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  1. Algorithmic Political Bias—an Entrenchment Concern.Ulrik Franke - 2022 - Philosophy and Technology 35 (3):1-6.
    This short commentary on Peters identifies the entrenchment of political positions as one additional concern related to algorithmic political bias, beyond those identified by Peters. First, it is observed that the political positions detected and predicted by algorithms are typically contingent and largely explained by “political tribalism”, as argued by Brennan. Second, following Hacking, the social construction of political identities is analyzed and it is concluded that algorithmic political bias can contribute to such identities. Third, following Nozick, it is argued (...)
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  • Transparency as Manipulation? Uncovering the Disciplinary Power of Algorithmic Transparency.Hao Wang - 2022 - Philosophy and Technology 35 (3):1-25.
    Automated algorithms are silently making crucial decisions about our lives, but most of the time we have little understanding of how they work. To counter this hidden influence, there have been increasing calls for algorithmic transparency. Much ink has been spilled over the informational account of algorithmic transparency—about how much information should be revealed about the inner workings of an algorithm. But few studies question the power structure beneath the informational disclosure of the algorithm. As a result, the information disclosure (...)
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  • The Limits of Calibration and the Possibility of Roles for Trustworthy AI.Ulrik Franke - 2024 - Philosophy and Technology 37 (3):1-7.
    With increasing use of artificial intelligence (AI) in high-stakes contexts, a race for “trustworthy AI” is under way. However, Dorsch and Deroy (Philosophy & Technology 37, 62, 2024) recently argued that regardless of its feasibility, morally trustworthy AI is unnecessary: We should merely rely on rather than trust AI, and carefully calibrate our reliance using the reliability scores which are often available. This short commentary on Dorsch and Deroy engages with the claim that morally trustworthy AI is unnecessary and argues (...)
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