Artificial Intelligence for data-driven decision-making and governance in public affairs

被引:19
|
作者
Charles, Vincent [1 ]
Rana, Nripendra P. [2 ]
Carter, Lemuria [3 ]
机构
[1] Univ Bradford, Sch Management, Bradford, England
[2] Qatar Univ, Coll Business & Econ, Doha, Qatar
[3] Univ New South Wales, Sydney, Australia
关键词
Artificial intelligence; Data-driven decision-making; Public governance; Public sector; Research agenda; FUTURE; ENERGY;
D O I
10.1016/j.giq.2022.101742
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
Literature shows there is a growing interest in studies involving Artificial Intelligence (AI) in the public sector; and while there is evidence of many governmental initiatives that have been established to harness the power of AI, empirical research on the topic and evidence-based insights are rather lacking. The aim of this Special Issue on Artificial Intelligence for Data-Driven Decision-Making and Governance in Public Affairs is to extend both the theoretical and practical boundaries of AI research in the public sector in order to improve governmental decision-making and governance, thus enhancing public value creation. The papers in this special issue focus on AI risks and guidelines, AI governance, the risks of governmental implementation of AI to citizens' privacy, increasing citizen satisfaction through AI-enabled government services, the enablers and challenges of AI implementation in specific public sectors, and using AI to study political opinion. These papers not only advance our knowledge and understanding of the use of AI in government and public governance, but they also help to set out a renewed research agenda. Future research should, among other things, focus on inter- and multi-disciplinary empirical studies that call for the collaboration of a variety of stakeholders; on the longitudinal dynamics of creating public value through the breadth and depth of AI assimilation; and on the investigation of the ethical challenges (particularly data privacy) in AI implementation.
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