Centre for Digital Governance
Refine
Year of publication
- 2021 (2) (remove)
Document Type
- Article (1)
- Working Paper (1)
Language
- English (2)
Has Fulltext
- no (2)
Is part of the Bibliography
- no (2)
To unlock the full potential of ICT-related public sector innovation and digital transformation, governments must embrace collaborative working structures and leadership, is commonly argued. However, little is known about the dynamics of such collaborations in contexts of hierarchy, silo cultures, and procedural accountability. A widely voiced but empirically insufficiently substantiated claim is that bringing cross-cutting digital endeavours forward requires more lateral, network-based approaches to governance beyond traditional Weberian ideals. We test this claim by shedding light on three distinct challenges (complexity, risk, and power imbalance) encountered when implementing the specific collaborative case of the German Online Access Act (OAA) and by examining how they have been addressed in institutional design and leadership. Our analysis, which combines desk research and semi-structured expert interviews, reveals that flexible, horizontal approaches are on the rise. Taking a closer look, however, vertical coordination continues to serve as complementary means to problem-solving capability.
There is an increased interest amongst governments and public sector organisations about how to best integrate artificial intelligence into their day-to-day business processes. Yet, a large majority of technical know how is concentrated within the private sector, requiring most public sector organisations to rely on public procurement for AI systems. While many governments may have experience with traditional forms of public technological procurement, this paper argues that the public procurement of AI is different and new insight is needed to understand this differentiation and procure AI better. This paper offers an initial contribution to the public administration and management literature by describing this difference, and identifying the challenges associated with the public procurement of AI. In order to achieve this contribution, the research studied guidelines in four European countries (Estonia, Netherlands, Serbia, and the United Kingdom) to generate insight into the challenges faced, and potential solutions to these challenges, during the public procurement of AI process.