Year: 2025
Type: dissertation
Abstract: Artificial intelligence (AI) is reshaping many aspects of daily life rapidly and unpredictably. Researchers highlight the challenges of policymaking under uncertainty, calling for adaptive and inclusive governance. However, the role of policy actors in shaping AI policy remains understudied. This study addresses this gap by examining how policy actors navigate AI-related uncertainties across sectoral and national boundaries. Using an innovative method, egocentric network analysis, it maps AI-related policy actor networks in Germany and Switzerland. The analysis includes both the emerging AI policy subsystem and established subsystems in Finance, Health, and Social Welfare. Findings reveal that sectoral networks still heavily influence engagement in AI policymaking, resulting in sector-specific policies. Simultaneously, the internationalization of policy actor networks may foster policy diffusion. Cross-sectoral and cross-jurisdictional connections are treated similarly to intra-sectoral ones, suggesting potential for more integrated policymaking. This research provides valuable insights into the governance of emerging and cross-cutting policy challenges.
Source: IRIS
Author: Lemke, Nicole
Institution: University of Lausanne
Language: English
Topic: Policy Transfer and Learning
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7054579862