As you know, one of our AIMS School-Wide Goals focuses on diversity. Holton identified diversity as a priority decades ago, and this AIMS goal simply represents a heightened commitment to this critically important work. In keeping with this renewed commitment, I decided to read Blindspot: Hidden Biases of Good People by Mahzarin R. Banaji and Anthony G. Greenwald psychologists at Harvard and the University of Washington, respectively. TIDE, our faculty diversity committee, has subsequently chosen Blindspot as our summer faculty-staff read, so for once, I've finished my homework in advance. Blindspot builds on years of Banaji and Greenwald's research, the core of which rests on the Implicit Association Test (IAT). This test has conclusively shown that most of us have biases we don't realize we have, biases that unknowingly affect our behavior. You may be skeptical about this research, so I encourage you to take the tests (which Banaji and Greenwald do throughout their book).
The IAT, which Greenwald invented, measures how quickly we make associations between two categories and positive and negative words, thereby revealing our automatic preferences. Greenwald and Banaji, who was originally his graduate student, have created numerous versions of the IAT. They introduce the format with a flowers and insects test; not surprisingly, most people have a negative bias towards insects as compared to flowers. Unless we are entomologists, having a negative opinion of bugs won't matter much. Most of their work, however, has focused on more serious biases such as racism, sexism and agism. One IAT, in which the test taker views White and Black faces and positive and negative words, has yielded important data. You might want to take this race test before reading further.
If you are like most people, you went faster when the test asked you to associate white faces with positive words than when it asked you to associate black faces with positive words. Fully 75% of the millions of people (14 million by 2013 with 20,000 more visiting the site weekly) showed this "automatic white preference." Another test measures the association between blacks and whites and harmful and harmless objects. Every ethnic group, including African-Americans, demonstrates an association between the harmful objects and the Black faces.
Another version of the IAT has shown that a significant majority of test takers associate women with family and men with careers: 75% of men and 80% of women – note the discrepancy. They have also found a bias towards men and science and math. The IATs about the elderly reveal negative associations with old people, a bias even the elderly themselves exhibit.
Many of the IAT test-takers, including the authors of the book and very likely you, believe deeply that they hold no prejudice against African-Americans or women or elderly people. Yet, despite these deeply held beliefs, their test results reveal a White preference or a preference for women and family over career or a negative view of older people. Malcolm Gladwell, whose mother is Jamaican, showed white preference when he took the IAT.
So what is going on here? Banaji and Greenwald explain that our brains encompass two separate systems: the reflective and the automatic. The reflective represents our conscious though; the automatic, the less conscious. Our instincts and reflexes reside in the automatic system, the origin of emotional responses sometimes we can't explain. We think we can control our actions and our thoughts because that's the part of our minds we are aware of. However, psychological research increasingly demonstrates that, in fact, this belief is a mirage. Eric Kandel, a Nobel laureate in neuroscience, has said that unconscious thought makes up 80-90% of our brain activity while John Bargh, a Yale psychologist, puts the estimate even higher: 99.44%. The psychologist Daniel Kahneman won a Nobel Prize in economics for proving that we make few decisions rationally, including economic ones, despite what we may think.
When we take the IAT, our automatic brain is categorizing, a strategy that originally helped us survive. If we discovered that a plant was poisonous, we needed mechanisms to discourage us from eating that plant and similar ones again, so we grouped similar items together. Likewise, it made sense in a primitive world to stick with the people we knew as strangers might very well prove unfriendly. As Banaji and Greenwald point out, we still find utility in categorizing people. For example, we categorize sales clerks as people safe to give our credit cards to and individuals dressed as doctors and nurses as people we will generally trust regarding healthcare advice. This kind of categorization is second nature – it's automatic. Of course, it's a short leap from categories to stereotypes, and stereotypes are generally negative.
Do the preferences indicated by the IAT's lead to discriminatory behavior, especially since so many of the people who take the test don't believe they are prejudiced? Research has definitively shown that, yes, these automatic preferences do lead to discriminatory behavior. One example of such research involved a black and a white woman interviewing University of Michigan students, asking them "innocuous" questions and then rating their friendliness based on tested criteria (such as smiling, laughing at joke, longer answers, how close the interviewee moved his/her chair, etc.). The study showed a direct correlation between white preference scores on the IAT and degrees of friendliness towards the black versus the white questioner. Other studies have found preference for white job candidates over equally qualified black candidates (only the names on the resumes were changed) and doctors prescribing superior care to white patients over black ones.
Given the proven connection between these often hidden preferences and prejudicial behavior, many of us probably engage unknowingly in discriminatory actions with some frequency. These could range from being less likely to help a black person than a white one to hiring and to disparate medical treatment.
However, these racial or gender preferences don't just influence our behavior towards others negatively. They can also negatively affect us. Stereotype threat presents one way in which this can happen. For example, women, rightly or wrongly, are generally believed to be less mathematically capable than men. If women are asked to check a gender box before taking a math test, they tend to do less well than if nothing reminded them of their gender prior to the test. Studies have shown a similar poorer performance on standardized tests when blacks are asked to check a race/ethnicity box at the beginning of the assessment.
Using IAT's to test the association of men with math and science, Banaji and Greenwald's colleague Brian Nosek found a correlation between the strength of a woman's association of men and math and how much she liked math and her math SAT score! Similarly, women with strong male/science associations were less likely to major in science. Indeed, the strength of this association markedly better predicted whether a woman would major in science than her stated "gender-math/science stereotypes or even, remarkably enough, math SAT scores." (119)
John Jost, an NYU psychologist, has conducted a number of studies that together "show that members of disadvantaged groups play a perplexing role in maintaining their own disadvantage through their acceptance of self-undermining stereotypes." For example, poor people think they are "unintelligent and therefore less deserving of resources."(118) Women's oft reported hesitation in pursuing opportunities and to negotiate for higher salaries, as well as the imposter syndrome, may result from our own hidden anti-female biases.
Finally, in-group favoritism offers another way in which we unwittingly discriminate. In-group favoritism means taking care of our own. In doing this, we feel as though we are simply helping family or friends, generosity that surely doesn't hurt anyone else. However, such favoritism excludes, even if unintentionally, people from outside our group from an opportunity or some kind of benefit. Over time in-group favoritism accrues to the advantage of the in-group while setting back, if only relatively, out-groups. This is what the "old-boy network" is all about. It's a type of discrimination hard to recognize from the inside, but easy to spot from the outside. So significant is the impact of in-group favoritism that Banaji and Greenwald argue that it "may be the largest contributing factor to the relative disadvantages experienced by Black Americans and other already disadvantaged groups."(162)
A few methods have developed to counter our hidden biases. Symphonies now audition players from behind a curtain so as to obscure the musician's gender, a step that has led to a doubling of female orchestra members. Doctors have guidelines to check all patients' cholesterol levels, male or female, to prevent a physician from neglecting to test women patients since they suffer from heart disease less than men. Such approaches could be used more widely. That said, research shows that our preferences prove surprisingly powerful and no one has yet devised ways to eradicate them. Hopefully, however, by being aware of the influence they can have on our behavior, we can be doubly conscious of not discriminating against others, undermining ourselves, or practicing unbridled in-group favoritism.