Geospatial Artificial Intelligence (GeoAI) is revolutionizing academia and industry by integrating advanced AI methodologies with geospatial sciences to enable smarter analysis, prediction, and decision-making. However, the global adoption of GeoAI faces critical challenges, including the lack of standardization, transparency, bias control, accountability, fairness, privacy protection, ethical oversight, and equitable collaboration. This study proposes an enhanced comprehensive framework and ethical guidelines to address these gaps and promote responsible GeoAI practices. The proposed frameworks emphasize the importance of ethical governance, interoperability, inclusivity, and reproducibility in GeoAI-driven systems. The proposed GeoAI framework integrates geospatial science, artificial intelligence, and domain expertise through a structured, multi-stage process including benchmarking, expert consultation, framework structuring, and iterative validation. We incorporated ethical guidelines and skill competencies to ensure transparency, fairness, privacy, and alignment with global standards, as outlined in the UN-GGIM. This approach enables the development of a scalable, responsible, and collaborative GeoAI ecosystem for sustainable decision-making. Findings underscore the need to stay current with technological and methodological advancements to enhance geospatial methods and services. Moreover, fostering collaboration among academic, industrial, and policy stakeholders is vital to ensuring that GeoAI initiatives align with and support the United Nations Sustainable Development Goals (SDGs). Ultimately, this work advocates for a transparent, fair, and ethically grounded GeoAI ecosystem that advances scientific innovation and contributes to sustainable global progress.
Mohamed-Ghouse et al. (Tue,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: