IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v133y2024ics0140988324002147.html
   My bibliography  Save this article

AI and Nuclear: A perfect intersection of danger and potential?

Author

Listed:
  • Chen, Yan
  • Zhang, Ruiqian
  • Lyu, Jiayi
  • Hou, Yuqi

Abstract

This paper explores the intersection between artificial intelligence and nuclear energy, shedding light on the intriguing scenario when these two sectors jointly consturct. Through the application of both full-sample and sub-sample methodologies, this study identifies the time-dependent interrelationships between China's artificial intelligence index (AI) and nuclear energy indicator (NUC). The quantitative analysis presents that AI's influence on nuclear energy is twofold. On one hand, AI contributes positively by acting as a catalyst and enhancing safety measures in the nuclear sector. On the other, the impact might be perceived negatively, primarily when cost-effective alternative energy sources overshadow the benefits of nuclear energy. Additionally, the positive effect of NUC on AI highlights the benefits derived from nuclear's expansive and consistent energy output, catering efficiently to AI's substantial energy demands. In essence, AI and NUC are found to be complementary, with each having the potential to propel the other forward. This reciprocity paves the way for a synergistic relationship, promising mutual benefits. The study introduces a fresh perspective on the co-evolution of energy and technology, offering thought-provoking recommendations aimed at cultivating the collaborative growth of AI and NUC towards a common good.

