Tort liability for the application risk of generative artificial intelligence technology in the circular economy and financial industry: evidence from China - Quancheng Chen; Xuemei Hu (Humanities & Social Sciences Communications)
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 < 0.001). Erroneous decisions and technical failures also influence liability, with coefficients of −0.36 (p = 0.012) and 0.45 (p = 0.005), respectively. Additionally, the characteristics of technology implementation, the legal environment, and enterprise management practices significantly mediate the relationship between risk and liability, with mediating coefficients of 0.25, 0.18, and 0.32 (all p < 0.05). The findings underscore a direct link between risk factors and legal liability. Moreover, factors related to the application of generative AI partially mediate this relationship, indicating a strong statistical correlation. These insights are critical for companies aiming to strengthen risk management, ensure regulatory compliance, and protect their legal and financial interests.