Consumed at Scale: Effects of AI-Driven Extraction on OpenStreetMap as a Digital Commons
Boettcher H (2026)
Publication Language: English
Publication Type: Conference contribution, Conference Contribution
Publication year: 2026
Series: Proceedings of the OSMScience 2026
Pages Range: 57-60
Conference Proceedings Title: OSM Science 2026 Conference Track Proceedings
Event location: Champs-sur-Marne, Paris
URI: https://zenodo.org/records/21561342
Abstract
Large-scale scraping attacks on OpenStreetMap's infrastructure have exposed a fundamental tension between open geodata as a community-maintained commons and its role in current commercial AI development dynamics. This contribution examines the implications of AI-driven data extraction for OSM’s infrastructure and licence compliance guidelines as well as its consequences for OSM’s position within the geospatial data ecosystem. Drawing on a qualitative analysis of community forum discussions, official OSM communications, and licensing documentation, the analysis is structured along two interrelated dimensions through which the implications of AI-driven extraction are discussed: infrastructural strain on volunteer-maintained systems and emerging risks to licence compliance. Rather than enclosure in the classical sense of a commons being fenced off, we argue that unaccountable, large-scale extraction may paradoxically push the community towards defensive forms of closure, altering OSM's character as a digital commons.
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How to cite
APA:
Boettcher, H. (2026). Consumed at Scale: Effects of AI-Driven Extraction on OpenStreetMap as a Digital Commons. In A. Y. Grinberger, P. Mooney, M. Minghini, A.-M. Olteanu-Raimond, A. Zanchetta, J. Raimbault, J. Perret (Eds.), OSM Science 2026 Conference Track Proceedings (pp. 57-60). Champs-sur-Marne, Paris, FR.
MLA:
Boettcher, Hannah. "Consumed at Scale: Effects of AI-Driven Extraction on OpenStreetMap as a Digital Commons." Proceedings of the State of the Map 2026 (OSMScience2026), Champs-sur-Marne, Paris Ed. A. Y. Grinberger, P. Mooney, M. Minghini, A.-M. Olteanu-Raimond, A. Zanchetta, J. Raimbault, J. Perret, 2026. 57-60.
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