The role of artificial intelligence in achieving the Sustainable Development Goals
Open accessAbstract
The emergence of artificial intelligence (AI) and its progressively wider impact on many sectors requires an assessment of its effect on the achievement of the Sustainable Development Goals. Using a consensus-based expert elicitation process, we find that AI can enable the accomplishment of 134 targets across all the goals, but it may also inhibit 59 targets. However, current research foci overlook important aspects. The fast development of AI needs to be supported by the necessary regulatory insight and oversight for AI-based technologies to enable sustainable development. Failure to do so could result in gaps in transparency, safety, and ethical standards.
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Various companies have launched AI learning and skill enhancement initiatives to widely educate employees and bridge the growing skills divide.
“Various companies have launched AI learning and skill enhancement initiatives (Vinuesa et al., 2020) to widely educate employees and bridge the growing skills divide.”
From Generative AI in Higher Education: The ChatGPT Effect (2024) · cites this paper as Vinuesa et al., 2020
The ‘AI and economic outcomes’ section discusses jobs requiring more skills and the risk of inequality, but does not describe companies launching AI learning or skill-enhancement initiatives. Searches for employee training, reskilling and company initiatives found no passage addressing that attributed claim. No page number was provided for the passages. (LLM, conf=0.76)
Experimental — accuracy not yet measuredOne of the biggest problems facing citizens is the lack of information about the types of data analyzed in AI systems.
“one of the biggest problems facing citizens is the lack of information about the types of data analyzed in AI systems [128].”
From Trust, transparency, and openness: How inclusion of cultural values shapes Nordic national public policy strategies for artificial intelligence (AI) (2020) · cites this paper as [128]
If policy-makers lack sufficient understanding of the risks and challenges of AI, the oversight policy is likely to be ineffective at best and counterproductive at worst.
“Otherwise, the oversight policy 'is likely to be ineffective at best and counterproductive at worst'.150”
From Artificial Intelligence and Sustainable Decisions (2023) · cites this paper as [150]
According to current estimates, the global electricity demand for advanced ICT could increase to 20% compared to around 1% today.
“According to current estimates, the global electricity demand for advanced ICT could increase to 20 % compared to around 1 % today [271].”
From Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review (2024) · cites this paper as [271]
AI has the potential to advance 134 targets across all SDGs while hindering 59 targets.
“Vinuesa et al. [271] reveal the potential of AI to advance 134 targets across all goals while hindering 59 targets.”
From Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review (2024) · cites this paper as [271]
Environmentally smart sustainable urbanism involves developing joint actions for preserving the environment based on analyzing large-scale databases, understanding climate change, modeling its impacts, improving ecosystem health, enabling high integration of renewable energy and smart energy, enhancing smart renewable energy infrastructures, optimizing energy consumption and production, developing
“This lies in developing joint actions for preserving the environment based on analyzing large-scale databases, understanding the complexity of climate change and modeling and simulating its potential impacts, improving the health of ecosystems, and enabling high integration of renewable energy and smart energy [271], enhancing smart renewable energy infrastructures in smart cities [275],”
From Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review (2024) · cites this paper as [271]
AI applications can potentially contribute to achieving 17 Sustainable Development Goals (SDGs).
“Overall, as Vinuesa et al. [104] have argued, AI applications can potentially contribute to achieving 17 Sustainable Development Goals (SDGs).”
From The sustainability of artificial intelligence: an urbanistic viewpoint from the lens of smart and sustainable cities (2020) · cites this paper as [104]
A great deal of research and innovation was witnessed in the field of AI in relation to environmental sustainability, climate change, and smart cities during the second and third periods.
“Consequently, a great deal of research and innovation was witnessed in the field of AI in relation to environmental sustainability, climate change, and smart cities (e.g., (Nishant et al. 2020); (Leal Filho et al. 2022; Vinuesa et al. 2020; Yigitcanlar and Cugurullo 2020; Yigitcanlar et al. 2020) during the second and third periods.”
From Environmentally sustainable smart cities and their converging AI, IoT, and big data technologies and solutions: an integrated approach to an extensive literature review (2023) · cites this paper as Vinuesa et al. 2020
The global electricity demand of advanced technologies (AI, IoT, and Big Data) could go up to 20% compared to around 1% today.
