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  1. AI under great uncertainty: implications and decision strategies for public policy.Maria Nordström - 2022 - AI and Society 37 (4):1703-1714.
    Decisions where there is not enough information for a well-informed decision due to unidentified consequences, options, or undetermined demarcation of the decision problem are called decisions under great uncertainty. This paper argues that public policy decisions on _how_ and _if_ to implement decision-making processes based on machine learning and AI for public use are such decisions. Decisions on public policy on AI are uncertain due to three features specific to the current landscape of AI, namely (i) the vagueness of the (...)
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  • Uncertainty and Planning: Cities, Technologies and Public Decision-Making.Stefano Moroni & Daniele Chiffi - 2022 - Perspectives on Science 30 (2):237-259.
    . Decision-making under uncertainty is sometimes investigated as a homogeneous problem, independently of the type of decision-maker and the level and nature of the decision itself. However, when the decision-maker is a public authority, there immediately arise problems additional to those that concern any other decision-maker. This is not always clearly recognised in orthodox discussions on decisions under conditions of uncertainty. This article investigates the methodological, strategic and procedural challenges of taking public decisions in such conditions. It focuses mainly on (...)
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  • Types of Technological Innovation in the Face of Uncertainty.Daniele Chiffi, Stefano Moroni & Luca Zanetti - 2022 - Philosophy and Technology 35 (4):1-17.
    Technological innovation is almost always investigated from an economic perspective; with few exceptions, the specific technological and social nature of innovation is often ignored. We argue that a novel way to characterise and make sense of different types of technological innovation is to start considering uncertainty. This seems plausible since technological development and innovation almost always occur under conditions of uncertainty. We rely on the distinction between, on the one hand, uncertainty that can be quantified (e.g. probabilistic risk) and, on (...)
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