5 found

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  1.  3
    A Probabilistic Theory of Trust Concerning Artificial Intelligence: Can Intelligent Robots Trust Humans?Saleh Afroogh - 2022 - AI and Ethics 2 (3).
    In this paper, I argue for a probabilistic theory of trust, and the plausibility of “trustworthy AI” in which we trust (as opposed to mere reliance). I show that the current trust theories cannot accommodate trust pertaining to AI, and I propose an alternative probabilistic theory, which accounts for the four major types of AI-related trust: an AI agent’s trust in another AI agent, a human agent’s trust in an AI agent, an AI agent’s trust in a human agent, and (...)
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  2. AI Ethics: The Case for Including Animals.Peter Singer - 2022 - AI and Ethics 2 (3).
    The ethics of artificial intelligence, or AI ethics, is a rapidly growing field, and rightly so. While the range of issues and groups of stakeholders concerned by the field of AI ethics is expanding, with speculation about whether it extends even to the machines themselves, there is a group of sentient beings who are also affected by AI, but are rarely mentioned within the field of AI ethics—the nonhuman animals. This paper seeks to explore the kinds of impact AI has (...)
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  3.  34
    Responsibility Gaps and the Reactive Attitudes.Fabio Tollon - 2022 - AI and Ethics 1 (1).
    Artificial Intelligence (AI) systems are ubiquitous. From social media timelines, video recommendations on YouTube, and the kinds of adverts we see online, AI, in a very real sense, filters the world we see. More than that, AI is being embedded in agent-like systems, which might prompt certain reactions from users. Specifically, we might find ourselves feeling frustrated if these systems do not meet our expectations. In normal situations, this might be fine, but with the ever increasing sophistication of AI-systems, this (...)
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  4. The Struggle for Recognition in the Age of Facial Recognition Technology.Rosalie Waelen - 2022 - AI and Ethics 1:1-8.
    Facial recognition is a promising emerging technology, but it sometimes fails to recognize people adequately. Facial recognition applications have been found to regularly misidentify certain demographics, misinterpret traits like gender, age, beliefs, or emotions, and categorize individuals in ways that do not resonate with their own sense of identity. In this paper, I argue that in each of these cases, the person who has their face analyzed is not merely misidentified or misunderstood, but misrecognized in an ethically relevant sense. Following (...)
     
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  5.  24
    Explainable Machine Learning Practices: Opening Another Black Box for Reliable Medical AI.Emanuele Ratti & Mark Graves - 2022 - AI and Ethics:1-14.
    In the past few years, machine learning (ML) tools have been implemented with success in the medical context. However, several practitioners have raised concerns about the lack of transparency—at the algorithmic level—of many of these tools; and solutions from the field of explainable AI (XAI) have been seen as a way to open the ‘black box’ and make the tools more trustworthy. Recently, Alex London has argued that in the medical context we do not need machine learning tools to be (...)
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