Suggested Citation

  • Chen, Yan & Zhang, Ruiqian & Lyu, Jiayi & Hou, Yuqi, 2024. "AI and Nuclear: A perfect intersection of danger and potential?," Energy Economics, Elsevier, vol. 133(C).
  • Handle: RePEc:eee:eneeco:v:133:y:2024:i:c:s0140988324002147
    DOI: 10.1016/j.eneco.2024.107506
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988324002147
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2024.107506?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Pesaran, M. Hashem & Timmermann, Allan, 2005. "Small sample properties of forecasts from autoregressive models under structural breaks," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 183-217.
    2. Li, Qiangyi & Zeng, Fu'e & Liu, Shaohui & Yang, Mian & Xu, Fei, 2021. "The effects of China's sustainable development policy for resource-based cities on local industrial transformation," Resources Policy, Elsevier, vol. 71(C).
    3. Balmer, Roberto E. & Levin, Stanford L. & Schmidt, Stephen, 2020. "Artificial Intelligence Applications in Telecommunications and other network industries," Telecommunications Policy, Elsevier, vol. 44(6).
    4. Yu, Lean & Zhao, Yang & Tang, Ling, 2014. "A compressed sensing based AI learning paradigm for crude oil price forecasting," Energy Economics, Elsevier, vol. 46(C), pages 236-245.
    5. Du, Kerui & Cheng, Yuanyuan & Yao, Xin, 2021. "Environmental regulation, green technology innovation, and industrial structure upgrading: The road to the green transformation of Chinese cities," Energy Economics, Elsevier, vol. 98(C).
    6. Anne-Laure Ligozat & Julien Lefevre & Aurélie Bugeau & Jacques Combaz, 2022. "Unraveling the Hidden Environmental Impacts of AI Solutions for Environment Life Cycle Assessment of AI Solutions," Sustainability, MDPI, vol. 14(9), pages 1-14, April.
    7. Guo, Di & Guo, Yan & Jiang, Kun, 2016. "Government-subsidized R&D and firm innovation: Evidence from China," Research Policy, Elsevier, vol. 45(6), pages 1129-1144.
    8. Azam, Anam & Rafiq, Muhammad & Shafique, Muhammad & Zhang, Haonan & Yuan, Jiahai, 2021. "Analyzing the effect of natural gas, nuclear energy and renewable energy on GDP and carbon emissions: A multi-variate panel data analysis," Energy, Elsevier, vol. 219(C).
    9. Teng, Sin Yong & Touš, Michal & Leong, Wei Dong & How, Bing Shen & Lam, Hon Loong & Máša, Vítězslav, 2021. "Recent advances on industrial data-driven energy savings: Digital twins and infrastructures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    10. Gozgor, Giray & Paramati, Sudharshan Reddy, 2022. "Does energy diversification cause an economic slowdown? Evidence from a newly constructed energy diversification index," Energy Economics, Elsevier, vol. 109(C).
    11. Lau, Chi Keung & Gozgor, Giray & Mahalik, Mantu Kumar & Patel, Gupteswar & Li, Jing, 2023. "Introducing a new measure of energy transition: Green quality of energy mix and its impact on CO2 emissions," Energy Economics, Elsevier, vol. 122(C).
    12. Lu, Zhou & Gozgor, Giray & Mahalik, Mantu Kumar & Padhan, Hemachandra & Yan, Cheng, 2022. "Welfare gains from international trade and renewable energy demand: Evidence from the OECD countries," Energy Economics, Elsevier, vol. 112(C).
    13. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    14. Wang, Fan & Gu, Jibao & Wu, Jianlin, 2020. "Perspective taking, energy policy involvement, and public acceptance of nuclear energy: Evidence from China," Energy Policy, Elsevier, vol. 145(C).
    15. Ren, Xiaohang & Zhong, Yan & Cheng, Xu & Yan, Cheng & Gozgor, Giray, 2023. "Does carbon price uncertainty affect stock price crash risk? Evidence from China," Energy Economics, Elsevier, vol. 122(C).
    16. Urpelainen, Johannes, 2011. "Export orientation and domestic electricity generation: Effects on energy efficiency innovation in select sectors," Energy Policy, Elsevier, vol. 39(9), pages 5638-5646, September.
    17. Wuqing Du & Wei You & Zhenqing Xu, 2022. "Review and Prospect of Legal Development in Commercial Nuclear Energy," Energies, MDPI, vol. 15(12), pages 1-16, June.
    18. Hansen, Bruce E, 2002. "Tests for Parameter Instability in Regressions with I(1) Processes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 45-59, January.
    19. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    20. Toda, Hiro Y. & Phillips, Peter C. B., 1993. "The spurious effect of unit roots on vector autoregressions : An analytical study," Journal of Econometrics, Elsevier, vol. 59(3), pages 229-255, October.
