Survey on AI sustainability: emerging trends on learning algorithms and research challenges
Artificial Intelligence (AI) is a fast-growing research and development (RandD) discipline which is attracting increasing attention because it promises to bring vast benefits for consumers and businesses, with considerable benefits promised in productivity growth and innovation. To date, significant...
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| Format: | Journal Article |
| Language: | English |
| Published: |
2023
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| Online Access: | https://hdl.handle.net/10356/170678 |
| _version_ | 1826120004332945408 |
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| author | Chen, Zhenghua Wu, Min Chan, Alvin Li, Xiaoli Ong, Yew-Soon |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Chen, Zhenghua Wu, Min Chan, Alvin Li, Xiaoli Ong, Yew-Soon |
| author_sort | Chen, Zhenghua |
| collection | NTU |
| description | Artificial Intelligence (AI) is a fast-growing research and development (RandD) discipline which is attracting increasing attention because it promises to bring vast benefits for consumers and businesses, with considerable benefits promised in productivity growth and innovation. To date, significant accomplishments have been reported in many areas that have been deemed challenging for machines, ranging from computer vision, natural language processing, audio analysis to smart sensing and many others. The technology trend in realizing success has developed towards increasingly complex and large-size AI models to solve more complex problems at superior performance and robustness. This rapid progress, however, has taken place at the expense of substantial environmental costs and resources. In addition, debates on the societal impacts of AI, such as fairness, safety, and privacy, have continued to grow in intensity. These issues have reflected major concerns pertaining to the sustainable development of AI. In this work, major trends in machine learning approaches that can address the sustainability problem of AI have been reviewed. Specifically, the emerging AI methodologies and algorithms are examined for addressing the sustainability issue of AI in two major aspects, i.e., environmental sustainability and social sustainability of AI. Then, the major limitations of the existing studies are highlighted, and potential research challenges and directions are proposed for the development of the next generation of sustainable AI techniques. It is believed that this technical review can help promote a sustainable development of AI RandD activities for the research community. |
| first_indexed | 2024-10-01T05:09:26Z |
| format | Journal Article |
| id | ntu-10356/170678 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:09:26Z |
| publishDate | 2023 |
| record_format | dspace |
| spelling | ntu-10356/1706782023-09-26T01:01:33Z Survey on AI sustainability: emerging trends on learning algorithms and research challenges Chen, Zhenghua Wu, Min Chan, Alvin Li, Xiaoli Ong, Yew-Soon School of Electrical and Electronic Engineering Engineering::Computer science and engineering Artificial Intelligence Sustainable Development Artificial Intelligence (AI) is a fast-growing research and development (RandD) discipline which is attracting increasing attention because it promises to bring vast benefits for consumers and businesses, with considerable benefits promised in productivity growth and innovation. To date, significant accomplishments have been reported in many areas that have been deemed challenging for machines, ranging from computer vision, natural language processing, audio analysis to smart sensing and many others. The technology trend in realizing success has developed towards increasingly complex and large-size AI models to solve more complex problems at superior performance and robustness. This rapid progress, however, has taken place at the expense of substantial environmental costs and resources. In addition, debates on the societal impacts of AI, such as fairness, safety, and privacy, have continued to grow in intensity. These issues have reflected major concerns pertaining to the sustainable development of AI. In this work, major trends in machine learning approaches that can address the sustainability problem of AI have been reviewed. Specifically, the emerging AI methodologies and algorithms are examined for addressing the sustainability issue of AI in two major aspects, i.e., environmental sustainability and social sustainability of AI. Then, the major limitations of the existing studies are highlighted, and potential research challenges and directions are proposed for the development of the next generation of sustainable AI techniques. It is believed that this technical review can help promote a sustainable development of AI RandD activities for the research community. Agency for Science, Technology and Research (A*STAR) Nanyang Technological University This work was supported in part by the A*STAR Center for Frontier AI Research, and in part by the School of Computer Science and Engineering at Nanyang Technological University. 2023-09-26T01:01:33Z 2023-09-26T01:01:33Z 2023 Journal Article Chen, Z., Wu, M., Chan, A., Li, X. & Ong, Y. (2023). Survey on AI sustainability: emerging trends on learning algorithms and research challenges. IEEE Computational Intelligence Magazine, 18(2), 60-77. https://dx.doi.org/10.1109/MCI.2023.3245733 1556-603X https://hdl.handle.net/10356/170678 10.1109/MCI.2023.3245733 2-s2.0-85153580309 2 18 60 77 en IEEE Computational Intelligence Magazine © 2023 IEEE. All rights reserved. |
| spellingShingle | Engineering::Computer science and engineering Artificial Intelligence Sustainable Development Chen, Zhenghua Wu, Min Chan, Alvin Li, Xiaoli Ong, Yew-Soon Survey on AI sustainability: emerging trends on learning algorithms and research challenges |
| title | Survey on AI sustainability: emerging trends on learning algorithms and research challenges |
| title_full | Survey on AI sustainability: emerging trends on learning algorithms and research challenges |
| title_fullStr | Survey on AI sustainability: emerging trends on learning algorithms and research challenges |
| title_full_unstemmed | Survey on AI sustainability: emerging trends on learning algorithms and research challenges |
| title_short | Survey on AI sustainability: emerging trends on learning algorithms and research challenges |
| title_sort | survey on ai sustainability emerging trends on learning algorithms and research challenges |
| topic | Engineering::Computer science and engineering Artificial Intelligence Sustainable Development |
| url | https://hdl.handle.net/10356/170678 |
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