The Implementation of Adaptive Governance of Artificial Intelligence in the Public Sector in the UAE
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Date
2024-05
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The British University in Dubai (BUiD)
Abstract
Artificial intelligence (AI) has been constantly progressing, with a recent hype lead by developments in artificial neural networks, such as large language models, that resulted in the evolution of generative AI solutions. Today, AI use cases are widely spread across different sectors, and governments are no exception. One example is the government of the United Arab Emirates (UAE), which has put tremendous efforts into sustaining the implementation of AI in the public sector, including implementing AI in public services. As AI implementation is highly affected and steered by its governance style, this study explores the use of adaptive governance (AG) for the implementation of AI in public services in the UAE. It utilises an exploratory qualitative research approach to investigate the challenges of AI implementation in public services in the UAE, the set of AG principles applicable to the context, and the factors that either support or constrain the implementation of such principles. The study results show that all challenges fall within the challenge categories previously identified in the literature. Also, five principles of AG were identified, which are efforts to mobilize internal and external capabilities, continuous adjustments to deal with uncertainty, wider participation to spot and internalise developments, ambidexterity, and knowledge dissemination among stakeholders. Also, eighteen factors were identified and categorized into five themes, which are organisational capabilities, stakeholders’ relations, situational awareness, enabling environment, and public welfare. Finally, a conceptual framework is developed to explain the implementation of AG of AI in public services in the UAE.