Friday October 07, 2016
How algorithms are targeting implicit bias
Innovative research programs targeting implicit bias offer new insights and strategies for addressing unconscious prejudice.
A study at Yale University released this week asked 135 teachers to identify challenging tendencies in a video which featured four children: a white girl and boy, and a black girl and boy. Despite the fact that none of the children depicted bad behaviour, 42 per cent of the teachers characterized the black boy as needing more attention.
Although it is a universal trait, studies reveal there are various degrees of implicit bias.
Stephen Shea, the Canadian managing partner of talent with EY, says there are ways to mediate unconscious discrimination. "Create self-awareness — whether it's the tests, whether it's inclusive workshops, whether it's [changing] the whole culture of how you work in high performing teams."
Tony Greenwald, a social psychologist at the University of Washington and co-author of Blind Spot: Hidden Biases of Good People, agrees that good intentions are not enough, and wages tool kits informed by research are the best way to lessen bias. "Those are things that can actually change procedures in ways that take implicit bias out of operation. Bias is something that can be faced only by preventing it from playing a role."
The Current delves into the expansion of implicit bias research, what the data reveals, and to what extent public organizations, like the police force, are taking efforts to combat unconscious discrimination.
Listen to the full conversation at the top of this web post.
This segment was produced by The Current's John Chipman and Pacinthe Mattar.