eprintid: 10060001
rev_number: 16
eprint_status: archive
userid: 608
dir: disk0/10/06/00/01
datestamp: 2018-11-01 16:03:53
lastmod: 2021-09-17 22:02:17
status_changed: 2018-11-01 16:03:53
type: article
metadata_visibility: show
creators_name: Mikhaylov, SJ
creators_name: Esteve, M
creators_name: Campion, A
title: Artificial intelligence for the public sector: opportunities and challenges of cross-sector collaboration
ispublished: pub
divisions: UCL
divisions: B03
divisions: C03
divisions: F30
keywords: Science & Technology, Multidisciplinary Sciences, Science & Technology - Other Topics, cross-sector collaboration, data science, artificial intelligence, public policy, PRIVATE JOINT VENTURES, MANAGEMENT, PERFORMANCE, LEADERSHIP, NETWORKS, SERVICE, IMPLEMENTATION, PARTNERSHIPS, GOVERNANCE, DIVERSITY
note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
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’.
date: 2018-08-06
date_type: published
publisher: ROYAL SOC
official_url: https://doi.org/10.1098/rsta.2017.0357
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
article_type_text: Article
verified: verified_manual
elements_id: 1576703
doi: 10.1098/rsta.2017.0357
lyricists_name: Esteve, Marc
lyricists_name: Mikhaylov, Vyacheslav
lyricists_id: MESTE42
lyricists_id: VMIKH60
actors_name: Esteve, Marc
actors_id: MESTE42
actors_role: owner
full_text_status: public
publication: Philosophical Transactions of The Royal Society A - Mathematical, Physical and Engineering Sciences
volume: 376
number: 2128
pages: 21
issn: 1471-2962
citation:        Mikhaylov, SJ;    Esteve, M;    Campion, A;      (2018)    Artificial intelligence for the public sector: opportunities and challenges of cross-sector collaboration.                   Philosophical Transactions of The Royal Society A - Mathematical, Physical and Engineering Sciences , 376  (2128)      10.1098/rsta.2017.0357 <https://doi.org/10.1098/rsta.2017.0357>.       Green open access   
 
document_url: https://discovery-pp.ucl.ac.uk/id/eprint/10060001/1/1809.04399v1.pdf