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Journal articles on the topic 'Sustainable artificial intelligence'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Rosen, Marc A. "Artificial intelligence and sustainable development." European Journal of Sustainable Development Research 9, no. 1 (2025): em0275. https://doi.org/10.29333/ejosdr/15819.

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Many factors will affect society’s shift towards sustainable development and attainment of the UN Sustainable Development Goals for 2015-2030. But of all, perhaps none has the potential to have a greater impact than artificial intelligence. AI has the potential to foster many advances in numerous areas, as well as the potential to cause some problems. But on the whole, the potential to make advances in sustainable development methods, technologies and operations offered by AI are profound and could lead to great strides in a relatively short time. In this editorial, the relation between AI and

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Goralski, Margaret A., and Tay Keong Tan. "Artificial intelligence and sustainable development." International Journal of Management Education 18, no. 1 (2020): 100330. http://dx.doi.org/10.1016/j.ijme.2019.100330.

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Mathur, Rashmi. "Artificial Intelligence in Sustainable Agriculture." International Journal for Research in Applied Science and Engineering Technology 11, no. 6 (2023): 4047–52. http://dx.doi.org/10.22214/ijraset.2023.54360.

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Abstract: Humans have been inventing machines to accomplish arduous and time-consuming tasks. Technology has advanced to enable the development of machines that perceive and acquire data, understand language, retain it as knowledge, deduce information, reason, and solve problems. The widespread deployment of artificial intelligence is a milestone in the history of the transformative aspects of modern technology. Agriculture is a vital sector that supports economic growth and human subsistence and automation in this sector is a global concern. A vast majority of people in India's agrarian econo

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Jennifer, Babirye. "Harnessing Artificial Intelligence to promote sustainable development in Uganda." International Journal of Research Publication and Reviews 5, no. 6 (2024): 5657–61. http://dx.doi.org/10.55248/gengpi.5.0624.1605.

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Quispe, Roberto, Kathia Reyes, Jimmy Cáceda, Jeyson Vásquez, Daniel Rodríguez, and Juan Chavez. "Sustainable convergence: artificial intelligence and circular economy." SCIÉNDO 27, no. 4 (2024): 557–64. https://doi.org/10.17268/sciendo.2024.091.

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Sipola, Juha, Minna Saunila, and Juhani Ukko. "Adopting artificial intelligence in sustainable business." Journal of Cleaner Production 426 (November 2023): 139197. http://dx.doi.org/10.1016/j.jclepro.2023.139197.

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Nashielly Yarzábal Coronel. "HydroHackathon Sustainable Solutions from Artificial Intelligence." Journal of Information Systems Engineering and Management 10, no. 29s (2025): 1–11. https://doi.org/10.52783/jisem.v10i29s.4433.

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In the midst of a global crisis due to the loss of social, environmental and economic balance, it is urgent to solve this situation with innovative and sustainable proposals that subscribe to the ODS, the HidroHackathon is an academic event where project proposals are developed through the Methodology STEAM-ABP with the Integration of Artificial Intelligence in this event achieves excellent results to create real effective solutions by subscribing with this to the ODS through the application We conclude that the AI application of the K-Means algorithm is fundamental for data analysis for the g

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Zheng, Xuetong, Qing Xu, and Rongchuan Pan. "Artificial Intelligence for Sustainable Building Materials." International Journal of Computer Science and Information Technology 6, no. 1 (2025): 24–29. https://doi.org/10.62051/ijcsit.v6n1.03.

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This paper reviews the role of artificial intelligence (AI), with a focus on machine learning (ML) and tools like ChatGPT, in advancing sustainable building materials. As the construction industry seeks to reduce its environmental footprint, AI offers innovative methods for discovering low-carbon alternatives, optimizing material composition, and designing bio-inspired structures. A narrative literature review was conducted, synthesizing peer-reviewed publications from 2014 to 2024. The findings are categorized into three main areas: low-carbon material discovery, ML-based material optimizatio

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Jonathan, Dr KN. "Artificial Intelligence Tools and Sustainable Development." Journal of Information and Technology 5, no. 5 (2025): 26–33. https://doi.org/10.70619/vol5iss5pp26-33.

