Design Justice AI is a Global Humanities Institute sponsored by the Consortium of Humanities Centers and Institutes and the Mellon Foundation. The Institute is being coordinated by Critical AI @ Rutgers in collaboration with the Rutgers Center for Cultural Analysis, the Center for Advancement of Scholarship at the University of Pretoria, the Humanities Research Centre at ANU, and the Humanities Institute at the University of Connecticut. The Institute will explore community-centered, humanistic, and interdisciplinary engagement of “Generative AI” (the statistical modeling of human languages, communication, arts, and cultures).

CALL FOR EARLY CAREER PARTICIPANTS: GLOBAL HUMANITIES INSTITUTE 2024

Design Justice AI is a collaboration between Colin Jager (Director of the Center for Cultural Analysis at Rutgers) and Lead PI Lauren M. E. Goodlad (Distinguished Professor of English & Comparative Literature, Chair of the Critical AI @ Rutgers initiative, and editor of Critical AI) in conjunction with co-PIs at each of the partnering centers: Matthew Stone (Professor and Chair of Computer Science at Rutgers), Katherine Bode (Professor of Literary and Textual Studies at ANU), Vukosi Marivate (Chair of Data Science at the University of Pretoria and lead for the Data Science for Social Impact Group), and Michael P. Lynch (Board of Trustees Distinguished Professor of Philosophy and former director of the Humanities Institute).

Our Design Justice AI institute will cross disciplinary divides and reach out to affected communities as we foster creative thinking, model new forms of research, and produce resources for scholars and the general public. As commercial technologies aim to simulate and mediate human expression and creativity at an unprecedented scale, our Global Humanities Institute will seek interdisciplinary standpoints and fertile alliances that produce knowledge “from below”: through creative collaborations between researchers, students, and community partners. Our goal is not only to “critique” these fast-developing technologies, but also to envision ML systems that work in the public interest: i.e., safe, accountable, and inclusive systems that are receptive to many voices.  

A detailed description of the project is availabe on Critical AI @ Rutgers website.