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Funded Incubator Projects

The Hammers and the Nails: Connecting Data Scientists with Domain Experts

Co-PIs: Ahmed Aziz Ezzat, Industrial and Systems Engineering & Ryan Sills, Materials Science and Engineering

Abstract

The goal of this incubation workshop is to bring together data scientists (“hammers”) and domain experts (“nails”) to spur novel research collaborations. The concept underlying the workshop structure is that often these collaborations do not take root because (1) data scientists are not fully aware of domain problems that can be addressed through an AI/cyber infrastructure lens (CI) and/or (2) domain experts are not fully aware of AI/CI methods/tools available to aid in scientific analysis and discovery. This workshop is designed to overcome these barriers to stimulate novel research and mobilize data and domain scientists to pursue funding opportunities.

 

 

 

Research Libraries in the Age of Chatbots: Building Critical AI Literacies and Labs for Student and Faculty Researchers

Project Team

  • Francesca Gianetti, New Brunswick Libraries (lead PI)
  • Lauren M. E. Goodlad, English/Comparative Literature and Critical AI @ Rutgers (co-PI)
  • Matthew Stone, Computer Science (co-PI)
  • Joseph Deodato, Rutgers University Libraries (faculty collaborator)

Abstract

Research Libraries in the Age of Chatbots will center partly around a visit from Inioluwa Deborah Raji (University of Toronto, Fellow, Mozilla Foundation) a scholar and researcher who will work with librarians and interdisciplinary faculty and students to explore the impact of generative artificial intelligence in research, education, and college writing. By foregrounding the issues of misinformation, bias, labor, and research integrity, we will work at the forefront of what research libraries can do to provide resources, best practices, and published work on this emerging challenge for university scholars and teachers across disciplines. We will partner with the NEH- and Mellon-funded Design Justice Labs (lead PI Lauren Goodlad, English/Critical AI @ Rutgers, and co-PI Matthew Stone, Computer Science) to plan and organize this workshop. The workshop will explore the latest work in the probing and auditing of large language models as a basis for critical AI literacy and knowledge production as well as a strategy for educating students. The outputs of this workshop will be a white paper or peer-reviewed publication and a roadmap for the implementation of tutorials, modules, and other curriculum to develop best practices for critical AI literacy in its multiple intersections with faculty and student-led research.