Geography According to ChatGPT -- How Generative AI Represents and Reasons about Geography
Organizations: University of Vienna, Austria · University of Texas at Austin, USA · University of Bristol, UK · University of Wisconsin-Madison, USA ·
Abstract
Understanding how AI will represent and reason about geography should be a key concern for all of us, as the broader public increasingly interacts with spaces and places through these systems. Similarly, in line with the nature of foundation models, our own research often relies on pre-trained models. Hence, understanding what world AI systems construct is as important as evaluating their accuracy, including factual recall. To motivate the need for such studies, we provide three illustrative vignettes, i.e., exploratory probes, in the hope that they will spark lively discussions and follow-up work: (1) Do models form strong defaults, and how brittle are model outputs to minute syntactic variations? (2) Can distributional shifts resurface from the composition of individually benign tasks, e.g., when using AI systems to create personas? (3) Do we overlook deeper questions of understanding when solely focusing on the ability of systems to recall facts such as geographic principles?
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Geospatial Reasoning
Geospatial reasoning studies how AI interprets locations, maps, spatial relationships, and Earth-observation data to answer questions and make decisions.
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