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  1. Why we should talk about institutional (dis)trustworthiness and medical machine learning.Michiel De Proost & Giorgia Pozzi - forthcoming - Medicine, Health Care and Philosophy:1-10.
    The principle of trust has been placed at the centre as an attitude for engaging with clinical machine learning systems. However, the notions of trust and distrust remain fiercely debated in the philosophical and ethical literature. In this article, we proceed on a structural level ex negativo as we aim to analyse the concept of “institutional distrustworthiness” to achieve a proper diagnosis of how we should not engage with medical machine learning. First, we begin with several examples that hint at (...)
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  • AI-Related Risk: An Epistemological Approach.Giacomo Zanotti, Daniele Chiffi & Viola Schiaffonati - 2024 - Philosophy and Technology 37 (2):1-18.
    Risks connected with AI systems have become a recurrent topic in public and academic debates, and the European proposal for the AI Act explicitly adopts a risk-based tiered approach that associates different levels of regulation with different levels of risk. However, a comprehensive and general framework to think about AI-related risk is still lacking. In this work, we aim to provide an epistemological analysis of such risk building upon the existing literature on disaster risk analysis and reduction. We show how (...)
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  • Affective Artificial Agents as sui generis Affective Artifacts.Marco Facchin & Giacomo Zanotti - 2024 - Topoi 43 (3).
    AI-based technologies are increasingly pervasive in a number of contexts. Our affective and emotional life makes no exception. In this article, we analyze one way in which AI-based technologies can affect them. In particular, our investigation will focus on affective artificial agents, namely AI-powered software or robotic agents designed to interact with us in affectively salient ways. We build upon the existing literature on affective artifacts with the aim of providing an original analysis of affective artificial agents and their distinctive (...)
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  • The human biological advantage over AI.William Stewart - forthcoming - AI and Society:1-10.
    Recent advances in AI raise the possibility that AI systems will one day be able to do anything humans can do, only better. If artificial general intelligence (AGI) is achieved, AI systems may be able to understand, reason, problem solve, create, and evolve at a level and speed that humans will increasingly be unable to match, or even understand. These possibilities raise a natural question as to whether AI will eventually become superior to humans, a successor “digital species”, with a (...)
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