Like other sectors around the world, the lightning-fast development of artificial intelligence (AI) has made its way into healthcare, particularly in the field of healthcare. radiology field. As such, AI-based diagnostic systems are booming, with hospitals rapidly adopting the technology to assist radiologists. On the other hand, there are concerns about the environmental impact of increasingly complex AI models and the need for more sustainable AI solutions.
Therefore, Associate Professor Daiju Ueda of Osaka Metropolitan University Graduate School of Medicine, a member of the Radiological Society of Japan, led a research team in studying the environmental costs of AI. In this research review, core members of the Japanese Society of Radiology and researchers in the medical field discussed the power consumption of AI systems in the medical field, carbon emissions from data centers, and issues electronic waste. Specific solutions to mitigate these environmental impacts were discussed, including the development of energy-efficient AI models, the implementation of green computing and the use of renewable energy.
Furthermore, the review proposes measures for the sustainable deployment of AI in the medical field. These are important guidelines for medical institutions, policymakers, and AI developers to operate AI systems in an environmentally friendly manner.
AI has the potential to improve the quality of healthcare, but at the same time its environmental impact cannot be ignored. The best practices we have recommended are the first step toward balancing these two factors. The challenge for the future will be to verify and deepen these recommendations in real medical practice. They should also contribute to the standardization of methods for assessing the environmental impact of AI and the development of an international regulatory framework. »
Daiju Ueda, associate professor of Osaka Metropolitan University Graduate School of Medicine
The results were published in Diagnostic and interventional imaging.
Source:
Journal reference:
Ueda, D., et al. (2024). Climate change and artificial intelligence in healthcare: assessment and recommendations for a sustainable future. Diagnostic and interventional imaging. doi.org/10.1016/j.diii.2024.06.002.