生成式人工智能的算法治理挑戰與治理型監管

Algorithmic governance Challenges and Governance Supervision in Generative Artificial Intelligence

以ChatGPT為代表的大規模預訓練語言模型日益展現出通用潛力，其超大規模、超多參數量、超級易擴展性和超級應用場景的技術特性對以算法透明度、算法公平性和算法問責為內核的算法治理體系帶來全方位挑戰。在全球人工智能治理的主流範式中，歐盟形成了基於風險的治理範式，我國構建了基於主體的治理範式，美國採用了基於應用的治理範式。三種治理范式均形成于傳統人工智能的“1. 0時代”，與展現通用潛能的新一代人工智能難以充分適配，並在不同維度凸顯治理局限。因此，在人工智能技術範式變革之際，應以監管權的開放協同、監管方式的多元融合、監管措施的兼容一致為特徵推動監管範式的全面革新，邁向面向人工智能“2. 0時代”的“治理型監管”。

As exemplified by ChatGPT, large-scale pre-trained language models are progressively showcasing their potential. The technical features of these models, including their vast scale, substantial parameter count, extraordinary scalability, and varied application scenarios, present comprehensive challenges to the algorithmic governance system centered around transparency, fairness, and accountability. In the prevailing global AI governance paradigms, the EU has instituted a risk-based governance framework, China has devised a subject-based governance approach, and the U. S. has embraced an application-based governance method. These three governance paradigms emerged during the“1. 0 era”of narrow AI. Consequently, as AI technology evolves, it is crucial to foster a holistic transformation of the regulatory structure, characterized by open collaboration in regulatory authority, the incorporation of diverse regulatory approaches, and the harmonization of regulatory measures. This shift will enable a transition towards“governance-oriented regulation”fitting for the AI“2. 0 era”.