Artificial intelligence and public administration: Understanding actors, governance, and policy from micro, meso, and macro perspectives

Abstract

Artificial Intelligence (AI) has become one of the most prominent topics in public policy and administration studies over the last years. Despite the attention to AI in this field isn’t entirely new, the universality of these group of technologies has radically increased the attention of scholars around the globe. This expansion of AI in the public sector entails the exploration of renovated foundations of analysis, not only to understand the novelty of these technologies, but also to connect these processes of adoption and implementation with other debates in public policy and administration. To do so, in this article we debate the need of an analytical framework of AI in the public sector based on the three levels of public administration: macro, meso, and micro. Also, we review the state-of-the-art in the field using the articles presented in the special issue on Artificial Intelligence and Public Administration: Actors, Governance, and Policy. Form here, we propose studying AI using a combination of macro, meso, and micro levels of public administration. We assume this will help to broadly apprehend how and why people, policies, and institutions interrelate with AI in public sector settings, and which effects can be expected from these processes in public administration.