Overcoming the Challenges of Collaboratively Adopting Artificial Intelligence in the Public Sector
Datos Bibliográficos
| ID | 12169554 |
|---|---|
| Autores | Averill Campion (Ramon Llull University, Barcelona, Spain), Mila Gascó-Hernández (0000-0002-6308-8519, University at Albany, State University of New York, Albany, NY, USA, autor de correspondencia), Slava Jankin (0000-0001-6915-177X, Hertie School), Slava Jankin Mikhaylov (Hertie School, Berlin, Germany), Marc Esteves (0000-0002-9732-8082, Ramon Llull University, Barcelona, Spain) |
| Año | 2020 |
| Volumen | 40 |
| Número | 2 |
| Páginas | 462-477 |
| Fecha de publicación | 2020-12-20 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Social Science Computer Review (JOURNAL) |
| Identificadores de la revista | ISSN: 0894-4393 • E-ISSN: 1552-8286 |
| Editorial | SAGE Publishing (PUBLISHER • US) |
| DOI | 10.1177/0894439320979953 |
| OpenAlex | W3118099700 |
| Idioma | EN |
| Citas recibidas | 28 |
| Referencias citadas | 38 |
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
Cognitive reframing · Data sharing · Government (linguistics · Hierarchy · Knowledge management · Knowledge sharing · Political science · Popularity · Public relations · Public sector · Computer Science · E-Government and Public Services · Psychology · Public Policy and Administration Research · Smart Cities and Technologies
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| Obras citantes distintas | 28 |
|---|---|
| Citas por año | 5,6 |
| Intervalo de citas | 2021 - 2026 (6) |
| Velocidad de citación | current |
| Altamente citado | No |
| Tipos de cita | Neutras: 28 |