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| Main Authors: | , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2405.20868 |
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| _version_ | 1866911896782766080 |
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| author | Ghamisi, Pedram Yu, Weikang Marinoni, Andrea Gevaert, Caroline M. Persello, Claudio Selvakumaran, Sivasakthy Girotto, Manuela Horton, Benjamin P. Rufin, Philippe Hostert, Patrick Pacifici, Fabio Atkinson, Peter M. |
| author_facet | Ghamisi, Pedram Yu, Weikang Marinoni, Andrea Gevaert, Caroline M. Persello, Claudio Selvakumaran, Sivasakthy Girotto, Manuela Horton, Benjamin P. Rufin, Philippe Hostert, Patrick Pacifici, Fabio Atkinson, Peter M. |
| contents | The convergence of artificial intelligence (AI) and Earth observation (EO) technologies has brought geoscience and remote sensing into an era of unparalleled capabilities. AI's transformative impact on data analysis, particularly derived from EO platforms, holds great promise in addressing global challenges such as environmental monitoring, disaster response and climate change analysis. However, the rapid integration of AI necessitates a careful examination of the responsible dimensions inherent in its application within these domains. In this paper, we represent a pioneering effort to systematically define the intersection of AI and EO, with a central focus on responsible AI practices. Specifically, we identify several critical components guiding this exploration from both academia and industry perspectives within the EO field: AI and EO for social good, mitigating unfair biases, AI security in EO, geo-privacy and privacy-preserving measures, as well as maintaining scientific excellence, open data, and guiding AI usage based on ethical principles. Furthermore, the paper explores potential opportunities and emerging trends, providing valuable insights for future research endeavors. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_20868 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Responsible AI for Earth Observation Ghamisi, Pedram Yu, Weikang Marinoni, Andrea Gevaert, Caroline M. Persello, Claudio Selvakumaran, Sivasakthy Girotto, Manuela Horton, Benjamin P. Rufin, Philippe Hostert, Patrick Pacifici, Fabio Atkinson, Peter M. Computer Vision and Pattern Recognition Computers and Society The convergence of artificial intelligence (AI) and Earth observation (EO) technologies has brought geoscience and remote sensing into an era of unparalleled capabilities. AI's transformative impact on data analysis, particularly derived from EO platforms, holds great promise in addressing global challenges such as environmental monitoring, disaster response and climate change analysis. However, the rapid integration of AI necessitates a careful examination of the responsible dimensions inherent in its application within these domains. In this paper, we represent a pioneering effort to systematically define the intersection of AI and EO, with a central focus on responsible AI practices. Specifically, we identify several critical components guiding this exploration from both academia and industry perspectives within the EO field: AI and EO for social good, mitigating unfair biases, AI security in EO, geo-privacy and privacy-preserving measures, as well as maintaining scientific excellence, open data, and guiding AI usage based on ethical principles. Furthermore, the paper explores potential opportunities and emerging trends, providing valuable insights for future research endeavors. |
| title | Responsible AI for Earth Observation |
| topic | Computer Vision and Pattern Recognition Computers and Society |
| url | https://arxiv.org/abs/2405.20868 |