Esteve, M; Campion, A; Gasco, M; Mikhaylov, S; (2020) The Challenges of Organizational Factors in Collaborative Artificial Intelligence Projects. Social Science Computer Review (In press).

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Abstract

Despite the current popularity of AI and a steady increase in publications over time, few studies have investigated artificial intelligence (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 multi-year 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, re-framing 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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