About DESIGN JUSTICE AI

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 at UConn).

Our shared focus is the rapid diffusion of so-called generative AI–machine learning technologies that simulate human languages, communication, arts, and cultures through the statistical modeling of vast troves of “scraped” internet data. Our Global Humanities Institute is inspired by the work of the Design Justice Network, a hub for people committed to embodying and practicing the Design Justice Network Principles. Longstanding DJN member Sasha Costanza-Chock (former fellow of the Berkman-Klein Center for Internet & Society and Head of Research for OneProject.org) wrote Design Justice: Community-Led Practices to Build the Worlds We Need (2020) to advance community-led design practices. Our approach to these topics combines interdisciplinary critique, public humanities, and best practices from data science and digital humanities (DH), with collaborative research that strives to center people and cultures that have been marginalized by design processes. 

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.

Through publication of blogs, research templates, interviews, experimental datasets, recorded lectures, pedagogical practices, and peer-reviewed articles and special issues, our institute will share resources that help to diffuse these critical methods. In doing so, we hope to help any campus to develop nuanced understanding of and engagement with “generative AI,” including robust pedagogical strategies, and the potential for community-centered research projects informed by design justice principles.