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Artificial Intelligence (AI) has emerged as a transformative technology, playing a critical role in advancing sustainable development. This paper examines the intersection of AI tools and sustainable development, focusing on key areas such as environmental protection, resource management, and societal well-being. By leveraging AI for climate change mitigation, biodiversity conservation, and waste management, we can achieve significant environmental benefits. In resource management, AI enhances water resource management, agricultural practices, and sustainable urban planning. Additionally, AI c

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Ebule, Amejuma Emmanuel. "Business Intelligence and Artificial Intelligence for Sustainable Business Operations." International Journal of Scientific Research and Management (IJSRM) 13, no. 01 (2025): 1917–35. https://doi.org/10.18535/ijsrm/v13i01.ec05.

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In the modern business landscape, sustainability has become a fundamental goal for organizations, driven by growing environmental concerns, social responsibility, and the need for long-term profitability (Bocken et al., 2014). Companies are under increasing pressure to reduce their environmental footprint, optimize resources, and improve operational efficiency, all while maintaining competitiveness. Business Intelligence (BI) and Artificial Intelligence (AI) have emerged as key technologies in this transition, offering organizations the ability to make data-driven decisions that promote sustai

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Avetisyana, A. I. "Trusted artificial intelligence." Вестник Российской академии наук 94, no. 3 (2024): 200–209. http://dx.doi.org/10.31857/s0869587324030039.

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In this paper we discuss the problem of creating trusted artificial intelligence (AI) technologies. Modern AI is based on machine learning and neural networks and is vulnerable to biases and errors. Efforts are made to establish standards for the development of trusted AI technologies, but they have not yet succeeded. AI technologies trust can only be achieved with the appropriate scientific and technological base and corresponding tools and techniques for countering attacks. We present the ISP RAS Trusted AI Research Center results and propose a work model that can ensure technological indepe

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Rizzo, Santi Agatino. "To be Artificial Intelligence for sustainability or not to be sustainable Artificial Intelligence." Renewable and Sustainable Energy Reviews 223 (November 2025): 116063. https://doi.org/10.1016/j.rser.2025.116063.

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Liengpunsakul, Subin. "Artificial Intelligence and Sustainable Development in China." Chinese Economy 54, no. 4 (2021): 235–48. http://dx.doi.org/10.1080/10971475.2020.1857062.

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Nazarov, Anton, Denis Kovtun, and Stefan Talu. "Using artificial intelligence technologies for sustainable development." E3S Web of Conferences 291 (2021): 04010. http://dx.doi.org/10.1051/e3sconf/202129104010.

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Artificial intelligence as a simulator of human behavior and thinking emerged as a result of machine learning. Through AI, they recognize and interpret data, on the basis of which programs of various types of activities are subsequently built. The rapid introduction of artificial intelligence-based technologies into the economic and social spheres of the international community has not been left out of the United Nations’ view from the point of view of using the capabilities of digital computers to solve problems at the level of intelligent beings in order to achieve the goals of sustainable d

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Goel, Anushka, Geeta Raut, Asmita Sharma, and Udita Taneja. "Artificial Intelligence and Sustainable Business: A Review." South Asian Journal of Business and Management Cases 13, no. 3 (2024): 340–65. https://doi.org/10.1177/22779779241302146.

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Over recent years, there has been a significant increase in research exploring the impact of Artificial Intelligence in different business contexts. These intelligent machines can solve complex problems and are fast emerging in the business ecosystem. This study aims to explore the current literature on the sustainability of artificial Intelligence in the service context. In this regard, this study consolidates the extant literature, maps sustainable AI’s performance and intellectual framework, and addresses the extant gap. A corpus of 87 articles was identified using SPAR-4-SLR and was review

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Bencsik, Andrea, Viktor Busanszki, and Alzbeta Simon. "GNH and Artificial Intelligence for Sustainable Development." Proceedings International Conference on Business, Economics & Management, no. 1 (July 26, 2023): 453–70. http://dx.doi.org/10.47747/icbem.v1i1.1233.

