TY - GEN
T1 - Embedding Ethics and Trustworthiness for Sustainable AI in Earth Sciences
T2 - 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022
AU - Dias, Philipe
AU - Lunga, Dalton
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - As in many other research domains, Artificial Intelligence (AI) techniques have been increasing their footprint in Earth Sciences to extract meaningful information from the large amount of high-detailed data available from multiple sensor modalities. While on the one hand the existing success cases endorse the great potential of AI to help address open challenges in ES, on the other hand on-going discussions and established lessons from studies on the sustainability, ethics and trustworthiness of AI must be taken into consideration if the community is to ensure that its research efforts move into directions that effectively benefit the society and the environment. In this paper, we discuss insights gathered from a brief literature review on the subtopics of AI Ethics, Sustainable AI, AI Trustworthiness and AI for Earth Sciences in an attempt to identify some of the promising directions and key needs to successfully bring these concepts together.
AB - As in many other research domains, Artificial Intelligence (AI) techniques have been increasing their footprint in Earth Sciences to extract meaningful information from the large amount of high-detailed data available from multiple sensor modalities. While on the one hand the existing success cases endorse the great potential of AI to help address open challenges in ES, on the other hand on-going discussions and established lessons from studies on the sustainability, ethics and trustworthiness of AI must be taken into consideration if the community is to ensure that its research efforts move into directions that effectively benefit the society and the environment. In this paper, we discuss insights gathered from a brief literature review on the subtopics of AI Ethics, Sustainable AI, AI Trustworthiness and AI for Earth Sciences in an attempt to identify some of the promising directions and key needs to successfully bring these concepts together.
KW - AI ethics
KW - AI trustworthiness
KW - Artificial Intelligence
KW - Earth Sciences
KW - Sustainable AI
UR - http://www.scopus.com/inward/record.url?scp=85140408245&partnerID=8YFLogxK
U2 - 10.1109/IGARSS46834.2022.9883030
DO - 10.1109/IGARSS46834.2022.9883030
M3 - Conference contribution
AN - SCOPUS:85140408245
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 4639
EP - 4642
BT - IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 17 July 2022 through 22 July 2022
ER -