Algorithmic profiling as a source of hermeneutical injustice

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Abstract

It is well-established that algorithms can be instruments of injustice. It is less frequently discussed, however, how current modes of AI deployment often make the very discovery of injustice difficult, if not impossible. In this article, we focus on the effects of algorithmic profiling on epistemic agency. We show how algorithmic profiling can give rise to epistemic injustice through the depletion of epistemic resources that are needed to interpret and evaluate certain experiences. By doing so, we not only demonstrate how the philosophical conceptual framework of epistemic injustice can help pinpoint potential, systematic harms from algorithmic profiling, but we also identify a novel source of hermeneutical injustice that to date has received little attention in the relevant literature, what we call epistemic fragmentation. As we detail in this paper, epistemic fragmentation is a structural characteristic of algorithmically-mediated environments that isolate individuals, making it more difficult to develop, uptake and apply new epistemic resources, thus making it more difficult to identify and conceptualise emerging harms in these environments. We thus trace the occurrence of hermeneutical injustice back to the fragmentation of the epistemic experiences of individuals, who are left more vulnerable by the inability to share, compare and learn from shared experiences.

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Milano, S., & Prunkl, C. (2025). Algorithmic profiling as a source of hermeneutical injustice. Philosophical Studies, 182(1), 185–203. https://doi.org/10.1007/s11098-023-02095-2

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