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The objective of this research is application of Gross National Happiness (GNH) framework, grounded in the principles of Buddhist economics, in the Eastern European sustainable development context, specifically in Slovakia. This studies aim is to investigate the possibility of applying GNH framework in Slovakian environment. The research is an experimental study about the evaluation of the happiness index of Slovakian employees and employers of SMEs in Slovakia, in Rožňava region. The sustainable development in the region is lowest in the country, its' characterized by high unemployment rate,

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Siti Kustini, Rizky Amelia, Heppy Mutammimah, Rahma Pitria Ningsih, and Rini Amelia. "Artificial Intelligence Driven Learning for Sustainable Education:." Proceeding International Seminar of Science and Technology 4 (April 17, 2025): 25–36. https://doi.org/10.33830/isst.v4i1.5224.

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The integration of Artificial Intelligence (AI) with technology-enhanced learning platforms has the potential to improve education and presents a transformative approach to addressing educational challenges. Despite its beneficial impacts on education, concerns about students’ AI literacy have prompted empirical investigations on the perceived AI presences in connection with its usage, benefits, and related risks in classroom instructional practices. This study examined higher vocational students’ perceptions and attitudes on artificial intelligence-driven learning based on survey results. The

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Kambarbekov, G. М., and A. Ye Baimaganbetov. "USING ARTIFICIAL INTELLIGENCE FOR HYDROLOGICAL MODELLING." Geography and water resources, no. 1 (March 28, 2024): 58–62. http://dx.doi.org/10.55764/2957-9856/2024-1-58-62.8.

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Hydrological modelling plays a critical role in managing water resources, especially in arid and semi-arid regions where water scarcity is a major challenge. With the emergence of artificial intelligence (AI), hydrological modelling has experienced a significant transformation in recent years. This paper reviews the recent advances in AI-based hydrological modelling and examines its potential applications in water resource management. The study highlights the role of AI in enhancing the accuracy of hydrological models and facilitating more efficient and sustainable water management practices.

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Davidyuk, M. O., and E. I. Kozlova. "The impact of artificial intelligence on sustainable development." Innovative Economics and Law, no. 1 (2024): 76–80. https://doi.org/10.53015/2782-263x_2024_1_76.

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Subject. The study is devoted to analyzing the role and influence of artificial intelligence in the context of sustainable development of the modern economy. Goal. The purpose of this article is to identify prospects, challenges and innovative solutions associated with the use of artificial intelligence in the economy, with an emphasis on its role in sustainable development. Method or methodology. To achieve this goal, a comprehensive analysis is used, including a literature review of current research, analysis of statistical data, as well as a comparative analysis of successful cases of intro

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Brevini, Benedetta. "Inteligência Artificial, Soluções Artificiais - Colocando a emergência climática no centro dos desenvolvimentos de IA." Revista Mídia e Cotidiano 18, no. 2 (2024): 11–26. http://dx.doi.org/10.22409/rmc.v18i2.63056.

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Despite growing attention to the environmental costs of information communication technology systems, Artificial Intelligence gets principally heralded as the key technology to solve contemporary challenges, including the environmental crisis, which is one of the goals of sustainable development. But how green is Artificial Intelligence? This text considers the materiality of AI and attempts to go beyond mainstream hypes as it explores the multifaceted ways in which AI is impacting the climate emergency, thus impacting sustainable environmental development. It concludes by offering a set of so

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Pal Singh, Jatin. "Artificial Intelligence in Circular Economies: A Pathway to Sustainable Resource Management." International Journal of Science and Research (IJSR) 12, no. 12 (2023): 1128–31. http://dx.doi.org/10.21275/sr231214040053.

