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Sustainability
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AI and Sustainability: Risks and Challenges
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AI and Sustainability: Risks and Challenges

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: closed (31 December 2024) | Viewed by 5169

Special Issue Editor

Prof. Dr. Ertel Wolfgang

E-Mail Website
Guest Editor
Institute for Artificial Intelligence, Ravensburg-Weingarten University of Applied Sciences, Doggenriedstraße, 88250 Weingarten, Germany
Interests: artificial intelligence; machine learning; sustainability; climate change

Special Issue Information

Dear Colleagues,

The great successes of AI in the last decade have ushered in the age of intelligent autonomous vehicles, robots, machines, and office helpers. AI systems are now better than the best humans at quite a few difficult specialized tasks, and the pace of development is accelerating. AI will make our lives even more comfortable and convenient. It will take many jobs off our hands and lead to huge disruptions in professional life. Entire professions will become obsolete. AI is one of the biggest growth drivers in the economy. At the same time, we have exceeded the limits of growth since about 1970, and climate change is clearly showing us these limits. In the next few decades, super-intelligent AI could possibly evolve to take the helm from us humans, with a completely open end.

The aim of this Special Issue is to scientifically explore the tension between AI and sustainability and suggest possible solutions. Original research articles and reviews are welcome. The following questions arise, among many others:

● What contribution does AI make to economic growth?
● How can we solve the dilemma between growth and sustainability?
● Do we need to limit research in AI?
● Can AI contribute to a more sustainable way of life, for example, by saving energy in smart homes, optimizing processes in industry or sorting waste in recycling plants?
● What does the use of autonomous weapons systems such as killer drones mean for our security, but above all for future wars?
● Can and should intelligent service robots serve as substitutes for life partners or as caregivers in nursing homes?
● What will social interaction look like in the future when chatbots or robots perhaps replace our partners or colleagues?
● Will AI in the future control and manipulate social media platforms, the internet as a whole, and our political opinions?
● What should the working world of the future look like when people work together with AIs and robots?
● What happens to the productivity gains from even more automation and AI in the workplace?
● How will the economic system and our definition of prosperity have to change when AIs do the work?

I/We look forward to receiving your contributions.

Prof. Dr. Ertel Wolfgang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • artificial intelligence
  • sustainability
  • economic growth
  • prosperity
  • limits to growth
  • future work place
  • climate change
  • environmental protection
  • singularity
  • autonomous weapons

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Published Papers (3 papers)

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Research

9 pages, 377 KiB  
Article
Rebound Effects Caused by Artificial Intelligence and Automation in Private Life and Industry
by Wolfgang Ertel and Christopher Bonenberger
Sustainability 2025, 17(5), 1988; https://doi.org/10.3390/su17051988 - 26 Feb 2025
Viewed by 755
Abstract
Many tasks in a modern household are performed by machines, e.g., a dishwasher or a vacuum cleaner, and in the near future most household tasks will be performed by smart service robots. This will relieve the residents, who in turn can enjoy their [...] Read more.
Many tasks in a modern household are performed by machines, e.g., a dishwasher or a vacuum cleaner, and in the near future most household tasks will be performed by smart service robots. This will relieve the residents, who in turn can enjoy their free time. This newly gained free time will turn out to cause the so-called spare time rebound effect due to more resource consumption. We roughly quantify this rebound effect and propose a CO2-budget model to reduce or even avoid it. In modern industry, automation and AI are taking over work from humans, leading to higher productivity of the company as a whole. This is the main reason for economic growth, which leads to environmental problems due to higher consumption of natural resources. We show that, even though the effects of automation at home and in the industry are different (free time versus higher productivity), in the end they both lead to more resource consumption and environmental pollution. We discuss possible solutions to this problem, such as carbon taxes, emissions trading systems, and a carbon budget. Full article
(This article belongs to the Special Issue AI and Sustainability: Risks and Challenges)
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19 pages, 726 KiB  
Article
Towards Sustainable Development: Can Industrial Intelligence Promote Carbon Emission Reduction
by Hanqing Xu, Zhengxu Cao and Dongqing Han
Sustainability 2025, 17(1), 370; https://doi.org/10.3390/su17010370 - 6 Jan 2025
Cited by 1 | Viewed by 1097
Abstract
The realization of intelligent transformation is an important path for the industry to move towards low-carbon development. Based on panel data from 30 provinces in China, this study utilizes the intermediate effect model and spatial econometric model to analyze the influence of industrial [...] Read more.
The realization of intelligent transformation is an important path for the industry to move towards low-carbon development. Based on panel data from 30 provinces in China, this study utilizes the intermediate effect model and spatial econometric model to analyze the influence of industrial intelligence on carbon emissions. The research reveals that industrial intelligence helps with carbon reduction, and the result is still valid after undergoing various tests. Industrial intelligence relies on green technological innovation, industrial structure upgrading, and energy intensity to realize carbon reduction. There is a spatial spillover role of industrial intelligence on carbon emissions, which has a positive influence on carbon reduction in local and adjoining regions. The influence of industrial intelligence on carbon emissions exhibits heterogeneity in the regional dimension, time dimension, and industrial intelligence level dimension. The research provides empirical evidence and implications for using artificial intelligence to achieve carbon reduction. Full article
(This article belongs to the Special Issue AI and Sustainability: Risks and Challenges)
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23 pages, 3034 KiB  
Article
AI Carbon Footprint Management with Multi-Agent Participation: A Tripartite Evolutionary Game Analysis Based on a Case in China
by Xuwei Wang, Kaiwen Ji and Tongping Xie
Sustainability 2023, 15(11), 9013; https://doi.org/10.3390/su15119013 - 2 Jun 2023
Cited by 2 | Viewed by 2392
Abstract
AI is playing an important role in promoting sustainable development, but the carbon footprint caused by AI is scaling quickly and may partly offset the effort to reduce carbon emissions. However, recommendations for limiting the AI carbon footprint are lacking. In order to [...] Read more.
AI is playing an important role in promoting sustainable development, but the carbon footprint caused by AI is scaling quickly and may partly offset the effort to reduce carbon emissions. However, recommendations for limiting the AI carbon footprint are lacking. In order to address this gap in the literature, this paper first constructs a tripartite evolutionary game model by taking governments, AI industry alliances, and consumers into consideration, and then exploring the impacts of key factors on these three players’ strategy selection based on the case of smart air conditioner consumption in China. The results show that the behavior of governments has an important influence on the behavior of AI industry alliances and consumers. The ideal consequence is that governments adopt an unregulated strategy, AI industry alliances adopt a green development strategy, and consumers adopt a green purchase strategy. Regulation by governments is indispensable for limiting the AI carbon footprint during an early stage but becomes dispensable when the system reaches an optimal state. Although a tendency toward green consumption, image benefit, regulatory cost, carbon price, and the subsidies given to consumers and AI industry alliances can largely influence the strategy selection of governments, governments are most sensitive to carbon prices and the subsidies given to consumers. AI industry alliances are not sensitive to subsidies, reputation improvement, and reputation loss but are most sensitive to carbon prices. Consumers are most sensitive to green consumption tendencies, self-satisfaction, and utility but are not sensitive to subsidies. Full article
(This article belongs to the Special Issue AI and Sustainability: Risks and Challenges)
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