Washington, Jan 21 (IANS) One way of reducing racial bias could be to help people differentiate between faces of individuals of a different race, according to the latest study.
Brown University and University of Victoria researchers learned of this through a new measurement system and protocol they developed to train Caucasian subjects to recognise different African-American faces.
'The idea is that this sort of perceptual training gives you a new tool to address the kinds of biases people show unconsciously and may not even be aware they have,' said Michael J. Tarr, a Brown cognitive neuroscientist and a senior co-author of the paper.
'There is a strong connection between the way we perceive and categorise the world and the way we end up making stereotypes and generalisations about social entities.'
New research suggests that training people to recognise facial differences among individuals of other races may blunt the effect of racial bias.
The programme could be used to train anyone who comes into contact with other races - police officers, social workers or immigration officials - said Tarr, professor of ophthalmology, cognitive and linguistic sciences at Brown.
Sophie Lebrecht, a third-year Ph.D student at Brown and member of Tarr's lab, is the study's lead author. Jim Tanaka, professor at Victoria and Lara Pierce, a graduate student at McGill University, collaborated on the research.
Researchers used 20 Caucasian subjects for the study, which incorporated a measurement developed at Brown and dubbed the Affective Lexical Priming Score (ALPS).
The ALPS measure is similar to, and builds on, a test developed at Harvard University known as the Implicit Association Test, which helps to identify unconscious social biases.
The ALPS measurement involved first showing each subject a series of pictures of different races, such as African-American and Caucasian faces. All the faces were shown in black and white, so subjects would focus on facial features rather than skin colour.
On each ALPS trial, each test subject was shown a picture of a face, which then disappeared. The test subject then saw a word that could be real or nonsense - 'tree' or 'malk', for example - and had to decide whether the word was a real word or nonsense word. Real words could imply something positive or negative.
Lebrecht found that prior to training, subjects more quickly responded if the word was negative and followed an African-American face. Subjects responded more slowly if the word was positive and followed an African-American face.
After using the ALPS to measure each subjects' implicit racial bias, the subjects took part in about 10 hours of facial recognition training. Half learned to tell apart individual African-American faces and half learned simply to tell whether the faces were African-American or not.
The training worked on a number of levels. Individual subjects improved their ability to tell the difference between separate Africa-American faces. Those same subjects who improved that ability also showed the greatest reduction in their implicit racial bias as measured by the ALPS system.
Their positive associations with African-American faces increased and they had fewer negative associations with African-American faces, said a Brown and Victoria release.
The findings were published Wednesday in PLoS ONE.
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