Analysis of Potential Ethical Risks and Countermeasures of AI+ Technology in Smart Finance Applications
Abstract
The deep integration of AI technology with the finance field has given rise to a new paradigm of smart finance applications, which have also given rise to complex ethical risks while enhancing the efficiency of financial decision-making. Data bias may lead to credit discrimination, black-box decision-making mechanisms weaken regulatory transparency, and risk transmission effects may trigger systemic financial vulnerability. Existing research focuses on technology optimization, but pays little attention to the quantitative assessment and dynamic governance of ethical risks. In this paper, we build a multi-dimensional ethical risk detection system for smart financial scenarios, develop core algorithms for data traceability, decision visualization, and risk modeling, and form a synergistic framework of technical governance and institutional constraints. The research breaks through the limitations of traditional qualitative analysis, provides operable solutions for the construction of a trustworthy smart financial system, and has practical value for maintaining the fairness and stability of the financial market.
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