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This paper investigates the integration of human dynamics within GeoAI, emphasizing the potential of human-centric approaches to improve geospatial data analysis and address ethical concerns. It highlights the use of "humans-as-sensors" to enhance data accuracy and the importance of mixed-expert systems that combine human and AI expertise. The study underscores the need for ethical considerations, such as privacy and bias mitigation, in the development and deployment of GeoAI models.
GeoAI's revolution hinges on ethically integrating human insights, not just raw geospatial data, to truly understand human-environment interactions.
This study examines the role of human dynamics within Geospatial Artificial Intelligence (GeoAI), highlighting its potential to reshape the geospatial research field. GeoAI, emerging from the confluence of geospatial technologies and artificial intelligence, is revolutionizing our comprehension of human-environmental interactions. This revolution is powered by large-scale models trained on extensive geospatial datasets, employing deep learning to analyze complex geospatial phenomena. Our findings highlight the synergy between human intelligence and AI. Particularly, the humans-as-sensors approach enhances the accuracy of geospatial data analysis by leveraging human-centric AI, while the evolving GeoAI landscape underscores the significance of human–robot interaction and the customization of GeoAI services to meet individual needs. The concept of mixed-experts GeoAI, integrating human expertise with AI, plays a crucial role in conducting sophisticated data analyses, ensuring that human insights remain at the forefront of this field. This paper also tackles ethical issues such as privacy and bias, which are pivotal for the ethical application of GeoAI. By exploring these human-centric considerations, we discuss how the collaborations between humans and AI transform the future of work at the human-technology frontier and redefine the role of AI in geospatial contexts.
