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

Slava Jankin Mikhaylov, Marc Esteve, Averill Campion

Research output: Indexed journal article Articlepeer-review

102 Citations (Scopus)

Abstract

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'.

Original languageEnglish
Article number20170357
JournalPhilosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
Volume376
Issue number2128
DOIs
Publication statusPublished - 2018
Externally publishedYes

Keywords

  • Artificial intelligence
  • Cross-sector collaboration
  • Data science
  • Public policy

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