Learning how to do AI: managing organizational boundaries in an intergovernmental learning forum
运用边界理论分析公共管理者如何通过跨政府的学习论坛克服人工智能能力差距，发现非结构化论坛更适合传递隐性程序知识，并强调社会信任和网络结构对同行学习的重要性。
This analysis applies boundary theory to public manager efforts to overcome AI capacity gaps through a public sector collaborative learning forum. Administrative and interview data identify the types of knowledge managers are able to access, the types of organizational differences that influence learning, and the strategies public managers use to overcome them. Analysis suggests that unstructured learning fora are better suited to the transfer of tacit procedural knowledge than declarative knowledge about AI, and emphasizes the importance of social trust and network structure to overcome knowledge gaps through peer learning.