Bibliografías temáticas / Sustainable artificial intelligence

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Literatura académica sobre el tema "Sustainable artificial intelligence"

Autor: Grafiati
Publicado: 7 de junio de 2025
Última modificación: 2 de agosto de 2025

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Artículos de revistas sobre el tema "Sustainable artificial intelligence"

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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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Tesis sobre el tema "Sustainable artificial intelligence"

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Haidar, Ahmad. "Responsible Artificial Intelligence : Designing Frameworks for Ethical, Sustainable, and Risk-Aware Practices." Electronic Thesis or Diss., université Paris-Saclay, 2024. https://www.biblio.univ-evry.fr/theses/2024/interne/2024UPASI008.pdf.

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L'intelligence artificielle (IA) transforme rapidement le monde, redéfinissant les relations entre technologie et société. Cette thèse explore le besoin essentiel de développer, de gouverner et d'utiliser l'IA et l'IA générative (IAG) de manière responsable et durable. Elle traite des risques éthiques, des lacunes réglementaires et des défis associés aux systèmes d'IA, tout en proposant des cadres concrets pour promouvoir une Intelligence Artificielle Responsable (IAR) et une Innovation Numérique Responsable (INR).La thèse commence par une analyse approfondie de 27 déclarations éthiques mondia
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Ruberg, Nicolaas. "Bert goes sustainable: an NLP approach to ESG financing." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/24787/.

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Environmental, Social, and Governance (ESG) factors are a strategic topic for investors and financing institutions like the Brazilian Development Bank (BNDES). Currently, the bank’s experts are developing a framework based on those factors to assess companies' sustainable financing. We identify an opportunity to use Natural Language Processing (NLP) in this development. This opportunity arises from the observation that a critical document to the ESG analysis is the company annual activity report. This document undergoes a manual screening, and later it is decomposed, and its parts are redirect
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Russo, Inês Filipa Duarte. "O impacte da inteligência artificial na sustentabilidade ambiental : uma agricultura sustentável." Master's thesis, Instituto Superior de Economia e Gestão, 2020. http://hdl.handle.net/10400.5/21023.

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Mestrado em Gestão de Sistemas de Informação<br>Para lidar com o aumento da procura e de várias tendências disruptivas com sucesso, a indústria agrícola precisará superar os desafios de uma implementação de conectividade avançada. O presente estudo tem assim as seguintes questões de investigação: 1. Como pode a IA contribuir para uma gestão sustentável da agricultura? 2. Como introduzir o uso de IA na agricultura de uma forma continuada? E tem como objetivos de investigação: 1.Analisar as principais características das ferramentas baseadas em IA que permitem uma gestão sustentável da agricultu
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Kamal, Khurram. "Utilisation of embedded information devices to support a sustainable approach to product life-cycle management." Thesis, Loughborough University, 2008. https://dspace.lboro.ac.uk/2134/8137.

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The huge landfills from solid waste generated by the massive utilisation of different products from domestic sources are badly affecting the environment. About 70% of the solid municipal waste, two thirds of which comprises of household waste, is dumped as landflll all over the world. For efficient product lifecycle management via upgrade, maintenance, reuse, refurbishment, and reclamation of components etc., storage of product related information throughout its lifecycle is indispensable. Efficient use of information technology integrated with product design can enable products to manage them
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Riffelli, Stefano. "Sustainable comfort in indoor environments: global comfort indices and virtual sensors." Doctoral thesis, Urbino, 2022. http://hdl.handle.net/11576/2700929.

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MULK, MAISHA, and JONSSON AMANDA SKÄRBO. "Integrering av ekologiska aspekter vid produktutveckling av AI-baserade produkter." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279763.

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Under det senaste decenniet har artificiell intelligens fått allt större uppmärksamhet. Företag väljer att implementera system med kognitiva egenskaper för att kunna reglera energianvändning och därmed reducera det ekologiska fotavtrycket. Fyra stora internationella företag har intervjuats för att undersöka hur AI i produkter påverkar det ekologiska fotavtrycket och hur integreringen av ekologiska faktorer tas i beaktande under produktutvecklingsprocessen. Utöver intervjustudien har en kvalitativ litteraturstudie genomförts för att både belysa hur företag arbetar kring ämnet men också för att
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Bichraoui-Draper, Najet. "Computational sustainability assessment : agent-based models and agricultural industrial ecology." Thesis, Troyes, 2015. http://www.theses.fr/2015TROY0005/document.

