Official Repository for the book "Sustainable AI" by Raghavendra Selvan (2025)

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Table of Contents

1. Preface to the book
2. Exercises
3. List of References
4. Reproducibility
5. Errata
6. Additional Material
7. Usage Guidelines

Preface

Climate change is at our door step. It is causing heat waves, flash floods, droughts, and other erratic weather patterns. Addressing the challenges posed by climate change will be the defining project of our times. To do this, we should employ all the tools at our disposal. And one of the most powerful tools currently is artificial intelligence (AI), which has revolutionized tasks in many application domains. As such, AI can be indispensable in our efforts to combat climate change.

The recent class of AI methods, however, is growing to be extremely resource-intensive. Developing and using them requires powerful datacenters, which consume vast amounts of energy with correspondingly high carbon emissions. In addition, the datacenters used for AI require large volumes of fresh water in their cooling systems, rely on extractive mining to manufacture the electronics, and incur additional carbon emissions along their lifecycle. These factors, and other broader environmental impacts, pose a dilemma about using AI for sustainability.

The main argument in this book is that the material basis for any technology should not be discounted even in the light of their promised benefits. This is also true for AI. Even though AI has promised—and delivered on some—solutions to the sustainability challenges, the underlying resource cost of AI should not be ignored. If we don't pay close attention to these massive costs, the supposed benefits offered might be eclipsed by the negative impacts of AI; the trade-off between the cost and benefits should always be considered.

This book is an attempt to lay out these arguments so that we can make meaningful trade-offs that advance the sustainability of AI, while using it to improve the sustainability of our planet. To do this, the book presents practical tools and conceptual frameworks that will help us assess and grapple with the complex interplay between sustainability and AI.

Exercises

The book provides small worked examples along with the text. These are not complete by themselves as I have omitted package loading, book keeping, and other standard code. The complete code to run each of the examples, along with additional context, is provided here.

List of References

The book uses footnote-style referencing, and there is no single bibliography list in the book. The complete list of references, and additional reading material per chapter is provided here.

Reproducibility

Most of the figures in the book should be reproducible, if they are not derived from other sources. The data and code to reproduce all the book figures are provided here.

Errata

To err is human, and all. The book has been checked multiple times for correctness and language. However, as with everything that is sent for publication, we have spotted errors. A comprehensive list of errata will be maintained here.

If you find any errors, please report them as well. Future reprints will have them fixed.

Additional Material

Not all the content I wanted to cover made it to the book. I will update additional resources here

Usage Guidelines

If you find any errors or have suggestions for improvement, please raise Github issues, or fell free to contact me at [email protected]

Kindly cite the book if you use any part of the text, code, or the figures

@book{selvan2025sustainable-ai,
  title     = {Sustainable AI},
  author    = {Raghavendra Selvan},
  year      = {2025},
  publisher = {O'Reilly},
  url       = {https://raghavian.github.io/sustainable-ai/}
}