We all harbor biases — subconsciously, at least. We may automatically associate men with law enforcement work, for example, or women with children and family. In the workplace, these biases can affect managers’ hiring and promotion decisions.
So when Pete Sinclair, who’s chief of operations at the cybersecurity firm RedSeal, realized that — like many other Silicon Valley companies — his company had very few female engineers and few employees who weren’t white, Chinese or Indian, he wanted to do something about it.
“I was trying to figure out, ‘How do I expand my employment base to include those under-represented groups?’ Because if we do appeal to those, we’ll have more candidates to hire from,” he says.
Unitive’s software is based on social science research, including work by Anthony Greenwald, a psychologist at the University of Washington who developed the seminal implicit-association test in the 1990s. It measures how easy — or difficult — it is for the test-takers to associate words like “good” and “bad” with images of Caucasians or African-Americans.
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