4 found
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  1. “Just” accuracy? Procedural fairness demands explainability in AI‑based medical resource allocation.Jon Rueda, Janet Delgado Rodríguez, Iris Parra Jounou, Joaquín Hortal-Carmona, Txetxu Ausín & David Rodríguez-Arias - 2022 - AI and Society:1-12.
    The increasing application of artificial intelligence (AI) to healthcare raises both hope and ethical concerns. Some advanced machine learning methods provide accurate clinical predictions at the expense of a significant lack of explainability. Alex John London has defended that accuracy is a more important value than explainability in AI medicine. In this article, we locate the trade-off between accurate performance and explainable algorithms in the context of distributive justice. We acknowledge that accuracy is cardinal from outcome-oriented justice because it helps (...)
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  2. May Artificial Intelligence take health and sustainability on a honeymoon? Towards green technologies for multidimensional health and environmental justice.Cristian Moyano-Fernández, Jon Rueda, Janet Delgado & Txetxu Ausín - 2024 - Global Bioethics 35 (1).
    The application of Artificial Intelligence (AI) in healthcare and epidemiology undoubtedly has many benefits for the population. However, due to its environmental impact, the use of AI can produce social inequalities and long-term environmental damages that may not be thoroughly contemplated. In this paper, we propose to consider the impacts of AI applications in medical care from the One Health paradigm and long-term global health. From health and environmental justice, rather than settling for a short and fleeting green honeymoon between (...)
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  3. Ethical assessments and mitigation strategies for biases in AI-systems used during the COVID-19 pandemic.Alicia De Manuel, Janet Delgado, Parra Jonou Iris, Txetxu Ausín, David Casacuberta, Maite Cruz Piqueras, Ariel Guersenzvaig, Cristian Moyano, David Rodríguez-Arias, Jon Rueda & Angel Puyol - 2023 - Big Data and Society 10 (1).
    The main aim of this article is to reflect on the impact of biases related to artificial intelligence (AI) systems developed to tackle issues arising from the COVID-19 pandemic, with special focus on those developed for triage and risk prediction. A secondary aim is to review assessment tools that have been developed to prevent biases in AI systems. In addition, we provide a conceptual clarification for some terms related to biases in this particular context. We focus mainly on nonracial biases (...)
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  4. Interview with Philip Brey.Jon Rueda & Txetxu Ausín - 2021 - Dilemata 34:133-137.
    Interview with Philip Brey in which he clarifies and exemplifies the concept of ‘socially disruptive technology’, offering a series of key aspects for its present and future analysis from the disciplinary perspective of technology ethics. Philip Brey is Professor of Philosophy of Technology at the Department of Philosophy at the University of Twente. He has been a keynote speaker of the International Workshop on Controversies and Polarization on Disruptive Technologies, that took place virtually and in Granada, on October 5th and (...)
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