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Artha, Bhenu, Utami Tunjung Sari, Bahri Bahri, et al. "Artificial Intelligence and Sustainable Innovation: A Theoretical Review." Journal of Sustainable Innovation Engineering 1, no. 2 (2025): 39–43. https://doi.org/10.69693/sustainable.v1i2.12.

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Artificial intelligence (AI) has become universal across various sectors, permeating every aspect of our lives regardless of age or profession. In this era of AI, it's necessary to prioritize sustainable development and innovation in its application, while AI enables rapid completion of tasks alike human efficiency, it also raises concerns about increasing unemployment rates. A theoretical literature review is conducted in order to achieve the research's goals and objectives, and a conceptual framework for future study is offered. Authors conclude that artificial intelligence affects green pro

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Rieder, Emanuel, Matthias Schmuck, and Alexandru Tugui. "A Scientific Perspective on Using Artificial Intelligence in Sustainable Urban Development." Big Data and Cognitive Computing 7, no. 1 (2022): 3. http://dx.doi.org/10.3390/bdcc7010003.

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Digital transformation (or digitalization) is the process of continuous further development of digital technologies (such as smart devices, cloud services, and Big Data) that have a lasting impact on our economy and society. In this manner, digitalization is a huge driver for permanent change, even in the field of Sustainable Urban Development. In the wake of digitalization, expectations are changing, placing pressure at the societal level on the design and development of smart environments for everything that means Sustainable Urban Development. In this sense, the solution is the integration

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MEHTA, ANIRUDH, VARUN CHOUDHARY, MOAZAM NIAZ, and URENNA NWAGWU. "Artificial Intelligence Chatbots and Sustainable Supply Chain Optimization in Manufacturing: Examining the Role of Transparency, Innovativeness, and Industry 4.0 Advancements." ICONIC RESEARCH AND ENGINEERING JOURNALS 7, no. 1 (2023): 639–49. https://doi.org/10.5281/zenodo.14194113.

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Artificial intelligence chatbot systems have increased sales and customer engagement through sustainable supply chains. Industry 4.0 internetbased technology shares a lot of new opportunities for the growth of manufacturing organizations. Organizations are adopting these latest technologies to gain sustainability and competitive advantages in the supply chain. Artificial intelligence chatbots are providing help in accomplishing visibility in enhancing sustainability. Innovativeness is also helpful for improving the event's performance through technologies. This study also checks the implementa

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Kolesnikov, A. M., I. A. Kupriyanova, and P. S. Soroka. "ARTIFICIAL INTELLIGENCE IS A DRIVER OF SUSTAINABLE ECONOMIC DEVELOPMENT." ECONOMIC VECTOR 4, no. 35 (2023): 109–19. http://dx.doi.org/10.36807/2411-7269-2023-4-35-109-119.

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The article discusses the trends in the introduction and the need to use artificial intelligence to ensure sustainable economic development in the Russian Federation in 2023. The authors of the article systematized data on the fields of application of artificial intelligence, the experience of its use in Russia and abroad. The influence of artificial intelligence on the economy as a technology of the future is analyzed. A number of studies in the field of artificial intelligence are presented and data on the fields of application of artificial intelligence both in Russia and abroad are systema

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Fuentes-Penna, Alejandro, and Juan de Dios González Ibarra. "Personalized Education and Artificial Intelligence." International Journal of Combinatorial Optimization Problems and Informatics 15, no. 2 (2024): 1–12. http://dx.doi.org/10.61467/2007.1558.2024.v15i2.431.

