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Imagine coming home to a cute 20-year old who is always excited to see you, calls out “Missed you, darling” when you return home from work, and with whom there is never any conflict. The Gatebox male designers who created holographic virtual girl, Azuma Hikari, have just revealed their bias for a certain type of female companion.
There’s nothing intrinsically bad about that, of course; bias—the tendency to favor one thing over another—is the mental shortcut we all use to successfully navigate complex environments when bombarded with more information than we can possibly cope with. “The problem comes,” says Tiffany Jana, co-author of Overcoming Bias: Building Relationships Across Differences, “when you allow unconscious biases—or blindspots—to influence your behavior and the way you treat others.” This issue is increasingly crucial for millennials who soon, if not already, will lead more diverse groups than ever before.
So how do you go about checking your biases aren’t unconsciously favoring certain people and practices over others?
You might start by taking one of Project Implicit’s Association Tests (IAT), housed by Harvard University. Which is what I asked four people aged 28 to 30 to do: go online, chose any of the 14 topics offered, spend 10 minutes answering questions devised by Harvard scientists and others interested in educating the public about “thoughts and feelings outside of conscious awareness and control,” and be interviewed about the results. While some were naturally anxious about potentially discovering they weren’t as tolerant as they thought, the IAT measures beliefs, attitudes and opinions, not behavior. Even finding out you have a preference for straight over gay people, for example, doesn’t mean you’re going to act in a homophobic way. What these millennials did discover, however, revealed some fascinating insights into the conscious and unconscious influencers of bias.
Of the four participants only Cuban-American law student Eddie’s result showed a “strong preference” that aligned with 75% of the IAT’s sample of web participants—for thin over obese people. In explaining why, he illustrated how bias is one of the mechanisms we all use “for reading people quickly and navigating the world effectively.” After meeting a “rather rotund” real estate broker, this put him on guard as to whether, “being overweight and rather disheveled in appearance will translate into some kind of professional disorganization.”
Eddie’s choice of test was personally relevant, as it was for the others. About to start law school he was “passionate about maintaining a professional image” not least because, “being overweight doesn’t fit the image of the law, which is a very conservative field,” and could be, “a hindrance in, say, trying to sway a jury.”
The results for the other millennials, however, were “outliers,” largely influenced by their family circumstances and upbringing.
After taking the skin tone test, U.S.-born Priti—from a Southeast Asian family—reported a “slight automatic preference for dark skinned over light skinned people,” a result found in just 7% of the IAT’s web sample. She is only too aware that Indian standards of beauty favor lighter skin, because her dark-skinned mother was teased as a child in Mumbai and still talks about it. While Priti was brought up to treat everyone the same, “It seems I’ve overcompensated to the other end of the scale.” Not until she took the test did she realize she also finds it easier to visually recall and describe people of color rather than those with light skins.
Both Heather, a white female, and Matt who is African-American, took the test called Gender-Career—with different but similarly contrarian results. Heather, who works in data management for a research organization, reported a “slight automatic association with male and family, and female with career,” typical of just 5% of IAT takers. While this is the reverse of the stereotype, “It makes sense because my father stayed home to be my primary caregiver while my mother worked,” says Heather.
Matt, on the other hand, showed little or no automatic association between female and family and male with career, common to 17% of IAT’s web sample. Raised by a single mother and strongly influenced by his aunt, “both of whom were working professionals and incredibly entrepreneurial,” Matt, a diversity educator, regards his result as indicative of his view that women are “very capable leaders” who have mentored and supported him throughout his career. It also reflects his research and ongoing work helping others understand the systemic and institutional nature of bias so they can begin to help eliminate it.
Matt’s colleague at Wake Forest University, Shayla Herndon-Edmunds, Director of Diversity Education in the Office of Diversity and Inclusion, has been using the IAT for six years with students, faculty and staff as a way to help participants process their results privately before embarking on the “high risk activity” of group discussions. While awareness is the first step, says Herndon-Edmunds, it’s important to seek “training to learn about actionable steps, tips and best practices so that we’re contributing toward equitable treatment for all.”
An important next step, says Tiffany Jana, involves what these four participants did easily and quickly, which was to make sense of their bias by grounding it in reality. Usually, she says, this takes at least a week following reactions ranging from calling results “garbage” to feeling anxious about what bias says about someone. “Numerous studies show that levels of bias are consistent across generations when controlled for age. But to be fluent in talking about and owning biases openly appears to be different for millennials compared with older generations.”
Given current pervasive nature of gender bias within the tech community, looking forward, that has got to be a good thing. Right?
(Additional Note May 9th, 2017: For those who criticize the Implicit Bias Test and feel it isn't valid, you may be interested in another approach covered in an article entitled: Is This How Discrimination Ends? A New Approach to Implicit Bias featured in The Atlantic.)
(A version of my article appeared originally in Fast Company in April 2017)
