Authors: Ryan Burns*, University of Calgary, Jim Thatcher, University of Washington - Tacoma, Craig Dalton, Hofstra University
Topics: Geographic Information Science and Systems, Geographic Theory, Social Theory
Keywords: critical geoAI, digital geographies, critical GIS, artificial intelligence, critical data studies
Session Type: Virtual Paper
Start / End Time: 11:10 AM / 12:25 PM
Room: Virtual 47
Presentation File: No File Uploaded
Despite a potential intellectual lineage from critical GIS, recent critical work on geographic artificial intelligence (geoAI) has largely bypassed those early debates. This may be partly due to the broader non-geographic research agenda from which AI stems, and also partly due to the emergence of newer theoretical frameworks such as critical data studies, data feminism, and digital geographies writ large. Still, it’s important to ask the place of criticality within an emergent "critical geoAI": to what extent, if any, are conceptual debts owed to critical GIS?
We argue that critical GIS raised two contentions for the broader digital geographies research agenda that increasingly informs critical geoAI work. The first is that early research has valorized inquiries of a conceptual orientation, drawing on the humanistic tradition of critique. Productive as this work has been, geographers have engaged less frequently with work that mobilizes technical skills and languages. The shape of critical geoAI to come seems to be once more caught in the tension between social theory and computation by which early critical GIS work was dismissed. Second, geographers must ask the precise meaning of the term "critical" in an emergent "critical geoAI". Aside from "critical thinking" writ large, stronger connections to the limits of representation and reason within western thinking, such as the Frankfurt School’s critical social theory, sublatern and indigenous ontologies, critical race theory, and queer and de-colonial thinking offer directions for rethinking the possible. Taken together, we argue these steps will produce a more robust and inclusive critical geoAI.