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The Sustainable Development Goals (SDGs) are a universal call for action to end poverty, protect the planet, and improve people's quality of life. With the approval of the 17 SDGs as part of the 2030 Agenda for Sustainable Development, a plan was established to achieve them in 15 years. Quality Education (SDG 4) is fundamental to the development of people and societies, as it enables individuals to express themselves, actively participate in society, and make decisions that benefit their lives. Access to education is a determining factor in overcoming poverty and discrimination; it can improve

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Yang, Ying, Jinruo Qin, Jing Lei, and Yanping Liu. "Research Status and Challenges on the Sustainable Development of Artificial Intelligence Courses from a Global Perspective." Sustainability 15, no. 12 (2023): 9335. http://dx.doi.org/10.3390/su15129335.

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The widespread application of artificial intelligence technology in various fields has made the sustainable development of artificial intelligence courses an important direction in the field of artificial intelligence education and teaching. Therefore, it is particularly important to conduct an in-depth analysis of the current research status of “artificial intelligence courses” from a global perspective. Firstly, this article clarifies the three stages of slow development, rapid development, and mature development of artificial intelligence curriculum research through the number and distribut

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Gupta, Eva. "Smart Wardrobe System Using Artificial Intelligence." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem48062.

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Abstract—This paper introduces a smart wardrobe system powered by artificial intelligence, designed to simplify wardrobe management and promote sustainable fashion. Using a ResNet- 50 convolutional neural network for clothing recognition and a hybrid recommendation engine, the system reduces outfit selection time by 40% and increases wardrobe utilization by 15%, as validated with 200 users. Despite a 5% error rate with unconventional garments, this research paves the way for innovations like smart mirrors, enhancing both convenience and environmental consciousness. Index Terms—Smart wardrobe,

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Sharma, Ashutosh, Elizaveta Podoplelova, Gleb Shapovalov, Alexey Tselykh, and Alexander Tselykh. "Sustainable Smart Cities: Convergence of Artificial Intelligence and Blockchain." Sustainability 13, no. 23 (2021): 13076. http://dx.doi.org/10.3390/su132313076.

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Recently, 6G-enabled Internet of Things (IoT) is gaining attention and addressing various challenges of real time application. The artificial intelligence plays a significant role for big data analytics and presents accurate data analysis in real time. However, designing big data analysis through artificial intelligence faces some issues in terms of security, privacy, training data, and centralized architecture. In this article, blockchain-based IoT framework with artificial intelligence is proposed which presents the integration of artificial intelligence and blockchain for IoT applications.

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Shlapak, Alla, Artur Zhavoronok, Natalia Vdovenko, Oleksiy Bilousov, Dmytro Horban, and Denys Krylov. "impact of digital technologies and artificial intelligence on the management of socioeconomic processes in the context of sustainable development." Journal on Innovation and Sustainability RISUS 16, no. 2 (2025): 180–93. https://doi.org/10.23925/2179-3565.2025v16i2p180-193.

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The modern world is experiencing transition to the digital economy, where digital technologies and artificial intelligence play the key role in transformation of socio-economic processes. These technologies allow states optimizing resource management, automating production and administrative processes, increasing efficiency of urban governance, and ensuring inclusive sustainable development. In the article, the impact of digital technologies and artificial intelligence on formation of modern development strategies, in particular in the aspect of sustainable urban and economic governance is ana

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Avurakoghene, Onome Peace, and Afolakemi Olasumbo Oredein. "Educational Leadership and Artificial Intelligence for Sustainable Development." Shodh Sari-An International Multidisciplinary Journal 02, no. 03 (2023): 211–23. http://dx.doi.org/10.59231/sari7600.

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The imperativeness of educational leadership and artificial intelligence in contemporary society cannot be overstated in the quest for sustainable development, given the pivotal role of education in achieving the stated developmental objectives. Sadly, educational leaders in Nigeria face several challenges in maximizing the use of AI for sustainable development. This has not only influenced their effectiveness negatively but has equally deprived them of optimal achievement of the objectives of education in the country, considering the roles of teachers in education service delivery. Using a qu

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Hofkirchner, Wolfgang. "Intelligence, Artificial Intelligence and Wisdom in the Global Sustainable Information Society." Proceedings 47, no. 1 (2020): 39. http://dx.doi.org/10.3390/proceedings2020047039.

