Towards a quantitative evaluation of the relationship between performance and environmental sustainability of Artificial Intelligence algorithms

被引：0
作者：
Duraccio, Luigi [1 ]
Angrisani, Leopoldo [2 ]
D'Arco, Mauro [2 ]
De Benedetto, Egidio [2 ]
Imbo, Monica [2 ]
Tedesco, Annarita [3 ]
机构：
[1] Univ Naples Federico II, Ctr Metrol & Adv Technol Serv CeSMA, Naples, Italy
[2] Univ Naples Federico II, Dept Informat Technol & Elect Engn, Naples, Italy
[3] Univ Naples Federico II, Dept Publ Hlth, Naples, Italy
来源：
2024 IEEE INTERNATIONAL INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE, I2MTC 2024 | 2024年
关键词：
4.0; Era; Artificial Intelligence; Carbon Footprint; Climate Change; ICT; LCA; Measurement; Monitoring Systems; Sustainability; Uncertainty; ICT;
D O I：
10.1109/I2MTC60896.2024.10560898
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This work addresses the relationship between the performance and environmental sustainability of artificial intelligence (AI) algorithms. Although it is widely recognized that the adoption of AI technology is fundamental in various fields, ranging from healthcare to industry and entertainment, a quantitative assessment on an operational scale of the environmental impact of training and validating AI algorithms is still an open issue. In order to address this aspect, in this work, the first steps towards a metrology-based analysis are investigated with a two-fold aim: (i) to outline a methodology for evaluating AI algorithms also considering the consequent greenhouse gas emissions, and (ii) to better understand how to continue improving their classification performance in a non-harmful way for the environment.
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页数：6
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