Mitigating Cyber Risks in AI-Driven Circular Economy Implementations
pdf (English)

Słowa kluczowe

AI
CE
cyberrisk

Kategorie

Jak cytować

Bashynska, I. i Prokopenko, O. (2024) „Mitigating Cyber Risks in AI-Driven Circular Economy Implementations”, Zeszyty Naukowe Wyższej Szkoły Finansów i Prawa w Bielsku-Białej. Bielsko-Biała, PL, 28(4). doi: 10.19192/wsfip.sj4.2024.10.

Abstrakt

This article explores the integration of artificial intelligence (AI) into circular economy (CE) systems, focusing on its potential to enhance sustainability by optimizing resource utilization, reducing waste, and improving supply chain processes. It highlights how AI-driven innovations such as predictive maintenance, waste sorting, and big data analytics contribute to the effective implementation of CE principles. At the same time, the study addresses the cybersecurity risks associated with these systems, including data breaches, system vulnerabilities, and ethical concerns. The research underscores the importance of adopting robust cybersecurity frameworks, such as the NIST AI Risk Management Framework and ISO/IEC 27001, to mitigate these risks and ensure the scalability and sustainability of AI-driven CE initiatives. Additionally, the article examines public perceptions of AI's societal impact, revealing optimism about productivity and efficiency but concerns regarding job market disruptions. Recommendations for organizations include proactive cybersecurity strategies, leveraging emerging technologies like blockchain, and fostering interdisciplinary collaboration. This study provides actionable insights for achieving a balance between technological advancement and sustainability in AI-enabled circular economy systems

https://doi.org/10.19192/wsfip.sj4.2024.10
pdf (English)

Bibliografia

Akanbi, L. A., Oyedele, A. O., Oyedele, L. O., & Salami, R. O. (2020). Deep learning model for Demolition Waste Prediction in a circular economy. Journal of Cleaner Production, 274, Article 122843. https://doi.org/10.1016/j.jclepro.2020.122843

Al Halbusi, H., Al-Sulaiti, K. I., Alalwan, A. A., & Al-Busaidi, A. S. (2025). AI capability and green innovation impact on sustainable performance: Moderating role of big data and knowledge management. Technological Forecasting and Social Change, 210, Article 123897.

Ali, Z. A., Zain, M., Pathan, M. S., & Mooney, P. (2024). Contributions of artificial intelligence for circular economy transition leading toward sustainability: An explorative study in agriculture and food industries of Pakistan. Environment, Development and Sustainability, 26(8), 19131–19175. https://doi.org/10.1007/s10668-023-03445-5

Andono, P. N., Saputra, F. O., Shidik, G. F., & Hasibuan, Z. A. (2022). End-to-End Circular Economy in Onion Farming with the Application of Artificial Intelligence and Internet of Things. 2022 International Seminar on Application for Technology of Information and Communication, pp. 459-462. https://doi.org/10.1109/iSemantic55962.2022.9920447

Bag, S., Pretorius, J. H. C., Gupta, S., & Dwivedi, Y. K. (2021). Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices, and circular economy capabilities. Technological Forecasting and Social Change, 163, Article 120420. https://doi.org/10.1016/j.techfore.2020.120420

Bashynska I., Malanchuk M., Zhuravel O., Olinichenko K. (2019). Smart Solutions: Risk Management of Crypto-Assets and Blockchain Technology, International Journal of Civil Engineering and Technology, 10(2), pp. 1121–1131.

Bashynska, I., Mukhamejanuly, S., Malynovska, Y., Bortnikova, M., Saiensus, M., Malynovskyy, Y. (2023). Assessing the Outcomes of Digital Transformation Smartization Projects in Industrial Enterprises: A Model for Enabling Sustainability. Sustainability, 15, 14075. https://doi.org/10.3390/su151914075

Cheng, T., Kojima, D., Hu, H., Onoda, H., & Pandyaswargo, A. H. (2024). Optimizing Waste Sorting for Sustainability: An AI-Powered Robotic Solution for Beverage Container Recycling. Sustainability, 16(23), 10155.

D’Amore, G., Di Vaio, A., Balsalobre-Lorente, D., & Boccia, F. (2022). Artificial Intelligence in the Water–Energy–Food Model: A Holistic Approach towards Sustainable Development Goals. Sustainability (Switzerland), 14(2), Article 867. https://doi.org/10.3390/su14020867

Daneshmand, M., Noroozi, F., Corneanu, C., Mafakheri, F., & Fiorini, P. (2023). Industry 4.0 and prospects of circular economy: a survey of robotic assembly and disassembly. International Journal of Advanced Manufacturing Technology, 124(9), 2973–3000. https://doi.org/10.1007/s00170-021-08389-1

Di Vaio, A., Palladino, R., Hassan, R., & Escobar, O. (2020). Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review. Journal of Business Research, 121, 283–314. https://doi.org/10.1016/j.jbusres.2020.08.019

European Parliament & Council of the European Union. (2024). Regulation (EU) 2024/1689 of the European Parliament and of the Council of 13 June 2024 laying down harmonised rules on artificial intelligence (Artificial Intelligence Act) and amending certain Union legislative acts. Official Journal of the European Union, 1 L 1689, 1-68

Hernik, J. (2023). The usefulness of big data in creating innovations. The example of Google Trends. Managerial Economics, 23(2), 131.

ISO/IEC 27001:2022 (2022). Information security, cybersecurity and privacy protection — Information security management systems — Requirements. https://www.iso.org/standard/27001

National Institute of Standards and Technology (NIST). (2023). Artificial Intelligence Risk Management Framework (AI RMF 1.0). U.S. Department of Commerce. Retrieved from https://doi.org/10.6028/NIST.AI.100-1

National Institute of Standards and Technology (NIST). (2023). Artificial Intelligence Risk Management Framework (AI RMF 1.0). U.S. Department of Commerce. Retrieved from https://doi.org/10.6028/NIST.AI.100-1

Rusko, R. (2024). The Role of AI in Finnish Green Economy and Especially in Circular Economy: Challenges and Possibilities. In Reshaping Environmental Science Through Machine Learning and IoT (pp. 18). IGI Global. https://doi.org/10.4018/979-8-3693-2351-9.ch007

Singh, A. (2025). AI-Driven Innovations for Enabling a Circular Economy: Optimizing Resource Efficiency and Sustainability. In Innovating Sustainability Through Digital Circular Economy (pp. 18). IGI Global. https://doi.org/10.4018/979-8-3373-0578-3.ch003

Singh, J. P. (2023). Artificial Intelligence in Circular Economies: A Pathway to Sustainable Resource Management. International Journal of Science and Research (IJSR), 12(12), 1128–1130. https://doi.org/10.21275/SR231214040053

Statista (2024a). https://www.statista.com/statistics/1446052/worldwide-spending-on-ai-by-industry/

Statista (2024b). https://www.statista.com/statistics/784802/global-factory-automation-market-growth/

Statista (2024c). https://www.statista.com/statistics/1412761/ai-infrastructure-challenges-worldwide/

Statista (2024d). https://www.statista.com/statistics/1449200/ai-impact-of-life-aspects-globally/

Creative Commons License

Utwór dostępny jest na licencji Creative Commons Uznanie autorstwa – Użycie niekomercyjne 4.0 Międzynarodowe.

Prawa autorskie (c) 2024 Iryna Bashynska, Olha Prokopenko

##plugins.generic.usageStats.downloads##

##plugins.generic.usageStats.noStats##