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Cette thèse porte sur le développement d'une approche de modélisation destinée à quantifier la durabilité de systèmes industriels à partir de biomasse (considérés comme des systèmes complexes), et à fournir un outil d’aide à la décision qui permette, en modifiant certaines de leurs caractéristiques, de diminuer leurs impacts environnementaux.Elle s’appuie sur deux études de cas régionales : la première permet de tester l’hypothèse théorique pour évaluer les facteurs qui contribuent à l’adoption par les agriculteurs du « panic érigé » (switchgrass) dans l’Etat du Michigan (USA), et les effets a
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Chollet, Nicolas. "Embedded-AI-enabled semantic IoT platform for agroecology." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG078.

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L'agriculture moderne nécessite une profonde transformation pour répondre aux défis du développement durable tout en nourrissant qualitativement et quantitativement la population mondiale croissante. Dans cette optique, les agriculteurs adoptent le "Smart Farming" ou agriculture intelligente. C'est une méthode agricole qui utilise la technologie pour améliorer l'efficacité, la productivité et la durabilité de la production agricole. Elle englobe l'usage de capteurs, l'internet des objets (IoT), l'Intelligence Artificielle (IA), l'analyse de données, la robotique et divers autres outils numériq
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Narmack, Kirilll. "Dynamic Speed Adaptation for Curves using Machine Learning." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233545.

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The vehicles of tomorrow will be more sophisticated, intelligent and safe than the vehicles of today. The future is leaning towards fully autonomous vehicles. This degree project provides a data driven solution for a speed adaptation system that can be used to compute a vehicle speed for curves, suitable for the underlying driving style of the driver, road properties and weather conditions. A speed adaptation system for curves aims to compute a vehicle speed suitable for curves that can be used in Advanced Driver Assistance Systems (ADAS) or in Autonomous Driving (AD) applications. This degree
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Politt, Clemens Carl Emil. "Introducing Artificial Intelligence into sustainable business models : development of an artifact to facilitate sustainable business model innovation." Master's thesis, 2020. http://hdl.handle.net/10400.14/31145.

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Through the rise of sustainable business models, social and environmental dimensions made their way into the renowned research field of business models and business model innovation. Thereby, sustainable business model patterns can support the challenging process of designing and innovating appropriate sustainable business models. While it seems to be a promising approach to employ artificial intelligence and machine learning for sustainable business model innovation, a generally acknowledged lack of corresponding support systems exists. Therefore, this study addresses the development of
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Libros sobre el tema "Sustainable artificial intelligence"

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Tiwari, Sanju, Fernando Ortiz-Rodríguez, Sashikala Mishra, Edlira Vakaj, and Ketan Kotecha, eds. Artificial Intelligence: Towards Sustainable Intelligence. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-47997-7.

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Tiwari, Sanju, Fernando Ortiz-Rodriguez, Miguel-Angel Sicilia, and Tek Raj Chhetri, eds. Artificial Intelligence: Towards Sustainable Intelligence. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-81369-6.

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Tsafack Chetsa, Ghislain Landry. Towards Sustainable Artificial Intelligence. Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-7214-5.

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Dubey, Hari Mohan, Manjaree Pandit, Laxmi Srivastava, and Bijaya Ketan Panigrahi, eds. Artificial Intelligence and Sustainable Computing. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-1220-6.

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Pandit, Manjaree, M. K. Gaur, Prashant Singh Rana, and Akhilesh Tiwari, eds. Artificial Intelligence and Sustainable Computing. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1653-3.

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Pandit, Manjaree, M. K. Gaur, and Sandeep Kumar, eds. Artificial Intelligence and Sustainable Computing. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-0327-2.

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Haldorai, Anandakumar, Babitha Lincy R, Suriya Murugan, and Minu Balakrishnan. Artificial Intelligence for Sustainable Development. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-53972-5.

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Mathew, Jimson, Lenin Gopal, and Filbert H. Juwono, eds. Artificial Intelligence for Sustainable Energy. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-9833-3.

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Pandit, Manjaree, M. K. Gaur, and Sandeep Kumar, eds. Artificial Intelligence and Sustainable Computing. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1431-9.

