AICYSep 12, 2018

Artificial Intelligence for the Public Sector: Opportunities and challenges of cross-sector collaboration

arXiv:1809.04399v1214 citations
Originality Synthesis-oriented
AI Analysis

This work targets public sector organizations and researchers, offering incremental insights into collaboration management without introducing new technical methods.

The paper addresses the management challenges of cross-sector collaborations in applying AI to the public sector, proposing strategies to improve their success.

Public sector organisations 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 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 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 and challenges from AI for public sector. Finally, we propose a series of strategies to successfully manage these cross-sectoral collaborations.

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