    21. Su, Chi-Wei & Qin, Meng & Tao, Ran & Shao, Xue-Feng & Albu, Lucian Liviu & Umar, Muhammad, 2020. "Can Bitcoin hedge the risks of geopolitical events?," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    22. Shahbaz, Muhammad & Siddiqui, Aaliyah & Ahmad, Shabbir & Jiao, Zhilun, 2023. "Financial development as a new determinant of energy diversification: The role of natural capital and structural changes in Australia," Energy Economics, Elsevier, vol. 126(C).
    23. Sims, Christopher A & Stock, James H & Watson, Mark W, 1990. "Inference in Linear Time Series Models with Some Unit Roots," Econometrica, Econometric Society, vol. 58(1), pages 113-144, January.
    24. Chatziantoniou, Ioannis & Elsayed, Ahmed H. & Gabauer, David & Gozgor, Giray, 2023. "Oil price shocks and exchange rate dynamics: Evidence from decomposed and partial connectedness measures for oil importing and exporting economies," Energy Economics, Elsevier, vol. 120(C).
    25. Chishti, Muhammad Zubair & Sinha, Avik & Zaman, Umer & Shahzad, Umer, 2023. "Exploring the dynamic connectedness among energy transition and its drivers: Understanding the moderating role of global geopolitical risk," Energy Economics, Elsevier, vol. 119(C).
    26. Manuel Woschank & Erwin Rauch & Helmut Zsifkovits, 2020. "A Review of Further Directions for Artificial Intelligence, Machine Learning, and Deep Learning in Smart Logistics," Sustainability, MDPI, vol. 12(9), pages 1-23, May.
    27. Lyu, Wenjing & Liu, Jin, 2021. "Artificial Intelligence and emerging digital technologies in the energy sector," Applied Energy, Elsevier, vol. 303(C).
    28. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    29. Sjödin, David & Parida, Vinit & Palmié, Maximilian & Wincent, Joakim, 2021. "How AI capabilities enable business model innovation: Scaling AI through co-evolutionary processes and feedback loops," Journal of Business Research, Elsevier, vol. 134(C), pages 574-587.
    30. Jordan Bernhardt & Lauren Sukin, 2021. "Joint Military Exercises and Crisis Dynamics on the Korean Peninsula," Journal of Conflict Resolution, Peace Science Society (International), vol. 65(5), pages 855-888, May.
    31. Ghazi Shukur & Panagiotis Mantalos, 2000. "A simple investigation of the Granger-causality test in integrated-cointegrated VAR systems," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(8), pages 1021-1031.
    32. Yi, Zonggen & Luo, Yusheng & Westover, Tyler & Katikaneni, Sravya & Ponkiya, Binaka & Sah, Suba & Mahmud, Sadab & Raker, David & Javaid, Ahmad & Heben, Michael J. & Khanna, Raghav, 2022. "Deep reinforcement learning based optimization for a tightly coupled nuclear renewable integrated energy system," Applied Energy, Elsevier, vol. 328(C).
    33. Alvin Camba & Janica Magat, 2021. "How Do Investors Respond To Territorial Disputes? Evidence From The South China Sea And Implications On Philippines Economic Strategy," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 66(01), pages 243-267, March.
    34. Hu, Yucai & Ren, Shenggang & Wang, Yangjie & Chen, Xiaohong, 2020. "Can carbon emission trading scheme achieve energy conservation and emission reduction? Evidence from the industrial sector in China," Energy Economics, Elsevier, vol. 85(C).
    35. Jie Yang & Jie Wang & Xiaofeng Zhang & Chunqi Shen & Zhijuan Shao, 2022. "How Social Impressions Affect Public Acceptance of Nuclear Energy: A Case Study in China," Sustainability, MDPI, vol. 14(18), pages 1-23, September.
    36. Sinha, Avik & Bekiros, Stelios & Hussain, Nazim & Nguyen, Duc Khuong & Khan, Sana Akbar, 2023. "How social imbalance and governance quality shape policy directives for energy transition in the OECD countries?," Energy Economics, Elsevier, vol. 120(C).
    37. Xiang, Pianpian & Jiang, Kejun & Wang, Jiachen & He, Chenmin & Chen, Sha & Jiang, Weiyi, 2024. "Evaluation of LCOH of conventional technology, energy storage coupled solar PV electrolysis, and HTGR in China," Applied Energy, Elsevier, vol. 353(PA).
    38. Qin, Meng & Mirza, Nawazish & Su, Chi-Wei & Umar, Muhammad, 2023. "Exploring Bubbles in the Digital Economy: The Case of China," Global Finance Journal, Elsevier, vol. 57(C).
    39. Ming-Hui Huang & Roland T. Rust, 2021. "A strategic framework for artificial intelligence in marketing," Journal of the Academy of Marketing Science, Springer, vol. 49(1), pages 30-50, January.
    40. Darren J. Lim & Victor A. Ferguson, 2022. "Informal economic sanctions: the political economy of Chinese coercion during the THAAD dispute," Review of International Political Economy, Taylor & Francis Journals, vol. 29(5), pages 1525-1548, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Qin, Meng & Hu, Wei & Qi, Xinzhou & Chang, Tsangyao, 2024. "Do the benefits outweigh the disadvantages? Exploring the role of artificial intelligence in renewable energy," Energy Economics, Elsevier, vol. 131(C).
