Overcoming the Challenges of Collaboratively Adopting Artificial Intelligence in the Public Sector
Open accessAbstract
Despite the current popularity of artificial intelligence (AI) and a steady increase in publications over time, few studies have investigated AI in public contexts. As a result, assumptions about the drivers, challenges, and impacts of AI in government are far from conclusive. By using a case study that involves a large research university in England and two different county councils in a multiyear collaborative project around AI, we study the challenges that interorganizational collaborations face in adopting AI tools and implementing organizational routines to address them. Our findings reveal the most important challenges facing such collaborations: a resistance to sharing data due to privacy and security concerns, insufficient understanding of the required and available data, a lack of alignment between project interests and expectations around data sharing, and a lack of engagement across organizational hierarchy. Organizational routines capable of overcoming such challenges include working on-site, presenting the benefits of data sharing, reframing problems, designating joint appointments and boundary spanners, and connecting participants in the collaboration at all levels around project design and purpose.
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Some changes result from external factors that include the societal context; others include aspects of inter-organizational collaboration with an ecology of external partners.
“Some changes result from external factors (4a) that include the societal context (Rahwan 2018), others usually include aspects of inter-organizational collaboration (Campion et al. 2020) with an ecology of external partners.”
From Keeping the organization in the loop: a socio-technical extension of human-centered artificial intelligence (2023) · cites this paper as Campion et al. 2020
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- Authors
- Campion, A., Gasco-Hernandez, M., Jankin Mikhaylov, S., & Esteve, M.
- Affiliations
- Universitat Ramon Llull (ES)
- University at Albany, State University of New York, Albany, NY, USA
- Hertie School, Berlin, Germany
- Ramon Llull University, Barcelona, Spain
- Venue
- Social Science Computer Review
- Publisher
- SAGE Publications
- Published
- 2020-12-20
- Volume
- 40
- Issue
- 2
- Pages
- 462-477
- ISSN
- 0894-4393 (ISSN-L)
- 1552-8286
- OpenAlex
- W3118099700
- Cited by
- 162
- References
- 50
- Citations by year
- 2026: 41 · 2025: 52 · 2024: 34 · 2023: 22 · 2022: 9 · 2021: 4
- FWCI
- 30.21
- Type
- journal article
- Language
- en
- Open access
- green
- discovery.ucl.ac.uk
- Locations
- Social Science Computer Review (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- University of Birmingham Research Portal (University of Birmingham) (submittedVersion)
- Topics
- Social Sciences › Political Science and International Relations › E-Government and Public Services
- Social Sciences › Sociology and Political Science › Information Systems Theories and Implementation
- Social Sciences › Public Administration › Public Policy and Administration Research
- Keywords
- artificial intelligence adoption, public sector, inter-organizational collaboration, data sharing, privacy and security concerns, organizational routines, boundary spanners, county councils, university-government collaboration, organizational hierarchy
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