Why Stereotypes Are Bad and What You Can Do about Them

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August 13, 2014

According to an Internet quiz I took, I associate men with careers and women with family. But the quiz wasn’t a harmless BuzzFeed time killer. It was the Gender-Career Implicit Bias Test, a survey designed by Harvard researchers to test thought processes.

My result wasn’t wholly unexpected — I live in a culture that regularly questions whether women should work in the first place — but it still stung. After all, I’ve devoted my career to making sure that women have access to bias-free education and workplaces. So if I was harboring a bias in favor of men in the workplace, what must others be thinking? And what does that mean for those of us who want to end bias and stereotypes in the workplace?

What Are Stereotypes?

A “stereotype” is a cognitive shortcut — that is, it allows your brain to make a snap judgment based on immediately visible characteristics such as gender, race, or age. Your brain is hardwired to make quick calls, and that’s ok. The problem comes when we start to apply those stereotypes beyond that immediate impulse. That’s called “bias,” which is basically a belief that a stereotype is true. For example, the stereotype that girls are bad at math can lead to the suggestion that some innate difference between women and men leads to this discrepancy.

In reality, however, girls and women are just as capable as boys and men when it comes to math. The problem is that we live in a culture that bombards girls and women with the notion that math is hard and that they don’t need to worry their pretty little heads about it. And the well-documented “stereotype threat” means that when you hear that you aren’t supposed to be good at something, you underperform, often unconsciously.

In the AAUW research report Why So Few? Women in Science, Technology, Engineering, and Mathematics, my colleagues compiled and analyzed several studies showing that any time students were primed with the directions that men were better than women at a certain skill, the men outperformed the women on the subsequent test of that skill. But when test takers were told that men and women performed equally well in that same skill, the test results evened out. In some cases, the women outperformed the men.

Why Should We Care about Stereotypes and Biases?

Of course, the above example only takes into account an academic setting. Most of us stopped taking tests long ago, and most of us don’t work in the STEM fields either.

But don’t forget that almost all major industries and institutions are still run by men — and usually tall, thin, white men, as Malcolm Gladwell points out in his book on rapid cognition, Blink. The rest of us get unconscious points off for every one of those four criteria we don’t meet — but just about everyone takes those points off, not just the tall, thin, white men already in power. Look at my implicit bias test — I take those points off of myself.

What does this mean? As Gladwell explains in the context of interviewing a black person for a job,

In all likelihood, you won’t be aware that you’re behaving any differently than you would around a white person. But chances are you’ll lean forward a little less, turn away slightly from him or her, close your body a bit, be a bit less expressive, maintain less eye contact, stand a little farther away, smile a lot less, hesitate and stumble over your words a bit more, laugh at jokes a bit less. Does that matter? Of course it does. … [The candidate]’s going to pick up on that uncertainty and distance, and that may well make him a little less certain of himself, a little less confident, and a little less friendly. And what will you think then? You may well get a gut feeling that the applicant doesn’t really have what it takes, or maybe that he is a bit standoffish, or maybe that he doesn’t really want the job.

In other words, stereotypes and biases serve to unfairly and sometimes unintentionally keep qualified, capable people out of jobs or positions of power. Men are the bosses, while women are just bossy. Or not up to the challenge. Or busy taking care of the kids and wouldn’t want the additional responsibility anyway.

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What We Can Do to Combat Stereotypes and Bias

But there’s hope, as evidenced by the test takers described in Why So Few. You can do something to curb the negative effects of bias and stereotypes. Here’s how to get started.

  1. Take the implicit bias test yourself. Visit implicit.harvard.edu and see what biases based on gender, sexuality, age, and race you hold.
     
  2. Admit that you have those biases — it’s ok! It’s what you do next that matters.
     
  3. Keep those biases in mind and take steps to correct them by slowing down and recognizing where they might be coming into play in your life. Are your “gut feelings” about job candidates valid or the product of biases? Are you discounting what a colleague is saying because of your biases? Educators, are biases affecting how you teach, advise, and evaluate students? Parents, are you sending different messages to your sons and daughters?
     
  4. Expose yourself to different experiences. By stepping out of your usual routines, you might better understand people who are different from you or how stereotypes came to be. Travel and education can go a long way toward mitigating biases.
     
  5. Raise awareness of biases. The first step to changing a problem is admitting you have one — and society has a problem. Have conversations with friends and encourage them to take the implicit bias test. And if you’re a college student, go ahead and apply for a Campus Action Project grant, sponsored by Pantene to take steps to fight against bias and stereotypes at your school.

The Good News: It’s Possible to Counteract Stereotypes and Biases

After my less-than-stellar result on the Implicit Bias Test, I decided to put some of the above advice into play. First, I stewed on my result for a few days. I thought about what kind of messages I must be unconsciously accepting and how I could recognize and confront them. I primed myself by thinking of how important my career is to me and about all my other women colleagues and the positive associations I have toward them. I thought about negative reactions that I’d automatically had toward people, and whether those reactions were based on fact or bias. And then I retook the test.

“Your data suggest a moderate association of female with career and male with family compared to male with career and female with family.”

Perhaps an overcorrection, but my new result is proof that our attitudes are malleable, if we care enough to change them.


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