In Erin Beeghly & Alex Madva (eds.), An Introduction to Implicit Bias: Knowledge, Justice, and the Social Mind. New York, NY, USA: pp. 77-98 (2020)

Erin Beeghly
University of Utah
If you care about securing knowledge, what is wrong with being biased? Often it is said that we are less accurate and reliable knowers due to implicit biases. Likewise, many people think that biases reflect inaccurate claims about groups, are based on limited experience, and are insensitive to evidence. Chapter 3 investigates objections such as these with the help of two popular metaphors: bias as fog and bias as shortcut. Guiding readers through these metaphors, I argue that they clarify the range of knowledge-related objections to implicit bias. They also suggest that there will be no unifying problem with bias from the perspective of knowledge. That is, they tell us that implicit biases can be wrong in different ways for different reasons. Finally, and perhaps most importantly, the metaphors reveal a deep—though perhaps not intractable—disagreement among theorists about whether implicit biases can be good in some cases when it comes to knowledge.
Keywords Bias, Discrimination, Social Epistemology, Heuristics, Stereotyping
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