Abstract
As public administrations adopt artificial intelligence (AI), we see this transition has the potential to transform public service and public policies, by offering a rapid turnaround on decision making and service delivery. However, a recent series of criticisms have pointed to problematic aspects of mainstreaming AI systems in public administration, noting troubled outcomes in terms of justice and values. The argument supplied here is that any public administration adopting AI systems must consider and address ambiguities and uncertainties surrounding two key dimensions: the algorithms’ results, and how public managers make decisions for and about AI systems’ design. The article is based on bibliographic research in institutional theory perspective that relates the design of AI systems and relevant literature on the decision-making process in public policy. The main finding is to explain why autonomous decision systems continue to reproduce ambiguities and uncertainties when applied in public administration and propose a reflection on AI governance in public administration. This article points to the need for design institutions that immerse themselves in understanding the nuances, details, and potential outcomes of AI governance for public administration. Such institutions would reconcile consequentialist logic with a logic of appropriateness to help navigate and mediate ambiguities and uncertainties.
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Notes
It is interesting to note that Nobel Prize laureate Herbert A. Simon experience. With the concept of bounded-rationality, Simon launches some fundamentals of institutional theory in social sciences and fundamentals of AI decision architecture.
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The author thanks Prof. Johan P. Olsen for his attentive reading and precious suggestions for the first version of this article. The author also thanks the anonymous reviewers who helped to improve the article. Of course, the author is responsible for any inconsistencies or inaccuracies.
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Filgueiras, F. New Pythias of public administration: ambiguity and choice in AI systems as challenges for governance. AI & Soc 37, 1473–1486 (2022). https://doi.org/10.1007/s00146-021-01201-4
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DOI: https://doi.org/10.1007/s00146-021-01201-4