Artificial Intelligence and Machine Learning (AI/ML) are becoming increasingly influential in our daily lives, guiding and shaping the social structures, economies, and political systems in which we live. From email filters to algorithmically powered legal decisions, these technologies have the potential to offer nearly $16 trillion to the global economy in the next 10 years. Yet, the development and application of AI/ML often unfold with limited input from those outside computational fields. While important scholarship on AI/ML has started to emerge from digital geographies, less attention has been given to its potentialities and ramifications in relation to place and space. In addition, the role of qualitative research within the larger onto-epistemological landscape of AI/ML has remained largely overlooked.
This paper session is designed to begin a conversation about the geographies, ethics, and practices of AI/ML in a broad way. Given geography’s long history of analytical and operational insights with other technologies, including GIS, what does growing interest in the field of AI/ML mean for geography, and what specifically can geographers contribute to these emerging technologies and fields?
These questions sit at the center of this paper session. Papers in it might address the following topics:
• What can the development of GIS/remote sensing within and beyond the context of geography show us about the likely paths AI/ML will take in and through our discipline?
• Can there be a revolutionary or counterhegemonic AI? If so, what might that AI look like? If not, are there emancipatory possibilities with this new technology?
• Can there be a publicly engaged AI? If so, what infrastructure, practices, and norms must be in place to support this kind of AI? If not, how do grassroots communities and groups respond to the proliferation of AI?
• What kinds of geographies and spatialities does AI produce and depend on? Within what geographies/spatialities is it embedded?
• Where and how does AI/ML touch, and potentially reconfigure, key concepts, topics, and subfields within geography?
• What new theoretical, empirical, methodological, and political questions or concerns does AI/ML raise for geography as a field?
|Presenter||Casey Lynch*, University of Nevada - Reno, Human/oid Geography: Emotion, Embodiment, and the Spatial Dimensions of Robotic Sociality||15||12:00 AM|
|Presenter||Nick Lally*, University of Kentucky, The forking paths of machine learning||15||12:00 AM|
|Presenter||Kafui Attoh*, CUNY School of Labor and Urban Studies, Declan Cullen*, George Washington University, Geography and “The Last Question”||15||12:00 AM|
|Presenter||Mark Boyle*, University of Liverpool, Governing AI: Politics, Ethics and UK and US ‘Geospatial Data Strategies’||15||12:00 AM|
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