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The Global Sustainable Information Society is a theoretical concept describing the vision of a good society in the age of global challenges. Globality, sustainability and informationality are understood in an innovative way as essential features of a world society to come that is capable of mastering the global challenges. Regarding informationality, the distinction between informedness and informatisation is made and a law of requisite information is introduced. The terms “intelligence”, “Artificial Intelligence” (AI) and “wisdom” are discussed from the perspective of complex systems. Intelli

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Hofkirchner, Wolfgang. "Intelligence, Artificial Intelligence and Wisdom in the Global Sustainable Information Society." Proceedings 47, no. 1 (2020): 39. http://dx.doi.org/10.3390/proceedings47010039.

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The Global Sustainable Information Society is a theoretical concept describing the vision of a good society in the age of global challenges. Globality, sustainability and informationality are understood in an innovative way as essential features of a world society to come that is capable of mastering the global challenges. Regarding informationality, the distinction between informedness and informatisation is made and a law of requisite information is introduced. The terms “intelligence”, “Artificial Intelligence” (AI) and “wisdom” are discussed from the perspective of complex systems. Intelli

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Yñiguez-Ovando, Rocío, Eva Maria Buitrago-Esquinas, Miguel Puig-Cabrera, Margarida Custódio Santos, and José António C. Santos. "Artificial Intelligence and Sustainable Tourism Planning: A Hetero-Intelligence Methodology Proposal." Tourism & Management Studies 20, SI (2024): 45–59. http://dx.doi.org/10.18089/tms.2024si04.

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This study explores the growing significance of Large Language Models (LLMs) in tourism, for their current and potential applications. It aims to achieve two primary objectives: first, to develop a novel hetero-intelligence framework merging human and artificial intelligence (AI) to address contemporary sustainability challenges in tourism; second, to validate this framework by applying it to sustainable tourism planning, assessing LLMs' capabilities and limitations. The research employs a hetero-intelligence performance test, contrasting human intelligence and AI contributions in sustainable

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Rohde, Friederike, Josephin Wagner, Andreas Meyer, et al. "Broadening the perspective for sustainable artificial intelligence: sustainability criteria and indicators for Artificial Intelligence systems." Current Opinion in Environmental Sustainability 66 (February 2024): 101411. http://dx.doi.org/10.1016/j.cosust.2023.101411.

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Harsha Jupalli, Pranay. "Harnessing Artificial Intelligence & Big Data for Sustainable Finance & Risk Management." International Journal of Science and Research (IJSR) 13, no. 7 (2024): 518–25. http://dx.doi.org/10.21275/sr24708233123.

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Jalin Sharmila, S. R., and S. Sam Santhose. "The Role of Artificial Intelligence in Sustainable Finance." Thiagarajar College of Preceptors Edu Spectra 7, S1 (2025): 61–66. https://doi.org/10.34293/eduspectra.v7is1-feb25.008.

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Artificial Intelligence (AI) plays a transformative role in sustainable finance by enhancing decision-making, risk assessment, and ESG (Environmental, Social, and Governance) integration. AI driven algorithms analyze vast datasets to identify sustainable investment opportunities, detect greenwashing, and optimize portfolio management for long-term environmental and financial benefits. Machine learning models improve climate risk forecasting, helping financial institutions mitigate sustainability-related risks. Additionally, AI-powered automation enhances regulatory compliance and sustainable r

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Abbasova Sakina, Murtazalieva Zumrud, Abbasova Sakina, Murtazalieva Zumrud, and Medzhidova Sevinj, Leonyuk Irina Medzhidova Sevinj, Leonyuk Irina. "USING ARTIFICIAL INTELLIGENCE FOR A SUSTAINABLE GREEN FUTURE." PAHTEI-Procedings of Azerbaijan High Technical Educational Institutions 52, no. 04-02 (2025): 56–61. https://doi.org/10.36962/pahtei5204-022025-56.

