Critical AI Research and Education (CAIRE) Lab

We aim to contribute to both established and emerging fields such as critical data, platform, and algorithm studies, critical AI, and justice informatics. Our current members include undergraduates, graduate students, and faculty members with backgrounds in human-computer interaction, comparative literature, sociology, philosophy, library and information science, and beyond.

As a successor to the HCC+D Lab, we continue the legacy of critical data studies research and scholarship. The term “critical” in our work signifies a deep, systematic, and reflexive critique of the entrenched binaries and hierarchies that shape our understanding of the world. This includes dismantling the false dichotomies between the ‘natural’ and ‘built’ environments, society and technology, and science and ideology, among others. Our critical approach also compels us to hold ourselves accountable for the genealogies and effects of the advanced technologies our societies envision, create, and enforce. Central to our mission are questions about who benefits and who is harmed by these technologies, how our engagement with technology affects the environment, and how the complex transnational AI supply chains directly and indirectly intensify long-standing interlocking systems of oppression. In other words, we explore what kinds of worlds and futures these technologies make possible or foreclose and for whom they are designed to benefit.

What the term “critical” in our approach does not mean is engaging in abstract critique devoid of questions of praxis or interactions with our communities. We are committed to generating tangible responses to the multiple crises in which AI plays a central role. Our work is informed by a dynamic combination of theories and methods, including transnational, post-colonial, queer, Black, Indigenous, East European, technoscientific, and disability feminisms, race and gender theories, science and technology studies, discourse and literary analysis and historical analysis. These perspectives shape our understanding of technology and the world, particularly around the concept we call “AI abolition.” Our theoretical and empirical work uses (primarily) critical qualitative methodologies to contribute meaningfully to global conversations challenging AI development.