[Is it possible to envision a sustainable artificial intelligence?]

Artificial intelligence (AI) promises to redefine production systems, decision-making processes, and even social relationships, but it raises critical (and ethical) questions about its environmental impact. The paradox is clear: AI can be both part of the solution and part of the problem. On one hand, it enables better forecasting of extreme weather events thanks to data collected from satellites and sensors, supports "smart" electrical grids that integrate renewable sources such as solar and wind power, strengthens "precision agriculture" by optimizing irrigation and fertilization, and makes smart cities more sustainable through intelligent mobility systems and energy optimization. On the other hand, it introduces unavoidable environmental costs linked to high energy and water consumption, the limited availability of raw materials needed to build data-center components, and the challenge of disposing of them sustainably. Experts propose shifting from energy-hungry Red AI to Green AI, based on lighter, less complex models powered by renewable energy. Techniques such as federated learning and pruning, combined with the use of sustainable data centers, recyclable hardware, and distributed architectures, make it possible to drastically reduce consumption without sacrificing performance. The challenge for the future will be to govern AI with a vision that balances innovation and sustainability, environmental justice and technological progress.