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The article is devoted to the problems of using artificial intelligence in projects of a sustainable green future. First, the main goals (standards) of the development area of a sustainable green future approved by the UN General Assembly are explained. These standards also serve as a mechanism for implementing the main goals of "green" design and regulators for the creation of environmentally friendly objects. Then, a number of aspects of using artificial intelligence in green technologies, as well as in the creation of "smart" objects, are considered Keywords: Sustainable future, green techn

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Marvin, Hans J. P., Yamine Bouzembrak, H. J. van der Fels-Klerx, et al. "Digitalisation and Artificial Intelligence for sustainable food systems." Trends in Food Science & Technology 120 (February 2022): 344–48. http://dx.doi.org/10.1016/j.tifs.2022.01.020.

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BRAN, Florina, Dumitru Alexandru BODISLAV, Svetlana GOMBOS, and Sorin Petrică ANGHELUȚĂ. "Artificial Intelligence for Sustainable Agribusiness: Innovations and Challenges." European Journal of Sustainable Development 13, no. 3 (2024): 233. http://dx.doi.org/10.14207/ejsd.2024.v13n3p233.

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The integration of artificial intelligence (AI) in sustainable agribusiness is examined in this research, with particular attention paid to robots, supply chain management, and precision agriculture. AI analyzes a variety of datasets, maximizes resource utilization, forecasts pest outbreaks and production changes, and allows for data-driven decision-making. AI improves supply chain management by lowering food loss, streamlining logistics, and guaranteeing on-time delivery. Robotics powered by AI revolutionize labor-intensive processes, increasing output while reducing the need for chemicals. N

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Hermosa Del Vasto, Paola Marcela, and María Lourdes Arco Castro. "ARTIFICIAL INTELLIGENCE (AI) IN SUSTAINABLE TOURISM: BIBLIOMETRIC ANALYSIS." Cuadernos de Turismo, no. 53 (June 28, 2024): 157–85. http://dx.doi.org/10.6018/turismo.616431.

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Artificial Intelligence (AI) has gained attention in tourism, which requires its sustainability. Our study focuses on a bibliometric analysis of AI in sustainable tourism using 174 manuscripts from 2000 to 2022. One of the main findings is that 'intelligence' appears frequently, followed by related terms such as work, performance, resources, sustainability, impact, optimization and management. There is no previous evidence on AI in the context of sustainable tourism to explain how public managers or politicians design public policies to create and improve resource efficiency. La Inteligencia A

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Albaaji, Ghassan Faisal, and Vinod Chandra S.S. "Artificial intelligence SoS framework for sustainable agricultural production." Computers and Electronics in Agriculture 213 (October 2023): 108182. http://dx.doi.org/10.1016/j.compag.2023.108182.

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Kunkel, Stefanie, Frieder Schmelzle, Silke Niehoff, and Grischa Beier. "More sustainable artificial intelligence systems through stakeholder involvement?" GAIA - Ecological Perspectives for Science and Society 32, no. 1 (2023): 64–70. http://dx.doi.org/10.14512/gaia.32.s1.10.

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Artificial intelligence (AI) systems carry risks and opportunities for environmental sustainability. The use of AI systems, for instance, can result in both software-related (direct) as well as application-context-related (indirect) resource use. Stakeholders are expected to play a role in understanding and steering the environmental effects of AI systems. However, the processes and anticipated outcomes of stakeholder involvement in AI system lifecycles are not clear. We provide a non-exhaustive scoping review of six software and AI sustainability frameworks with respect to their recognition o

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Ibrahim, Umar. "Artificial Intelligence in Agricultural Extension for Sustainable Development." International Journal of Applied and Scientific Research 1, no. 3 (2023): 259–68. http://dx.doi.org/10.59890/ijasr.v1i3.740.

