, Alisha Sharma

Framework for Archival Work and Digitization

Students: Lillian Carlson, Aishwarya Khrishnamoorthy, Celeste Stokan

Advancing Public Health: Constructing a Response AI Usage Tool for Public Health Education

Students: Emma Camps, Simon Fisher, Fernando Seanez

By: Emily Durning

We are excited to introduce the newest members of the Responsible Data Science (RDS) Student Scholars Program!

This program provides students with opportunities to engage in interdisciplinary training, collaborative projects, and responsible data science practices that connect classroom learning with real-world challenges.

Read more about the program.

The Responsible Data Science (RDS) Student Scholars Program at the University of Pittsburgh is bringing together an interdisciplinary group of undergraduates to explore how data and technology can be harnessed responsibly for the benefit of society.