The carbon impact of artificial intelligence

Dhar, Payal

doi:10.1038/s42256-020-0219-9

Cited by 264 publications

(132 citation statements)

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“…Matheson (2020) states that AI has become a sustainability issue focusing on specific ethical concerns, while Kobielus (2020) reveals that researchers have overestimated the benefits of AI and ignored its costs to raise the energy needed to make it operational. The data and computing power of AI comes at a cost that is approximately half a per cent of world energy consumption (Luccioni et al, 2020); AI, machine learning, information and communication technologies consume sizable electricity contributing to 8% of global energy use (Beyer, 2019); the carbon cost can be reduced by shifting to sustainable AI infrastructure (Dhar, 2020).…”

Section: Review Of the Literaturementioning

confidence: 99%

Artificial intelligence and carbon footprints: Roadmap for Indian agriculture

2021

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Artificial intelligence technology in the agricultural sector can reduce carbon emissions from agrarian activities and revitalize the whole industry. The Indian agricultural sector has become costly, time-consuming, and outdated owing to the global warming process. The deployment of AI technology in Indian agriculture is still a distant dream, given the peculiarities like small-size farms, traditional farming methods, lack of credit, storage facilities, and the decision maker's risk-seeking attitude. AI solutions need to be delivered at the farmers' doorstep in their local language, with proper training, input support, and in collective/cooperative manner for realizing sustainable and green agriculture.

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Section: Review Of the Literaturementioning

confidence: 99%

Artificial intelligence and carbon footprints: Roadmap for Indian agriculture

2021

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“…Moreover, AI-enabled personalized mobile marketing (e.g., Tong et al, 2020 ) and in-store communication and technology (e.g., Dekimpe et al, 2020 ; Grewal, Noble, et al, 2020 ; van Esch et al, 2021 ) can prompt unplanned offline purchases and impulsive buying, which, in turn, amplify consumption and its environmental drawbacks. Finally, information and communication technologies, applications, and systems related to AI themselves can have rebound effects caused by energy consumption and emissions of AI development, production, and deployment (e.g., Belkhir & Elmeligi, 2018 ; Dhar, 2020 ; Lange et al, 2020 ).…”

Section: The Ethics Of Ai In Marketingmentioning

confidence: 99%

Leveraging Artificial Intelligence in Marketing for Social Good—An Ethical Perspective

Hermann

2021

J Bus Ethics

147

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Artificial intelligence (AI) is (re)shaping strategy, activities, interactions, and relationships in business and specifically in marketing. The drawback of the substantial opportunities AI systems and applications (will) provide in marketing are ethical controversies. Building on the literature on AI ethics, the authors systematically scrutinize the ethical challenges of deploying AI in marketing from a multi-stakeholder perspective. By revealing interdependencies and tensions between ethical principles, the authors shed light on the applicability of a purely principled, deontological approach to AI ethics in marketing. To reconcile some of these tensions and account for the AI-for-social-good perspective, the authors make suggestions of how AI in marketing can be leveraged to promote societal and environmental well-being.

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“…After conducting a survey of 400 algorithms presented in research papers at two top AI conferences (IJCAI and NeurIPS), researchers reported that only 6% of the presented papers shared the algorithm's code, a third shared the data on which they tested their algorithms, and only half shared a partial summary of the algorithm (Gundersen and Kjensmo 2018;Hutson 2018). Several studies have investigated this issue in the context of energy consumption and carbon emissions (Lacoste et al 2019;Schwartz et al 2019;Strubell, Ganesh, and McCallum 2019;Henderson et al 2020;Dhar 2020). Indeed, after analysing a sample of 100 papers from the NeurIPS 2019 proceedings, Henderson et al (2020, 4) reported that none of them provided carbon metrics, only one of them "measured energy in some way, 45 measured runtimes in some way, 46 provided the hardware used" and 17 of them "provided some measure of computational complexity (e.g., compute-time, FPOs, parameters)".…”

Section: Normative Considerationsmentioning

confidence: 99%

The AI Gambit — Leveraging Artificial Intelligence to Combat Climate Change: Opportunities, Challenges, and Recommendations

et al. 2021

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In this article we analyse the role that artificial intelligence (AI) could play, and is playing, to combat global climate change. We identify two crucial opportunities that AI offers in this domain: it can help improve and expand current understanding of climate change and it contribute to combatting the climate crisis effectively. However, the development of AI also raises two sets of problems when considering climate change: the possible exacerbation of social and ethical challenges already associated with AI, and the contribution to climate change of the greenhouse gases emitted by training data and computation-intensive AI systems. We assess the carbon footprint of AI research, and the factors that influence AI's greenhouse gas (GHG) emissions in this domain. We find that the carbon footprint of AI research may be significant and highlight the need for more evidence concerning the trade-off between the GHG emissions generated by AI research and the energy and resource efficiency gains that AI can offer. In light of our analysis, we argue that leveraging the opportunities offered by AI for global climate change whilst limiting its risks is a gambit which requires responsive, evidence-based and effective governance to become a winning strategy. We conclude by identifying the European Union as being especially well-placed to play a leading role in this policy response and provide 13 recommendations that are designed to identify and harness the opportunities of AI for combatting climate change, while reducing its impact on the environment.

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The carbon impact of artificial intelligence

Cited by 264 publications

References 0 publications

Artificial intelligence and carbon footprints: Roadmap for Indian agriculture

Artificial intelligence and carbon footprints: Roadmap for Indian agriculture

Leveraging Artificial Intelligence in Marketing for Social Good—An Ethical Perspective

The AI Gambit — Leveraging Artificial Intelligence to Combat Climate Change: Opportunities, Challenges, and Recommendations

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