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Artificial Intelligence Leading the Way to Environmental Solutions

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Environmental Sustainability and Applications".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 2890

Special Issue Editor

Special Issue Information

Dear Colleagues,

The emergence of technologies of Industry 4.0 and 5.0 is having a substantial impact on the industries, firms, and societies, making our daily activities dependent on the innovativeness and use of digital technologies (Ben Youssef and Mejri, 2023). Among these disruptive technologies, artificial intelligence (AI) occupies a central place. Recent advances in AI have enabled significant progress in decarbonizing the global economy. Feedback on current applications of AI in different sectors shows a real positive impact that could lead to an overall reduction of around 5 to 10% of global emissions (BCG, 2023).

Digital transformation has the potential to foster economies to shift to more sustainable development and low-carbon economies (Ben Youssef, 2020; Ben Youssef and Zeqiri, 2022). Digital technologies are being applied in response to socioeconomic, environment, climate change, and sustainable problems to cope with the existing problems and to increase their efficiency. New patterns of production and consumption and new business models are created due to digitalization. However, there is a need for technologies and processes to be designed in line with the criteria of digitalization to foster the transition to a more sustainable economy.

In this regard, AI has been acknowledged for its ability to improve economic, environmental, and social sustainability, particularly in product design and development. The concept of "Green AI" has emerged as a field of research, focusing on leveraging AI for environmental sustainability (Verdecchia et al., 2023). Its role in achieving the sustainable development goals (SDGs) has been emphasized, demonstrating how AI can be effectively applied to contribute to specific SDGs and proposing further research on an AI-based evaluative infrastructure for SDGs. However, in discussions on the role of AI in accelerating sustainability, it is essential to consider not only the application of AI in improving environmental sustainability but also the process through which how these technologies are developed and utilized. The ethical and transparent use of AI in ecological research is key. To successfully integrate AI for environmental solutions, it is important to adopt a multilevel, system dynamics perspective and design thinking approach to AI for environmental sustainability, while considering the ethical, societal, and environmental implications of AI applications.

The aim of this Special Issue is to collate theoretical and practical analyses of AI leading the way to environmental solutions. It aims to understand how AI can foster the sustainable development of the economy of different countries or regions and what solutions there are to shift to a more sustainable economy through the application of AI. This Special Issue welcomes contributions at the methodological level presenting new ways of capturing the digitalization and sustainability of different sectors of the economy.

Potential topics may include, but are not limited to the following:

  • AI and sustainable economy; 
  • AI and ecological transition;
  • AI helping firms on the road to sustainability;
  • AI-driven digital transformation for sustainable tourism;
  • AI and energy transition;
  • AI and sustainable society;
  • AI and sustainable transport;
  • AI and climate change;
  • AI, digitalization, and circular economy ;
  • AI and pro-environmental behavior;
  • AI and eco-efficiency;
  • AI and the decarbonization of economy;
  • AI and sustainable manufacturing;
  • AI and sustainable entrepreneurship.

References

  1. Breque, M.; Nul, D.; Petridis, L. Industry 5.0: Towards a Sustainable, Human-Centric and Resilient European Industry; Directorate-General for Research and Innovation; European Commission: Brussels, Belgium, 2021.
  2. Ben Youssef, A., Mejri, I. (2023) Linking Digital Technologies to Sustainability through Industry 5.0: A bibliometric Analysis Sustainability 15 (9), 7465.
  3. Ben Youssef A., Zeqiri, A. (2022) “Hospitality industry 4.0 and climate change”, Circular economy and sustainability.
  4. Ben Youssef A. (2020) How Industry 4.0 can contribute to combatting Climate Change?", Industrial Economics Review (French Industrial Economics Review), June 2020, vol. 169.
  5. Verdecchia, R., Sallou, J., & Cruz, L. J. (2023). A systematic review of green ai. WIREs Data Mining and Knowledge Discovery, 13(4). https://doi.org/10.1002/widm.1507.
  6. Yin, S.; Yu, Y. An adoption-implementation framework of digital green knowledge to improve the performance of digital green innovation practices for industry 5.0. J. Clean. Prod. 2022.

Prof. Dr. Adel Ben Youssef
Guest Editor

Manuscript Submission Information

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Keywords

  • artificial intelligence
  • environment
  • sustainability
  • climate change
  • digital transformation

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Published Papers (1 paper)

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Research

23 pages, 572 KiB  
Article
Assessing the Impact of Digitalization, Tax Revenues, and Energy Resource Capacity on Environmental Quality: Fresh Evidence from CS-ARDL in the EKC Framework
by Adel Ben Youssef and Mounir Dahmani
Sustainability 2024, 16(2), 474; https://doi.org/10.3390/su16020474 - 5 Jan 2024
Cited by 5 | Viewed by 2235
Abstract
This study examines the dynamic relationships between digitalization, environmental tax revenues, and energy resource capacity within the framework of the Environmental Kuznets Curve (EKC), focusing on their combined impact on environmental quality. It employs a cross-sectional augmented autoregressive distributed lag (CS-ARDL) approach, an [...] Read more.
This study examines the dynamic relationships between digitalization, environmental tax revenues, and energy resource capacity within the framework of the Environmental Kuznets Curve (EKC), focusing on their combined impact on environmental quality. It employs a cross-sectional augmented autoregressive distributed lag (CS-ARDL) approach, an advanced technique for complex panel data that is specifically designed to address issues of cross-sectional dependence and slope heterogeneity inherent in panel data analysis. The research covers 88 countries, including both low- and middle-income countries (LMICs) and high-income countries (HICs), to understand how digitalization, as a driving force of the Fourth Industrial Revolution, interacts with environmental taxation and energy resource management to affect greenhouse gas emissions. The results reveal distinct effects of environmental taxes and energy capacity on environmental quality, with marked differences between LMICs and HICs. In HICs, technological progress, especially in information and communication technology (ICT), is found to contribute significantly to environmental quality. For LMICs, the effects are less evident, and the findings suggest the need for tailored strategies in environmental policy and energy management. By providing empirical evidence on the differential impacts of digitalization and energy policies in different economic contexts, this research enriches the environmental economics discourse. It highlights the need for policy frameworks tailored to specific contexts that effectively balance economic growth with sustainable development goals, thereby providing insightful implications for achieving the Sustainable Development Goals (SDGs). Full article
(This article belongs to the Special Issue Artificial Intelligence Leading the Way to Environmental Solutions)
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