证监会科技司刘铁斌:构建规范、健康的资本市场人工智能生态体系

Core Viewpoint - The China Securities Regulatory Commission (CSRC) is actively monitoring the application and development trends of artificial intelligence (AI) in the capital market, aiming to enhance the application level of AI while ensuring compliance and innovation [1][2]. Group 1: AI Application in Capital Markets - The capital market has shown a positive trend in exploring AI applications, characterized by leadership from the securities industry, followed by funds and futures, with top institutions setting examples [1]. - AI applications have covered core areas such as investment research, financing services, investor services, internal control management, information technology, and regulatory supervision [1]. Group 2: Challenges in AI Application - Challenges include non-unified data standards, insufficient high-quality data sources, and issues related to large models, such as "hallucination" [2]. - The supply and cost pressures of computing power restrict the large-scale and in-depth application of AI technology [2]. - Regulatory frameworks tailored to the characteristics of AI technology are still underdeveloped, and there is a need for improved precision and foresight in regulation [2]. Group 3: Future Directions for AI in Capital Markets - The basic work approach for building a healthy AI ecosystem in the capital market includes promoting innovation alongside regulatory compliance, respecting technological evolution, and collaborating across industry and institutional ecosystems [2][3]. - Key initiatives include establishing a differentiated regulatory framework, promoting pilot projects for "AI + capital markets," and building innovation application verification platforms [3]. Group 4: Institutional Ecosystem for AI - Institutions should develop governance structures and strategic plans that align AI applications with their development [3]. - Compliance with national AI ethical guidelines and social norms is essential to ensure that AI applications adhere to laws and regulations [3]. - Enhancing data governance and using authoritative data sources are critical for improving data quality and supporting AI applications [3]. Group 5: Regulatory Compliance and Risk Management - Institutions must ensure content compliance and establish mechanisms for content verification, especially in high-risk application scenarios [4]. - Strengthening data security management is necessary to prevent risks such as data misuse and information leakage [4]. - A collaborative mechanism involving human oversight and model assistance should be established to mitigate the inherent limitations of AI [4].