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Abstract The integration of Artificial Intelligence (AI) systems into Earth Observation (EO) research and innovation has catalyzed significant advancements in environmental monitoring, humanitarian response, and urban planning. However, these developments also raise novel regulatory and ethical challenges, particularly in light of the European Union’s Artificial Intelligence Act (EU AI Act), which introduces a tiered risk-based framework for the governance of AI systems. This paper provides the first comprehensive examination of how the EU AI Act, and its provisions concerning high-risk AI systems as delineated in Annex III, apply to EO-based applications. Through a structured analysis of EO use cases across key domains, such as access to public and private services, law enforcement, critical infrastructure, migration, and biometric surveillance, we illustrate how the same EO AI system may be variably classified depending on its intended purpose, autonomy level, and deployment context. We demonstrate that while many current EO AI systems are not yet autonomous enough to trigger high-risk classification, the rapid technological trajectory suggests an increasing prevalence of high-risk EO applications in the near future. Furthermore, we argue that EO researchers and developers must proactively engage with the regulatory demands of the EU AI Act, not merely to ensure compliance, but to contribute to the development of methodological tools, such as explainability, risk assessment, and auditability, that are essential for ensuring responsible AI innovation. By linking legal interpretation with technical and ethical considerations, this paper contributes to an emerging interdisciplinary framework for governing AI in the EO domain under conditions of legal uncertainty and accelerating innovation.
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Caroline Gevaert
Sanja Šćepanović
Nadia Bernaz
AI and Ethics
Wageningen University & Research
University of Würzburg
University of Twente
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Gevaert et al. (Fri,) studied this question.
www.synapsesocial.com/papers/6a095c6d7880e6d24efe29d5 — DOI: https://doi.org/10.1007/s43681-026-01149-5