Abstract: [Purpose/significance] AI governance is the cornerstone for advancing an AI-enabled society and building responsible AI. Humanities and social sciences are the theoretical foundations of AI governance. [Method/process] First, the "1+7 Principles" for AI governance is proposed based on case studies on the AI governance principles of Bos? ton Consulting Group, Microsoft, Google, Facebook, and Mercedes-Benz Group. Secondly, the implementation frame? work of AI governance is proposed using hierarchical analysis and the WSR method. AI governance is divided into six basic activities (R&D, iteration, operation and maintenance, accountability, training, and symbiosis), three main levels (technical technical-related and non-technical layers), and three different dimensions (Wuli, Renli, and Shili dimen? sions); then, the features of AI governance is described via discussing the main roles of AI ecosystem:individuals, groups, intelligent individuals, intelligent groups, human- machine hybrid individuals, and human- machine hybrid groups; Finally, five main topics of humanities and social sciences perspective studies on AI governance are identified. [Result/conclusion] Although the R&D of AI is a natural science issue, AI governance is subjected to the humanities and social sciences. AI governance needs to deal with humanism, sociality, value rationality, and interdisciplinarity studies. The core issues in AI governance from the perspective of humanities and social sciences are: to build a humancentered AI governance system, to transfer human culture and values to intelligent agents, to establish legal, moral, and ethical methods for human-machine co-existing society, algorithmic economy, and agent-based economic behaviors, as well as AI fairness and digital inclusion.