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Pandit, Manjaree, M. K. Gaur, and Sandeep Kumar, eds. Artificial Intelligence and Sustainable Computing. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-3333-3.

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Capítulos de libros sobre el tema "Sustainable artificial intelligence"

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Demirel, Yaşar, and Marc A. Rosen. "Artificial Intelligence." In Sustainable Engineering. CRC Press, 2023. http://dx.doi.org/10.1201/9781003191124-8.

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Brevini, Benedetta. "Artificial Intelligence, Artificial Solutions." In Technology and Sustainable Development. Routledge, 2023. http://dx.doi.org/10.1201/9781003325086-3.

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de Bem Machado, Andreia, Gertrudes Aparecida Dandolini, João Artur de Souza, Miltiades Demetrios Lytras, and Maria José Sousa. "Artificial Intelligence." In Technologies for Sustainable Global Higher Education. Auerbach Publications, 2023. http://dx.doi.org/10.1201/9781003424543-11.

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Ahmareen, Shafaque, Sirisha Potluri, and Alreem Khalid Khamies Alabdouli. "Artificial Intelligence." In AI in Agriculture for Sustainable and Economic Management. CRC Press, 2024. http://dx.doi.org/10.1201/9781003451648-1.

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Hamid, Kanchan Bhatt, Naseer Ahmed, and Priyanka Chauhan. "Green Artificial Intelligence." In Artificial Intelligence Techniques for Sustainable Development. CRC Press, 2024. http://dx.doi.org/10.1201/9781003546382-15.

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Zafar, Sarvat, and Nadim Rana. "Artificial Intelligence in Material Science." In Sustainable Materials. CRC Press, 2024. http://dx.doi.org/10.1201/9781003437369-1.

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Waser, Mark R. "Instructions for Engineering Sustainable People." In Artificial General Intelligence. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09274-4_21.

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Yigitcanlar, Tan. "Artificial Intelligence and Sustainable Development Goals." In Urban Artificial Intelligence. CRC Press, 2024. http://dx.doi.org/10.1201/9781003521440-10.

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Harish, V., Ravindra Sharma, Geeta Rana, and Anand Nayyar. "Artificial Intelligence in Sustainable Education." In The Role of Sustainability and Artificial Intelligence in Education Improvement. Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003425779-12.

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Zinke-Wehlmann, Christian, Julia Friedrich, Amit Kirschenbaum, Mandy Wölke, and Anja Brückner. "Conceptualizing Sustainable Artificial Intelligence Development." In Collaborative Networks in Digitalization and Society 5.0. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-14844-6_43.

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Actas de conferencias sobre el tema "Sustainable artificial intelligence"

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Labib, Wafa Abdelmajeed, and Moayad Alhasan. "Adapting Artificial Intelligence Towards Managing Sustainable Construction." In 2025 Eighth International Women in Data Science Conference at Prince Sultan University (WiDS PSU). IEEE, 2025. https://doi.org/10.1109/wids-psu64963.2025.00022.

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Venayagamoorthy, Ganesh Kumar. "Cellular Computational Networks for Sustainable Artificial Intelligence." In 2025 IEEE Conference on Artificial Intelligence (CAI). IEEE, 2025. https://doi.org/10.1109/cai64502.2025.00238.

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Gupta, Shipra, and Vijay Kumar. "Digitalization and Artificial Intelligence in Sustainable Development Goals." In 2024 4th International Conference on Soft Computing for Security Applications (ICSCSA). IEEE, 2024. https://doi.org/10.1109/icscsa64454.2024.00032.

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Hariharan, Shanmugasundaram, Pogula Srivani, Sreenivasulu Gogula, N. Venkateswaran, Vinay Kukreja, and Jose P. "Sustainable Smart Agriculture Advisor through Artificial Intelligence Approach." In 2024 International Conference on Distributed Systems, Computer Networks and Cybersecurity (ICDSCNC). IEEE, 2024. https://doi.org/10.1109/icdscnc62492.2024.10939809.

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Arslan, Muhammad, Saba Munawar, and Zainab Riaz. "Sustainable Urban Water Decisions Using Generative Artificial Intelligence." In 2024 International Conference on Decision Aid Sciences and Applications (DASA). IEEE, 2024. https://doi.org/10.1109/dasa63652.2024.10836374.

