Hi folks! Hope you're doing well! I recently wrote a research article titled " The Imperative for Sustainable AI Systems ( https://share.polymail.io/v1/z/b/NjE1NDFmMDQ0Yjg2/FU7oo27EnlvuhhooN5ZrUau0Bq... ) " (published by The Gradient) that talks about how including environmental aspects as a core consideration alongside business and functional requirements will lead to more eco-friendly, performant, and socially just outcomes in the design, development, and deployment of AI systems. It does so by: * *highlighting the challenges with the current paradigm* (exploitative data practices, centralization of power and homogenization, and massive energy footprint) * *explaining what sustainable AI is* (elevating smaller models, alternate deployment strategies, and carbon-awareness and carbon-efficiency) *and * * *what we can do next* (sharing the idea of sustainable AI widely, instrumenting AI systems to gather telemetry, and making carbon impacts a core consideration alongside functional and business requirements) Given the areas that we all work on as researchers, I hope that you find this useful - happy to answer any questions on this, thanks! Abhishek Gupta ( @atg_abhishek ( https://twitter.com/atg_abhishek ) ) Founder and Principal Researcher, Montreal AI Ethics Institute ( https://montrealethics.ai/ ) Machine Learning @ Microsoft Chair, Standards Working Group, Green Software Foundation ( https://greensoftware.foundation/ ) CSE Responsible AI Board Member, Microsoft Learn more about my work here ( https://atg-abhishek.github.io/ ). You can now support my work by buying me a coffee ( https://buymeacoff.ee/abhishekgupta ) !