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  1. Individualism, Structuralism, and Climate Change.Michael Brownstein, Alex Madva & Daniel Kelly - 2021 - Environmental Communication 1.
    Scholars, journalists, and activists working on climate change often distinguish between “individual” and “structural” approaches to decarbonization. The former concern choices individuals can make to reduce their “personal carbon footprint” (e.g., eating less meat). The latter concern changes to institutions, laws, and other social structures. These two approaches are often framed as oppositional, representing a mutually exclusive forced choice between alternative routes to decarbonization. After presenting representative samples of this oppositional framing of individual and structural approaches in environmental communication, we (...)
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  • 'I Love Women': An Explicit Explanation of Implicit Bias Test Results.Reis-Dennis Samuel & Vida Yao - 2021 - Synthese.
    Recent years have seen a surge of interest in implicit bias. Driving this concern is the thesis, apparently established by tests such as the IAT, that people who hold egalitarian explicit attitudes and beliefs, are often influenced by implicit mental processes that operate independently from, and are largely insensitive to, their explicit attitudes. We argue that implicit bias testing in social and empirical psychology does not, and without a fundamental shift in focus could not, establish this startling thesis. We suggest (...)
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  • Engineering Equity: How AI Can Help Reduce the Harm of Implicit Bias.Ying-Tung Lin, Tzu-Wei Hung & Linus Ta-Lun Huang - forthcoming - Philosophy and Technology:1-26.
    This paper focuses on the potential of “equitech”—AI technology that improves equity. Recently, interventions have been developed to reduce the harm of implicit bias, the automatic form of stereotype or prejudice that contributes to injustice. However, these interventions—some of which are assisted by AI-related technology—have significant limitations, including unintended negative consequences and general inefficacy. To overcome these limitations, we propose a two-dimensional framework to assess current AI-assisted interventions and explore promising new ones. We begin by using the case of human (...)
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  • What We Can (and Can’T) Infer About Implicit Bias From Debiasing Experiments.Nick Byrd - 2019 - Synthese (2):1-29.
    The received view of implicit bias holds that it is associative and unreflective. Recently, the received view has been challenged. Some argue that implicit bias is not predicated on “any” associative process, but it is unreflective. These arguments rely, in part, on debiasing experiments. They proceed as follows. If implicit bias is associative and unreflective, then certain experimental manipulations cannot change implicitly biased behavior. However, these manipulations can change such behavior. So, implicit bias is not associative and unreflective. This paper (...)
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  • Understanding Implicit Bias: Putting the Criticism Into Perspective.Michael Brownstein, Alex Madva & Bertram Gawronski - 2020 - Pacific Philosophical Quarterly 101 (2):276-307.
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  • Taking Social Psychology Out of Context.Michael Brownstein, Daniel Kelly & Alex Madva - forthcoming - Behavioral and Brain Sciences.
    We endorse Cesario’s call for more research into the complexities of “real-world” decisions and the comparative power of different causes of group disparities. Unfortunately, these reasonable suggestions are overshadowed by a barrage of non sequiturs, misdirected criticisms of methodology, and unsubstantiated claims about the assumptions and inferences of social psychologists.
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  • (How) Should We Tell Implicit Bias Stories?Jennifer Saul - 2018 - Disputatio 10 (50):217-244.
    As the phenomenon of implicit bias has become increasingly widely known and accepted, a variety of criticisms have similarly gained in prominence. This paper focuses on one particular set of criticisms, generally made from the political left, of what Sally Haslanger calls “implicit bias stories”—a broad term encompassing a wide range of discourses from media discussions to academic papers to implicit bias training. According to this line of thought, implicit bias stories are counterproductive because they serve to distract from the (...)
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  • Implicit Bias.Michael Brownstein - 2017 - Stanford Encyclopedia of Philosophy.
    “Implicit bias” is a term of art referring to relatively unconscious and relatively automatic features of prejudiced judgment and social behavior. While psychologists in the field of “implicit social cognition” study “implicit attitudes” toward consumer products, self-esteem, food, alcohol, political values, and more, the most striking and well-known research has focused on implicit attitudes toward members of socially stigmatized groups, such as African-Americans, women, and the LGBTQ community.[1] For example, imagine Frank, who explicitly believes that women and men are equally (...)
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  • Responsibility for Implicit Bias.Jules Holroyd - 2017 - Philosophy Compass 12 (3).
    Research programs in empirical psychology from the past two decades have revealed implicit biases. Although implicit processes are pervasive, unavoidable, and often useful aspects of our cognitions, they may also lead us into error. The most problematic forms of implicit cognition are those which target social groups, encoding stereotypes or reflecting prejudicial evaluative hierarchies. Despite intentions to the contrary, implicit biases can influence our behaviours and judgements, contributing to patterns of discriminatory behaviour. These patterns of discrimination are obviously wrong and (...)
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  • Who’s Responsible for This? Moral Responsibility, Externalism, and Knowledge about Implicit Bias.Natalia Washington & Daniel Kelly - 2016 - In Jennifer Saul & Michael Brownstein (eds.), Implicit Bias and Philosophy, Volume 2: Moral Responsibility, Structural Injustice, and Ethics. Oxford University Press UK.
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