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      Book Review

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            Author and article information

            Pluto Journals
            30 August 2022
            : 38
            : 2
            : 246-250
            Author notes

            All content is freely available without charge to users or their institutions. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles in this journal without asking prior permission of the publisher or the author. Articles published in the journal are distributed under a http://creativecommons.org/licenses/by/4.0/.

            Page count
            Pages: 5

            Is AI Good for the Planet? (2021) 160pp., $US13 paperback, Polity Press, Cambridge, ISBN: 978-1509547951

            Book Reviews

            Computer science,Arts,Social & Behavioral Sciences,Law,History,Economics


            1. (2020) ‘Carbontracker: tracking and predicting the carbon footprint of training deep learning models’, Proceedings of the ICML Workshop on Challenges in Deploying and Monitoring Machine Learning Systems, available at https://doi.org/10.48550/arxiv.2007.03051. (accessed May 2022).

            2. (2018) Notes from the AI Frontier: Modeling the Impact of AI on the World Economy, McKinsey Global Institute report, available at https://www.mckinsey.com/featured-insights/artificial-intelligence/notes-from-the-ai-frontier-applications-and-value-of-deep-learning (accessed May 2022).

            3. et al. (2021) The State of AI in 2021, McKinsey Global Institute report, available at https://www.mckinsey.com/business-functions/quantumblack/our-insights/global-survey-the-state-of-ai-in-2021 (accessed May 2022).

            4. (2021) Atlas of AI, Yale University Press, New Haven.

            5. (2021) ‘Chasing carbon: the elusive environmental footprint of computing’, paper presented at IEEE International Symposium on High-Performance Computer Architecture (HPCA), available at https://doi.org/10.1109/HPCA51647.2021.00076. (accessed May 2022)

            6. . (2020) ‘Towards the systematic reporting of the energy and carbon footprints of machine learning’, Journal of Machine Learning Research, 21, 248, pp.1−43.

            7. (2020) ‘Is green growth possible?’, New Political Economy, 25, 4, pp.469–86.

            8. IEA (2021) Data Centres and Data Transmission Networks, International Energy Agency, Paris, available at https://www.iea.org/reports/data-centres-and-data-transmission-networks (accessed May 2022).

            9. IPCC (2022) Climate Change 2022: Mitigation of Climate Change, Intergovernmental Panel on Climate Change, Sixth Assessment Report, Working Group III, available at https://www.ipcc.ch/report/sixth-assessment-report-working-group-3/ (accessed May 2022).

            10. (2012) ‘The economics of degrowth’, Ecological Economics, 84, pp.172–80.

            11. (2021) Three Years under the EU GDPR: An Implementation Progress Report, Access Now report, available at https://www.accessnow.org/gdpr-three-years/ (accessed May 2022).

            12. (2002) Cradle to Cradle: Remaking the Way we Make Things, North Point Press, New York.

            13. (2019) Artificial Intelligence: A Guide for Thinking Humans, Pelican Books, Harmondsworth UK.

            14. (forthcoming) ‘The carbon footprint of machine learning training will plateau, then shrink’, IEEE Computer, available at https://doi.org/10.36227/techrxiv.19139645.v4 (accessed May 2022).

            15. (2021) ‘Stop calling everything AI, machine-learning pioneer says’, IEEE Spectrum, 31 March, available at https://spectrum.ieee.org/stop-calling-everything-ai-machinelearning-pioneer-says (accessed May 2022).

            16. (2017) Doughnut Economics: Seven Ways to Think like a 21st-Century Economist, Chelsea Green Publishing, White River Junction VT.

            17. (forthcoming) ‘Tackling climate change with machine learning’, ACM Computing Surveys, 55, 2, paper 42, available at https://doi.org/10.1145/3485128 (accessed May 2022).

            18. (2021) Stakeholder Capitalism: A Global Economy that Works for Progress, People and Planet, John Wiley, Hoboken NJ.

            19. (2020) ‘Energy and policy considerations for modern deep learning research’, Proceedings of the AAAI Conference on Artificial Intelligence, 34, 9, paper 9, available at https://doi.org/10.1609/aaai.v34i09.7123 (accessed May 2022).

            20. (2022) ‘Perspectives in machine learning for wildlife conservation’, Nature Communications, 13, paper 792, available at https://doi.org/10.1038/s41467-022-27980-y (accessed May 2022).

            21. (2021) ‘The steep cost of capture’, ACM Interactions, 28, 6, available at https://doi.org/10.1145/3488666 (accessed May 2022).

            22. (2019) The Age of Surveillance Capitalism, Profile Books, London.


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