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The intersection of Artificial Intelligence (AI) and Agricultural Extension holds immense potential for enhancing sustainable development in the agricultural sector. This paper explores the transformative role of AI in agricultural extension services and its implications for sustainable development. Through a comprehensive literature review, data analysis, and case studies, we assess the current state of AI applications in agriculture and highlight the gaps and challenges in this field. Our study reveals that AI technologies offer innovative solutions for knowledge dissemination, decision supp

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Chen, Long, Yuting Xie, Yutong Wang, Shirong Ge, and Fei-Yue Wang. "Sustainable Mining in the Era of Artificial Intelligence." IEEE/CAA Journal of Automatica Sinica 11, no. 1 (2024): 1–4. http://dx.doi.org/10.1109/jas.2023.124182.

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Kaur, Swapandeep, Raman Kumar, Kanwardeep Singh, and Yinglai Huang. "Leveraging Artificial Intelligence for Enhanced Sustainable Energy Management." Journal of Sustainability for Energy 3, no. 1 (2024): 1–20. http://dx.doi.org/10.56578/jse030101.

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Ibrahim, Umar. "Artificial Intelligence in Agricultural Extension for Sustainable Development." Artificial Intelligence in Agricultural Extension for Sustainable Development 1, Vol. 1 No. 3 (2023): November 2023 (2024): 10. https://doi.org/10.59890/ijasr.v1i3.740.

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The intersection of Artificial Intelligence (AI) and Agricultural Extension holds immense potential for enhancing sustainable development in the agricultural sector. This paper explores the transformative role of AI in agricultural extension services and its implications for sustainable development. Through a comprehensive literature review, data analysis, and case studies, we assess the current state of AI applications in agriculture and highlight the gaps and challenges in this field. Our study reveals that AI technologies offer innovative solutions for knowledge dissemination, decision supp

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Jack, Huang1* Masato Abe2. "Artificial Intelligence: A Transformative Force for Sustainable Development." UAI Journal of Economics, Business and Management (UAIJEBM) 1, no. 2 (2025): 1–8. https://doi.org/10.5281/zenodo.15285929.

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<em>Artificial intelligence (AI) is a transformative force with the potential to accelerate progress toward the United Nations' Sustainable Development Goals (SDGs). AI's capacity for data analytics and predictive modeling can enhance decision-making and resource allocation across various sectors. This chapter examines AI's role in advancing the SDGs, particularly in healthcare, education, and environmental management, while addressing challenges related to ethical considerations and equitable access. It incorporates evidence from various research reports and global frameworks, adopting the ca

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Artificial, Intelligence: A. Transformative Force for Sustainable Development Jack Huang1* Masato Abe2. "Artificial Intelligence: A Transformative Force for Sustainable Development." UAI Journal of Arts, Humanities and Social Sciences (UAIJAHSS) 1, no. 2 (2025): 1–8. https://doi.org/10.5281/zenodo.15285993.

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<em>Artificial intelligence (AI) is a transformative force with the potential to accelerate progress toward the United Nations' Sustainable Development Goals (SDGs). AI's capacity for data analytics and predictive modeling can enhance decision-making and resource allocation across various sectors. This chapter examines AI's role in advancing the SDGs, particularly in healthcare, education, and environmental management, while addressing challenges related to ethical considerations and equitable access. It incorporates evidence from various research reports and global frameworks, adopting the ca

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Dr.Parturkar, M.S. "Artificial Intelligence In Supporting Sustainable Business Model's Development." International Journal of Advance and Applied Research S6, no. 13 (2025): 14–16. https://doi.org/10.5281/zenodo.14912780.

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<em>This research paper aims to shed light on the pivotal role played by artificial intelligence (AI) in supporting sustainable business models’ development. It delves into the opportunities AI presents in terms of efficiency, innovation, and problem-solving. However, the paper also acknowledges the critical concerns surrounding AI, including ethical implications, job displacement, and potential biases. By examining the current state of AI research and Business development, the paper proposes a vision policy to guide responsible AI adoption. A comprehensive research methodology is outlin

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