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Lalitha, Valapula, Regidi Suneetha, Basi Reddy A, Nilesh R. Mate, and Syeeda Mujeebunnisa. "Integrating Artificial Intelligence for Sustainable and Adaptable Architecture." In 2024 Second International Conference Computational and Characterization Techniques in Engineering & Sciences (IC3TES). IEEE, 2024. https://doi.org/10.1109/ic3tes62412.2024.10877541.

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Garg, Apeksha, and Sudha Vemaraju. "Artificial Intelligence Applications in Predictive Maintenance for Sustainable Logistics." In 2024 IEEE 4th International Conference on ICT in Business Industry & Government (ICTBIG). IEEE, 2024. https://doi.org/10.1109/ictbig64922.2024.10911124.

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Vaidya, Gauri, Meghana Kshirsagar, and Conor Ryan. "PurGE: Towards Responsible Artificial Intelligence Through Sustainable Hyperparameter Optimization." In 17th International Conference on Agents and Artificial Intelligence. SCITEPRESS - Science and Technology Publications, 2025. https://doi.org/10.5220/0013262100003890.

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Chandar S, Kumar. "Artificial Intelligence Driven Air Quality Prediction for Sustainable Goa." In 2025 Third International Conference on Augmented Intelligence and Sustainable Systems (ICAISS). IEEE, 2025. https://doi.org/10.1109/icaiss61471.2025.11041723.

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Indumathi, P., M. Suresh Kumar, M. Umamaheswari, A. Anisha Alex, B. Adalarasu, and S. Thangamani. "Sustainable Business Approaches for FMCG Companies Leveraging Artificial Intelligence." In 2025 7th International Conference on Intelligent Sustainable Systems (ICISS). IEEE, 2025. https://doi.org/10.1109/iciss63372.2025.11076260.

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Informes sobre el tema "Sustainable artificial intelligence"

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Vargas, Fernando, and Arturo Muente. Artificial Intelligence Framework for the Inter-American Development Group. Inter-American Development Bank, 2025. https://doi.org/10.18235/0013377.

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Artificial intelligence (AI) has the potential to become a transformative general-purpose technology, reshaping economic, social, and institutional frameworks globally. The Inter-American Development Bank Group (IDBG) recognizes the urgency of fostering AI adoption in Latin America and the Caribbean to catalyze productivity, inclusion, and sustainable development. This document provides a high-level strategic framework to guide IDBGs interventions in advancing AI adoption and responsible use across the region. The document reviews key challenges facing the three dimensions of AI institutions a
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Mehmood, Hamid, Surya Karthik Mukkavilli, Ingmar Weber, et al. Strategic Foresight to Applications of Artificial Intelligence to Achieve Water-related Sustainable Development Goals. United Nations University Institute for Water, Environment and Health, 2020. http://dx.doi.org/10.53328/lotc2968.

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The report recommends that: 1) Policymakers should conduct holistic assessments of social, economic, and cultural factors before AI adoption in the water sector, as prospective applications of AI are case- specific. It is also important to conduct baseline studies to measure the implementation capacity, return on investment, and impact of intervention. 2) To ensure positive development outcomes, policies regarding the use of AI for water-related challenges should be coupled with capacity and infrastructure development policies. Capacity development policies need to address the AI and Informati
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JOSI, Editor. How GPT Aligns with the United Nations' Sustainable Development Goals (SDGs). Industrial Engineering Department, Faculty of Engineering, Universitas Andalas, 2024. https://doi.org/10.25077/27122024.

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The United Nations' Sustainable Development Goals (SDGs) provide a global framework for addressing critical challenges such as economic growth, innovation, and sustainability. Industrial engineering plays a pivotal role in achieving these goals, particularly by optimizing systems, improving operational efficiency, and fostering innovation. Generative Pre-trained Transformers (GPT), as a cutting-edge artificial intelligence (AI) technology, are uniquely positioned to support industries in making meaningful progress toward these objectives.
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Latorre, Lucia, Carlo Magno Rivera Picado, and Emeli Florencia Ozcoidi. Green IT Strategies: Innovating for a Sustainable Digital Future. Inter-American Development Bank, 2025. https://doi.org/10.18235/0013611.

