PhilSci Archive

What We Can (And Can’t) Infer About Implicit Bias From Debiasing Experiments

Byrd, Nick (2019) What We Can (And Can’t) Infer About Implicit Bias From Debiasing Experiments. [Preprint]

Full text not available from this repository.

Abstract

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, and 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 finds philosophical and empirical problems with that argument. When the problems are solved, the conclusion is only half right: implicit bias is not necessarily unreflective, but it seems to be associative. Further, the paper shows that even if legitimate non-associative interventions on implicit bias exist, then both the received view and its recent contender would be false. In their stead would be interactionism or minimalism about implicit bias.


Export/Citation: EndNote | BibTeX | Dublin Core | ASCII/Text Citation (Chicago) | HTML Citation | OpenURL
Social Networking:
Share |

Item Type: Preprint
Creators:
CreatorsEmailORCID
Byrd, Nicknick.a.byrd@gmail.com0000-0001-5475-5941
Keywords: debiasing, dual process theory, implicit bias, implicit association test, associationism, reflectivism, interventionism, causation, philosophy of mind, philosophy of cognitive science, philosophy of science
Subjects: General Issues > Causation
Specific Sciences > Cognitive Science
General Issues > Experimentation
General Issues > Models and Idealization
General Issues > Science Education
Depositing User: Mr Nick Byrd
Date Deposited: 05 Feb 2019 15:12
Last Modified: 05 Feb 2019 15:12
Item ID: 15709
Official URL: http://dx.doi.org/10.1007/s11229-019-02128-6
DOI or Unique Handle: 10.1007/s11229-019-02128-6
Subjects: General Issues > Causation
Specific Sciences > Cognitive Science
General Issues > Experimentation
General Issues > Models and Idealization
General Issues > Science Education
Date: 2019
URI: http://philsci-archive.pitt.edu/id/eprint/15709

Monthly Views for the past 3 years

Monthly Downloads for the past 3 years

Plum Analytics

Altmetric.com

Actions (login required)

View Item View Item