The advocacy coalition framework in Japan: Contributions to policy process studies and the challenges involved

The advocacy coalition framework (ACF), a unified framework for understanding the policy process, has been applied in various countries and regions; however, there are few contributions from Japan, despite seemingly favorable conditions for applying it. An exploration of what hinders ACF applications in Japan is worthwhile for developing the ACF as a framework for comparative policy process studies across various social and political settings. Therefore, this study aims to systematically review previous Japanese ACF studies. Our review found that Japanese ACF studies are fewer in number, have less coverage of policy fields, and have less methodological diversity and transparency than international trends. While most of the Japanese ACF studies supported the basic hypotheses of the ACF, we found a need to refine some hypotheses and research methods of the ACF studies. We also discuss the background factors in the inactivity of ACF studies in Japan and suggest solutions for it.     

国家安全学视域下的人工智能安全研究：议题网络建构的初步尝试

国家安全学的创建为人工智能安全研究提供了整合与成长的契机。人工智能技术并非基于安全目的而诞生，却因其核心功能可以与既有安全体系内的诸多环节建立深度链接，从而获得了内在的安全属性。人工智能与国家安全学存在深度耦合关系，国家安全学研究框架能够为人工智能安全议题网络的建构提供基础条件。人工智能本身蕴含的“双重时空意义”与国家安全学框架内特点各异的安全领域形成复杂互动，能够在学科框架中建立以“中心—外围”结构为基本特征的人工智能安全研究议题网络。国家安全研究的六个领域同时兼容人工智能的双重身份：在研究视角更加宏观的政治安全、经济安全和军事安全领域，人工智能将以系统性要素的身份创建广泛的新议题，并成为网络的中心节点；在安全内涵相对具体的网络安全、核安全与国土安全领域，人工智能则成为重要的赋能主体，塑造了网络的半中心区域。其余十个国家安全领域与人工智能的链接相对松散，人工智能分别以博弈客体、功能性要素和技术性要素的身份发挥次要作用，从而构成议题网络的外围区域。议题网络的创建有助于人工智能安全研究迈入学科化的发展轨道。