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  1. AI Surveillance during Pandemics: Ethical Implementation Imperatives.Carmel Shachar, Sara Gerke & Eli Y. Adashi - 2020 - Hastings Center Report 50 (3):18-21.
    Artificial intelligence surveillance can be used to diagnose individual cases, track the spread of Covid‐19, and help provide care. The use of AI for surveillance purposes (such as detecting new Covid‐19 cases and gathering data from healthy and ill individuals) in a pandemic raises multiple concerns ranging from privacy to discrimination to access to care. Luckily, there exist several frameworks that can help guide stakeholders, especially physicians but also AI developers and public health officials, as they navigate these treacherous shoals. (...)
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  • Digital surveillance in a pandemic response: What bioethics ought to learn from Indigenous perspectives.Tereza Hendl & Tiara Roxanne - 2022 - Bioethics 36 (3):305-312.
    Bioethics, Volume 36, Issue 3, Page 305-312, March 2022.
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  • (1 other version)The ethics of algorithms: key problems and solutions.Andreas Tsamados, Nikita Aggarwal, Josh Cowls, Jessica Morley, Huw Roberts, Mariarosaria Taddeo & Luciano Floridi - 2022 - AI and Society 37 (1):215-230.
    Research on the ethics of algorithms has grown substantially over the past decade. Alongside the exponential development and application of machine learning algorithms, new ethical problems and solutions relating to their ubiquitous use in society have been proposed. This article builds on a review of the ethics of algorithms published in 2016, 2016). The goals are to contribute to the debate on the identification and analysis of the ethical implications of algorithms, to provide an updated analysis of epistemic and normative (...)
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  • (1 other version)The ethics of algorithms: key problems and solutions.Andreas Tsamados, Nikita Aggarwal, Josh Cowls, Jessica Morley, Huw Roberts, Mariarosaria Taddeo & Luciano Floridi - 2021 - AI and Society.
    Research on the ethics of algorithms has grown substantially over the past decade. Alongside the exponential development and application of machine learning algorithms, new ethical problems and solutions relating to their ubiquitous use in society have been proposed. This article builds on a review of the ethics of algorithms published in 2016, 2016). The goals are to contribute to the debate on the identification and analysis of the ethical implications of algorithms, to provide an updated analysis of epistemic and normative (...)
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  • Ética y protección de datos de salud en contexto de pandemia: una referencia especial al caso de las aplicaciones de rastreo de contactos.Txetxu Ausín & M. ª Belén Andreu Martínez - 2020 - Enrahonar: Quaderns de Filosofía 65:47.
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  • Bias.Daniel Moseley - 2013 - In Hugh LaFollette (ed.), The International Encyclopedia of Ethics. Hoboken, NJ: Blackwell.
    Following Kahneman and Tversky, I examine the term ‘bias’ as it is used to refer to systematic errors. Given the central role of error in this understanding of bias, it is helpful to consider what it is to err and to distinguish different kinds of error. I identify two main kinds of error, examine ethical issues that pertain to the relation of these types of error, and explain their moral significance. Next, I provide a four-level explanatory framework for understanding biases: (...)
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