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  1. Countering flaws in algorithm design and applications: a Delphi study.Anu Gokhale - forthcoming - AI and Society:1-13.
    Executives in business and government seek to leverage artificial intelligence (AI), the biggest driver of technological change, to inform decision-making. The intelligence behind AI comes from machine learning (ML) algorithms applied to large datasets. The goal of this research is to investigate the adage that while humans are fallible, computers are impartial with no implicit bias. Toward this purpose, the author used the Delphi research technique to achieve these three objectives: (1) identify and categorize the sources of flaws in algorithm (...)
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  • Tensions in transparent urban AI: designing a smart electric vehicle charge point.Kars Alfrink, Ianus Keller, Neelke Doorn & Gerd Kortuem - 2023 - AI and Society 38 (3):1049-1065.
    The increasing use of artificial intelligence (AI) by public actors has led to a push for more transparency. Previous research has conceptualized AI transparency as knowledge that empowers citizens and experts to make informed choices about the use and governance of AI. Conversely, in this paper, we critically examine if transparency-as-knowledge is an appropriate concept for a public realm where private interests intersect with democratic concerns. We conduct a practice-based design research study in which we prototype and evaluate a transparent (...)
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