GeoAI and the Law Newsletter
Tracking Developments in AI Laws and Regulations for Geospatial Professionals
GeoAI and the Law is not legal advice. The reader should consult with a trained lawyer on legal matters associated with GeoAI.
What’s New
European Parliament votes to delay EU AI Act implementation (CIO)
The European Parliament voted to delay application of the EU AI Act's rules on high-risk AI systems, pushing key deadlines to as late as 2027 and 2028, though the delay still requires approval from the Council of the European Union. Analysts broadly cautioned CIOs against treating the delay as a reprieve, warning that the operational, legal, and reputational risks of poorly governed AI are already present and that organizations should use the extra time to strengthen compliance and governance frameworks rather than wait for final regulatory clarity.
Deep Dive
Last edition of the newsletter referenced two different visions of what federal law in the U.S. should look like: the Trump Administration’s White House National Policy Framework for Artificial Intelligence Legislative Recommendations (March 2026) and the Artificial Intelligence Regulation and Safeguards Act, introduced by Sen. Blackburn (the “Act”). As each would have different impacts on the geospatial sector, I have prepared a comparison of the key points:
Comparison Chart
(Generated by Harvey AI)
Key Considerations for Geospatial Professionals
Key considerations for geospatial professionals include the following:
The Act, draws a statutory distinction between “precise geolocation information” (location within 5 miles or less) and “approximate geolocation information” (greater than 5 miles precision) in the context of algorithmic ranking and content personalization systems. While these definitions are scoped to consumer-facing online platforms and the Filter Bubble Transparency subtitle, they signal a Congressional willingness to regulate the use of location data in AI systems broadly, which could foreshadow future restrictions on how geospatial AI models ingest, process, and act upon precise location data derived from connected devices. Geospatial practitioners should monitor whether these definitional frameworks migrate into future AI or privacy legislation with broader sectoral application.
The duty of care and product liability provisions in of the Act carry significant operational implications for geospatial professionals who develop or deploy AI systems used in high-stakes decision-making environments. The Act imposes negligence-based liability, encompassing design defects, failure to warn, and breach of express warranty, as well as strict liability for unreasonably dangerous AI products. AI-driven spatial analysis tools used in “high-risk” sectors, such as critical infrastructure assessment, land use planning supporting law enforcement decisions, or emergency management, could expose their developers to liability under these provisions. This is in contrast to the White House Framework’s caution against open-ended liability that could stifle innovation.
The Act directs the Office of Science, Technology and Policy to prioritize Federal investment in curated, publicly available datasets for AI training, explicitly listing agriculture, transportation, weather services, and other sectors where geospatial data plays a foundational role. The White House Framework similarly calls for making federal datasets accessible in AI-ready formats for industry and academia. For geospatial professionals, these provisions could unlock expanded access to satellite imagery, environmental monitoring data, census geographic files, and infrastructure datasets maintained by agencies such as USGS, NOAA, and the Census Bureau thereby accelerating the development of geospatially-trained AI models for environmental monitoring, urban planning, disaster response, and national security applications.
The intellectual property and content provenance provisions of the Act have direct implications for geospatial professionals who create, license, or rely on AI-generated spatial content. The Act’s exclusion of AI training from fair use means that organizations using commercially licensed satellite imagery, proprietary map datasets, or curated geographic databases to train geospatial AI models could face copyright infringement claims if they have not secured explicit authorization from data rights holders. The proposed subpoena mechanism further empowers data owners to discover exactly what training datasets AI developers used, making due diligence in data licensing a critical compliance priority for geospatial AI developers.
Edited by Kevin Pomfret
Partner at Pierson Ferdinand, Author of Geospatial Law, Policy and Ethics: Where Geospatial Technology is Taking the Law | LinkedIn