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  1. Algorithmic bias: on the implicit biases of social technology.Gabbrielle M. Johnson - forthcoming - Synthese:1-21.
    Often machine learning programs inherit social patterns reflected in their training data without any directed effort by programmers to include such biases. Computer scientists call this algorithmic bias. This paper explores the relationship between machine bias and human cognitive bias. In it, I argue similarities between algorithmic and cognitive biases indicate a disconcerting sense in which sources of bias emerge out of seemingly innocuous patterns of information processing. The emergent nature of this bias obscures the existence of the bias itself, (...)
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  • Oppressive Things.Shen‐yi Liao & Bryce Huebner - forthcoming - Philosophy and Phenomenological Research.
    In analyzing oppressive systems like racism, social theorists have articulated accounts of the dynamic interaction and mutual dependence between psychological components, such as individuals’ patterns of thought and action, and social components, such as formal institutions and informal interactions. We argue for the further inclusion of physical components, such as material artifacts and spatial environments. Drawing on socially situated and ecologically embedded approaches in the cognitive sciences, we argue that physical components of racism are not only shaped by, but also (...)
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  • The Structure of Bias.Gabbrielle M. Johnson - forthcoming - Mind:fzaa011.
    What is a bias? Standard philosophical views of both implicit and explicit bias focus this question on the representations one harbours, for example, stereotypes or implicit attitudes, rather than the ways in which those representations are manipulated. I call this approach representationalism. In this paper, I argue that representationalism taken as a general theory of psychological social bias is a mistake, because it conceptualizes bias in ways that do not fully capture the phenomenon. Crucially, this view fails to capture a (...)
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