    2. Kai-Hua Wang & Jia-Min Kan & Cui-Feng Jiang & Chi-Wei Su, 2022. "Is Geopolitical Risk Powerful Enough to Affect Carbon Dioxide Emissions? Evidence from China," Sustainability, MDPI, vol. 14(13), pages 1-16, June.
    3. Qin, Meng & Zhu, Yujie & Xie, Xin & Shao, Xuefeng & Lobonţ, Oana-Ramona, 2024. "The impact of climate risk on technological progress under the fourth industrial era," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    4. Sun, Yanpeng & Song, Yuru & Long, Chi & Qin, Meng & Lobonţ, Oana-Ramona, 2023. "How to improve global environmental governance? Lessons learned from climate risk and climate policy uncertainty," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 1666-1676.
    5. Liu, Tie-Ying & Su, Chi-Wei, 2021. "Is transportation improving urbanization in China?," Socio-Economic Planning Sciences, Elsevier, vol. 77(C).
    6. Ghosh, Taniya & Bhadury, Soumya, 2018. "Money's causal role in exchange rate: Do divisia monetary aggregates explain more?," International Review of Economics & Finance, Elsevier, vol. 57(C), pages 402-417.
    7. Xiao-lin Li & Mehmet Balcilar & Rangan Gupta & Tsangyao Chang, 2016. "The Causal Relationship Between Economic Policy Uncertainty and Stock Returns in China and India: Evidence from a Bootstrap Rolling Window Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(3), pages 674-689, March.
    8. Zhang, Xiaojing & Chang, Hsu-Ling & Su, Chi-Wei & Qin, Meng & Umar, Muhammad, 2024. "Exploring the dynamic interaction between geopolitical risks and lithium prices: A time-varying analysis," Resources Policy, Elsevier, vol. 90(C).
    9. Yingying Xu & Zhi-Xin Liu & Hsu-Ling Chang & Adelina Dumitrescu Peculea & Chi-Wei Su, 2017. "Does self-fulfilment of the inflation expectation exist?," Applied Economics, Taylor & Francis Journals, vol. 49(11), pages 1098-1113, March.
    10. Su, Chi-Wei & Wang, Xiao-Qing & Tao, Ran & Chang, Hsu-Ling, 2019. "Does money supply drive housing prices in China?," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 85-94.
    11. Zhong, Yufei & Chen, Xuesheng & Wang, Zhixian & Lin, Regina Fang-Ying, 2024. "The nexus among artificial intelligence, supply chain and energy sustainability: A time-varying analysis," Energy Economics, Elsevier, vol. 132(C).
    12. Chi-Wei Su & Jiao-Jiao Fan & Hsu-Ling Chang & Xiao-Lin Li, 2016. "Is there Causal Relationship between Money Supply Growth and Inflation in China? Evidence from Quantity Theory of Money," Review of Development Economics, Wiley Blackwell, vol. 20(3), pages 702-719, August.
    13. Liu, Guanchun & He, Lei & Yue, Yiding & Wang, Jiying, 2014. "The linkage between insurance activity and banking credit: Some evidence from dynamic analysis," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 239-265.
    14. Qin, Meng & Su, Chi-Wei & Lobonţ, Oana-Ramona & Umar, Muhammad, 2023. "Blockchain: A carbon-neutral facilitator or an environmental destroyer?," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 604-615.
    15. Zhao, Qian & Ding, Longfei & Pirtea, Marilen Gabriel & Vǎtavu, Sorana, 2023. "Does technological innovation bring better air quality?," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 978-990.
    16. Cai, Yifei, 2016. "短期资本流动、经济政策不确定性与恐慌指数—基于时变分析框架下的研究 [Short-term Capital Flow, Economic Policy Uncertainty and VIX—Evidence from a Time-varying Analysis Framework]," MPRA Paper 73213, University Library of Munich, Germany.
    17. David Su & Xin Li & Oana-Ramona Lobonþ & Yanping Zhao, 2016. "Economic policy uncertainty and housing returns in Germany: Evidence from a bootstrap rolling window," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 34(1), pages 43-61.
    18. Zhao, Qiuyun & Jiang, Mei & Zhao, Zuoxiang & Liu, Fan & Zhou, Li, 2024. "The impact of green innovation on carbon reduction efficiency in China: Evidence from machine learning validation," Energy Economics, Elsevier, vol. 133(C).
    19. Ming-Hsien YANG & Chih-She WU, 2015. "Revisit Export and GDP Nexus in China and Taiwan: A Rolling Window Granger Causality Test," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(3(604), A), pages 75-92, Autumn.
    20. Qin, Meng & Su, Yun Hsuan & Zhao, Zhengtang & Mirza, Nawazish, 2023. "The politics of climate: Does factionalism impede U.S. carbon neutrality?," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 954-966.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:133:y:2024:i:c:s0140988324002147. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.