Researchers investigated the environmental costs of AI, including energy consumption of AI systems in the medical field, carbon emissions of data centers, and electronic waste issues.
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.
Therefore, Associate Professor Daiju Ueda of Osaka Metropolitan University's Graduate School of Medicine, a member of the Japan Radiological Society, led a research team in the investigation of the environmental costs of AI. In this research review, head members of the Japan Radiological Society and medical field researchers discussed the energy consumption of AI systems in the medical field, carbon emissions of data centers, and electronic waste issues.
"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 steps toward balancing these two factors," stated Professor Ueda."The challenge for the future will be to verify and further elaborate these recommendations in actual medical practice.
Medical Devices Medical Imaging Sustainability Environmental Issues Environmental Science Robotics Computational Biology Information Technology
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