Artificial intelligence for the public sector: opportunities and challenges of cross-sector collaboration

被引:97
作者
Mikhaylov, Slava Jankin [1 ,2 ]
Esteve, Marc [3 ,4 ]
Campion, Averill [4 ]
机构
[1] Univ Essex, Inst Analyt & Data Sci, Sch Comp Sci & Elect Engn, Colchester CO4 3AD, Essex, England
[2] Univ Essex, Dept Govt, Colchester CO4 3AD, Essex, England
[3] UCL, Sch Publ Policy, London WC1E 6BT, England
[4] Ramon Llull Univ, Dept Strategy & Gen Management, ESADE, Barcelona 08022, Spain
来源
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES | 2018年 / 376卷 / 2128期
基金
奥地利科学基金会;
关键词
cross-sector collaboration; data science; artificial intelligence; public policy; PRIVATE PARTNERSHIPS; MANAGEMENT; LEADERSHIP; NETWORKS; IMPLEMENTATION; DIVERSITY; BARRIERS;
D O I
10.1098/rsta.2017.0357
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Public sector organizations are increasingly interested in using data science and artificial intelligence capabilities to deliver policy and generate efficiencies in high-uncertainty environments. The long-term success of data science and artificial intelligence (AI) in the public sector relies on effectively embedding it into delivery solutions for policy implementation. However, governments cannot do this integration of AI into public service delivery on their own. The UK Government Industrial Strategy is clear that delivering on the AI grand challenge requires collaboration between universities and the public and private sectors. This cross-sectoral collaborative approach is the norm in applied AI centres of excellence around the world. Despite their popularity, cross-sector collaborations entail serious management challenges that hinder their success. In this article we discuss the opportunities for and challenges of AI for the public sector. Finally, we propose a series of strategies to successfully manage these cross-sectoral collaborations. This article is part of a discussion meeting issue 'The growing ubiquity of algorithms in society: implications, impacts and innovations'.
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页数:21
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