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Jeremy Crampton

Adjunct Professor of Geography, George Washington University
Chapter Member: Maryland-Washington, D.C. SSN
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About Jeremy

Crampton is an interdisciplinary social scientist with a background in geography, mapping, Geographic Information Science, and geospatial technologies. Crampton studies the socio-political aspects of spatial big data, location technologies, and algorithmic governance. His current interests lie in geolocational policy for data privacy and protection. He has contributed to policy frameworks for socially responsible location data in the public interest, resulting in White Papers in both the UK and the USA.

Contributions | No Jargon Podcast | In the News | Publications

Contributions

The U.S. Government Must Protect Citizens from Geolocational Disinformation and Surveillance AI

Basic Facts Brief,

In the News

Opinion: "Think. Resist. Act Local: Is a Slow AI Possible?," Jeremy Crampton, Ada Lovelace Institue, March 3, 2020.

Publications

"GeoAI, Counter-AI, and Human Geography: A Conversation" (with Krzysztof Janowicz and Renée Sieber). Dialogues in Human Geography 12, no. 13 (2022): 446-458.

A discussion between two experts in geographically-enhanced artificial intelligence (GeoAI), focussing on the threats and opportunities of GeoAI. Both participants emphasize concerns related to data representation, bias, algorithm blackboxing, and the importance of accountability and critique in this evolving field.

"A White Paper on Locational Information and the Public Interest," (with Michael Goodchild, Richard Appelbaum, William Herbert, Krzysztof Janowicz, Mei-Po Kwan, and Michael Katina et al.), The American Association of Geographers (AAG), The Center for Spatial Studies at the University of California, Santa Barbara, and Esri, September 2022.

Outlines the key issues that were identified by a series of public talks and domain experts in the field of geolocational information. Summarizes findings and provides recommendations for spatial information protection and privacy.

"Platform Biometrics" Surveillance & Society 17, no. 1 (2019).

Explores the emergence of platform biometrics, focusing on Microsoft Face, a prominent facial biometric system. Offers a critique of the assumptions behind the system: the reliability of facial expressions in expressing emotions, the universality of emotions, and the concept of seven basic emotions.