气候变化领域集成服务门户(CCPortal): How to promote AI in the US federal government: Insights from policy process frameworks

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DOI	10.1016/j.giq.2023.101908
	How to promote AI in the US federal government: Insights from policy process frameworks
	Khan, Muhammad Salar; Shoaib, Azka; Arledge, Elizabeth
发表日期	2024
ISSN	0740-624X
EISSN	1872-9517
起始页码	41
结束页码	1
卷号	41 期号:1
英文摘要	When it comes to routine government activities, such as immigration, justice, social welfare provision and climate change, the general perception is that the US federal government operates slowly. One potential solution to increase the productivity and efficiency of the federal government is to adopt AI technologies and devices. AI technologies and devices already provide unique capabilities, services, and products, as demonstrated by smart homes, autonomous vehicles, delivery drones, GPS navigation, Chatbots such as OpenAI's ChatGPT and Google's Bard, and virtual assistants such as Amazon's Alexa. However, incorporating massive AI into the US federal government would present several challenges, including ethical and legal concerns, outdated infrastructure, unprepared human capital, institutional obstacles, and a lack of social acceptance. How can US policymakers promote policies that increase AI usage in the face of these challenges? This will require a comprehensive strategy at the intersection of science, policy, and economics that addresses the aforementioned challenges. In this paper, we survey literature on the interrelated policy process to understand the advancement, or lack thereof, of AI in the US federal government, an emerging area of interest. To accomplish this, we examine several policy process frameworks, including the Advocacy Coalition Framework (ACF), Multiple Streams Framework (MSF), Punctuated Equilibrium Theory (PET), Internal Determinants and Diffusion (ID&D), Narrative Policy Framework (NPF), and Institutional Analysis and Development (IAD). We hope that insights from this literature will identify a set of policies to promote AI-operated functionalities in the US federal government.
英文关键词	AI adoption; Artificial intelligence; Federal government; Policy; Policy frameworks; Public policy process; Responsible AI; Technology adoption
语种	英语
WOS研究方向	Information Science & Library Science
WOS类目	Information Science & Library Science
WOS记录号	WOS:001155625300001
来源期刊	GOVERNMENT INFORMATION QUARTERLY
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/289188
作者单位	George Mason University; Massachusetts Institute of Technology (MIT); Virginia Polytechnic Institute & State University
推荐引用方式 GB/T 7714	Khan, Muhammad Salar,Shoaib, Azka,Arledge, Elizabeth. How to promote AI in the US federal government: Insights from policy process frameworks[J],2024,41(1).
APA	Khan, Muhammad Salar,Shoaib, Azka,&Arledge, Elizabeth.(2024).How to promote AI in the US federal government: Insights from policy process frameworks.GOVERNMENT INFORMATION QUARTERLY,41(1).
MLA	Khan, Muhammad Salar,et al."How to promote AI in the US federal government: Insights from policy process frameworks".GOVERNMENT INFORMATION QUARTERLY 41.1(2024).