Research on the Application Logic and Ethical Boundaries of Artificial Intelligence in Systemic Financial Risk Early Warning
DOI:
https://doi.org/10.71451/ISTAER2554Keywords:
Artificial intelligence; Systemic financial risk; Risk warning; Machine learning; Ethical boundariesAbstract
With the deep penetration of artificial intelligence (AI) technology into the field of financial risk control, its application in systemic risk early warning is attracting widespread attention from academia and regulatory agencies. This study focuses on the dual characteristics of AI technology in financial risk early warning: on the one hand, through multi-source data fusion, complex algorithm models, and intelligent decision support, AI technology has significantly improved its ability to identify high-dimensional nonlinear risks, realizing a paradigm shift from static assessment to dynamic early warning; on the other hand, ethical issues such as algorithmic bias, black-box decision-making, and data privacy violations are becoming increasingly prominent, and may even give rise to new systemic risks due to model homogeneity. This paper constructs a three-dimensional analysis system of "technology application-ethical boundaries-governance framework," and uses case analysis and comparative research methods to demonstrate the necessity of establishing a responsible AI early warning mechanism. The study finds that effective risk governance requires the organic combination of technological empowerment and ethical regulation. By developing explainable artificial intelligence, constructing an algorithm audit system, and improving cross-departmental collaborative supervision, while leveraging the early warning advantages of AI technology, it is essential to ensure that its application complies with the fundamental requirements of financial stability and fairness and justice. This provides an important reference for building a new paradigm of intelligent financial supervision in the digital age.
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