The Challenges of Organizational Factors in Collaborative Artificial Intelligence Projects
2020
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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