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This report explores the main areas of intervention of Green IT, such as the mapping of carbon emissions throughout the value chain, the virtualization of physical resources, the adoption of cloud computing services, and the design of green data centers that include sustainability criteria. Risks and consequences associated with greater digitalization are also identified, such as the rebound effect and the growth in the volume of data stored, even those without real use (“dark data”), as well as the ambivalent role of emerging technologies such as artificial intelligence and blockchain, whose
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Sangem, Monika. A Literature Review on Role of Artificial Intelligence in Optimization of Renewable Energy Generation for the Future of Sustainable Environment. Iowa State University, 2024. https://doi.org/10.31274/cc-20250502-54.

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Saba, Tania, Anne-Marie Hubert, and Myriam Bernet. Shaping Human Capital Standards: Exploring the Intersections of the Future of Work and Artificial Intelligence. Observatoire international sur les impacts sociétaux de l'intelligence artificielle et du numérique, 2024. https://doi.org/10.61737/nnso3210.

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This study represents a foundational phase in a broader research program designed to guide investors and policymakers in the development of human capital standards. By examining the critical intersections between the future of work and artificial intelligence (AI), it investigates how technological advancements are reshaping workforce dynamics, redefining skill requirements, and influencing human capital strategies. In this initial stage, the study focuses on key issues, including the assessment of risks, opportunities, and uncertainties associated with the integration of AI into workplace pra
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Gidwani, Mohit, Narine Avetisyan, Yoonee Jeong, and Christine Apikul. The Emerging Data Center Market in Armenia and Opportunities for Sustainable Growth. Asian Development Bank, 2024. https://doi.org/10.22617/brf240515-2.

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This brief analyzes Armenia’s emerging data center market and shows why it needs to expand its green energy, adopt carbon-efficient technology, and accommodate the latest technology trends to maximize its growth potential. The brief highlights forecasts for Armenia to increase its data center racks from 550 to up to 2,000 by 2028 and explains how its location alongside government support and financing gives it a competitive advantage. It recommends Armenia look to enhance its resilient international connectivity, accommodate generative artificial intelligence and edge computing requirements, a
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Tjondronegoro, Dr Dian Wirawan. Navigating AI risks for sustainable productivity and resilience. Asian Productivity Organization, 2025. https://doi.org/10.61145/occa6400.

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In Navigating AI Risks for Sustainable Productivity and Resilience, Dr. Dian Wirawan Tjondronegoro presents a structured framework for integrating artificial intelligence (AI) into organizations while mitigating associated risks. The report outlines three interdependent frameworks—EPIC (Education, Partnership, Infrastructure, Community), TOAST (Trustworthy, Optimised, Adaptable, Socio-Technological), and RAIIF (Responsible AI Implementation Framework)—which collectively support AI readiness, responsible governance, and continuous adaptation. Emphasizing the socio-technical nature of AI, the pu
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Pasupuleti, Murali Krishna. AI and Quantum-Nano Frontiers: Innovations in Health, Sustainability, Energy, and Security. National Education Services, 2025. https://doi.org/10.62311/nesx/rr525.

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Abstract: This research report explores transformative advancements at the intersection of Artificial Intelligence (AI), Quantum Computing, and Nanotechnology, focusing on breakthrough innovations in health, sustainability, energy, and global security. By integrating quantum algorithms, AI-driven analytics, and advanced nanomaterials, this report highlights revolutionary solutions in precision medicine, predictive diagnostics, sustainable energy storage, universal water purification, and cybersecurity. Real-world case studies and emerging technologies such as graphene-based nanomaterials, quan
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Quimba, Francis Mark, Ramonette Serafica, Connie Bayudan-Dacuycuy, Abigail Andrada, and Neil Irwin Moreno. Green and Digital: Managing the Twin Transition toward Sustainable Development. Philippine Institute for Development Studies, 2023. http://dx.doi.org/10.62986/dp2023.21.

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The global shift toward sustainability and increased digitalization is evident. Nations are integrating renewable energy, carbon emission reduction, and advancements in green technologies into their development plans. Simultaneously, Industry 4.0 has revealed the diverse ways technology influences human life. Rather than separate factors, these dual forces are interconnected elements that countries must navigate for sustainable progress. As countries pursue development strategies, taking a closer look at this twin phenomenon is important. This study assesses how investments, labor, science, te
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