Margetts, Helen and Dunleavy, Patrick ORCID: 0000-0002-2650-6398 (2024) The political economy of digital government: how Silicon Valley firms drove conversion to data science and artificial intelligence in public management. Public Money and Management. ISSN 0954-0962
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Abstract
Until 2010, Anglosphere digital governments struggled to modernize, dependent on large-scale contract relationships with global systems integrators (SIs) and elderly, custom-built legacy systems. Policy-makers have (belatedly) converted to the value of the latest Artificial Intelligence (AI) technologies for improving government. Using elite interviews with government officials in three Anglosphere governments, this article traces the origins of this conversion back to Silicon Valley (SV) and platform corporations. These massive firms drove cultural, organizational and technological developments that reduced the influence of SIs. Going forward, SV firms’ practices will now drive public management use of data science and AI, shaping financial systems and practices. Drawing together elements from business studies, organizational change, public management reform, digital government and AI scholarship and practice, the authors show how government’s relationships with SV firms re-shape political economy relationships and bring digital change in government closer to SV ways of working.
Item Type: | Article |
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Official URL: | https://www.tandfonline.com/journals/rpmm20 |
Additional Information: | © 2024 The Author(s) |
Divisions: | Government |
Subjects: | H Social Sciences > HB Economic Theory J Political Science |
JEL classification: | H - Public Economics > H8 - Miscellaneous Issues > H83 - Public Administration L - Industrial Organization > L8 - Industry Studies: Services > L86 - Information and Internet Services; Computer Software D - Microeconomics > D7 - Analysis of Collective Decision-Making > D73 - Bureaucracy; Administrative Processes in Public Organizations; Corruption |
Date Deposited: | 13 Aug 2024 15:18 |
Last Modified: | 23 Sep 2024 16:03 |
URI: | http://eprints.lse.ac.uk/id/eprint/124539 |
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