Mapping the challenges of Artificial Intelligence in the public sector: Evidence from public healthcare |
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| Institution: | 1. Sino-Danish College, University of Chinese Academy of Sciences, 19(A) Yuquan Road, Shijingshan District, 100049 Beijing, China;2. Department of Digitalization, Copenhagen Business School, Howitzvej 60, 2000 Frederiksberg, Denmark;1. University of the Aegean, Department of Information and Communication Systems Engineering, Gorgyras and Palama 2, Karlovassi 83200, Samos, Greece;2. University of Patras, Industrial Management and Information Systems Lab, Department of Mechanical Engineering and Aeronautics, 26110 Patra, Greece;1. Department of Health Administration and Public Health, John G. Rangos School of Health Sciences, Duquesne University, Pittsburgh, PA, USA;2. Hospital Management Research Center, Health Management Research Institute, Iran University of Medical Sciences, Tehran, Iran |
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| Abstract: | The nascent adoption of Artificial Intelligence (AI) in the public sector is being assessed in contradictory ways. But while there is increasing speculation about both its dangers and its benefits, there is very little empirical research to substantiate them. This study aims at mapping the challenges in the adoption of AI in the public sector as perceived by key stakeholders. Drawing on the theoretical lens of framing, we analyse a case of adoption of the AI system IBM Watson in public healthcare in China, to map how three groups of stakeholders (government policy-makers, hospital managers/doctors, and Information Technology (IT) firm managers) perceive the challenges of AI adoption in the public sector. Findings show that different stakeholders have diverse, and sometimes contradictory, framings of the challenges. We contribute to research by providing an empirical basis to claims of AI challenges in the public sector, and to practice by providing four sets of guidelines for the governance of AI adoption in the public sector. |
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