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Tort liability for the application risk of generative artificial intelligence technology in the circular economy and financial industry: evidence from China

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  • Quancheng Chen

    (East China Normal University)

  • Xuemei Hu

    (East China Normal University)

Abstract

This study investigates tort liability arising from the application risks of generative artificial intelligence (AI) in the financial industry and circular economy (CE), offering targeted management recommendations. The study is based on survey data collected from 60 companies, analyzed using structural equation modeling. The study first examines the frequency of risk events and legal disputes across companies of varying sizes. It identifies key associations between risk factors and legal liability, including the mediating effects of organizational and contextual elements. The analysis reveals that large CE enterprises experience higher rates of data breaches and technical failures, while smaller financial firms report more frequent legal disputes and data leaks. Data leakage shows a strong correlation with legal liability (coefficient = 0.72, p

Suggested Citation

  • Quancheng Chen & Xuemei Hu, 2025. "Tort liability for the application risk of generative artificial intelligence technology in the circular economy and financial industry: evidence from China," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-13, December.
    • Handle: RePEc:pal:palcom:v:12:y:2025:i:1:d:10.1057_s41599-025-05419-1
    DOI: 10.1057/s41599-025-05419-1
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    References listed on IDEAS

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    1. Loureiro, Sandra Maria Correia & Guerreiro, João & Tussyadiah, Iis, 2021. "Artificial intelligence in business: State of the art and future research agenda," Journal of Business Research, Elsevier, vol. 129(C), pages 911-926.
    2. Ahmed Izzidien, 2023. "Using the interest theory of rights and Hohfeldian taxonomy to address a gap in machine learning methods for legal document analysis," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 10(1), pages 1-15, December.
    3. Samuel Fosso Wamba & Cameron Guthrie & Maciel M. Queiroz & Stefan Minner, 2024. "ChatGPT and generative artificial intelligence: an exploratory study of key benefits and challenges in operations and supply chain management," International Journal of Production Research, Taylor & Francis Journals, vol. 62(16), pages 5676-5696, August.
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