“It is estimated that the global electricity demand of advanced technologies (AI, IoT, and Big Data) could go up to 20% compared to around 1% today (Vinuesa et al. 2020).”
From Environmentally sustainable smart cities and their converging AI, IoT, and big data technologies and solutions: an integrated approach to an extensive literature review (2023) · cites this paper as Vinuesa et al. 2020
AI will assist in better understanding the climate change phenomenon as well as modelling the impacts thereof.
“Furthermore, evidence exists that shows that AI will assist in better understanding the climate change phenomenon as well as modelling the impacts thereof (Vinuesa et al., 2020); however, this will not be possible in situations where DT distribution is already uneven between rich and developing countries (WHO, 2019).”
From Deploying artificial intelligence for climate change adaptation (2022) · cites this paper as Vinuesa et al. (2020)
AI can be integrated with improving renewable energy capabilities and energy efficiency, thus reducing total greenhouse gas emissions and carbon footprint.
“Vinuesa et al. (2020), who assert that AI can be integrated with improving renewable energy capabilities and energy efficiency, thus reducing the total greenhouse gas emissions and carbon footprint.”
From Deploying artificial intelligence for climate change adaptation (2022) · cites this paper as Vinuesa et al. (2020)
40% and 41% of respondents respectively believed that AI and DTs would not be good tools to aid research in climate change and the implementation of SDG13.
“On the other hand, 40% and 41% of respondents respectively, believed that AI and DTs would not be good tools to aid research in climate change and the implementation of SDG13 as some of the AI techniques are high energy demanders, and particularly where non-carbon neutral energy sources are used (Vinuesa et al., 2020).”
From Deploying artificial intelligence for climate change adaptation (2022) · cites this paper as Vinuesa et al., 2020
AI could act as an enabler in achieving environmental-related outcomes, including SDG13.
“Our study findings are similar to Vinuesa et al. (2020), which established that AI could act as an enabler in achieving environmental-related outcomes, including SDG13.”
From Deploying artificial intelligence for climate change adaptation (2022) · cites this paper as Vinuesa et al. (2020)
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- Authors
- Vinuesa, R., Azizpour, H., Leite, I., Balaam, M., Dignum, V., Domisch, S., Felländer, A., Langhans, S. D., Tegmark, M., & Fuso Nerini, F.
- Affiliations
- KTH Royal Institute of Technology (SE)
- Umeå University (SE)
- Leibniz Institute of Freshwater Ecology and Inland Fisheries (DE)
- Basque Centre for Climate Change (ES)
- Massachusetts Institute of Technology (US)
- Corresponding author
- Vinuesa, Ricardo
- ORCID
- Venue
- Nature Communications
- Published
- 2020-01-13
- Volume
- 11
- Issue
- 1
- Pages
- 233-233
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC6957485
- OpenAlex
- W3000603264
- Cited by
- 3,294
- References
- 72
- Citations by year
- 2026: 688 · 2025: 782 · 2024: 638 · 2023: 560 · 2022: 296 · 2021: 239 · 2020: 87 · 2019: 4
- FWCI
- 57.46
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- KTH Publication Database DiVA (KTH Royal Institute of Technology) (submittedVersion, other-oa)
- RePEc: Research Papers in Economics (submittedVersion)
- Communities in ADDI (Universidad del Pais Vasco) (submittedVersion, cc-by-nc-sa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Hispana (submittedVersion, cc-by-nc-sa)
- arXiv (Cornell University)
- Funders
- European Commission (HORIZON2020, 748625)
- Stiftelsen för Strategisk Forskning (2017-05189, RIT15-0046)
- Svenska Forskningsrådet Formas (2018-01253)
- Jacobs Foundation
- Knut och Alice Wallenbergs Stiftelse (RIT15-0046)
- Vetenskapsrådet (2017-05189, RIT15-0046, 2018-)
- Leibniz-Gemeinschaft (J45/2018)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Sociology and Political Science › Innovation, Sustainability, Human-Machine Systems
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- artificial intelligence, Sustainable Development Goals, SDG targets, AI impact assessment, AI regulation, AI governance, transparency, AI safety, AI ethics, expert elicitation
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