Skip
Current Issue
This Month's Print Issue

Follow Fast Company

We’ll come to you.

3 minute read

We Need To Redesign Work To Fight Bias, Because People Won't Get Any Less Sexist

A new book explains that it's not that hard to change the systems at your company so that the bias of your employees doesn't have a chance to affect business decisions.

We Need To Redesign Work To Fight Bias, Because People Won't Get Any Less Sexist

Photo: Hero Images/Getty Images

Leaning in doesn't always work. If you ask for a raise and you're female, studies suggest that your manager might be less likely to want to work with you afterward; you've violated gender norms. If you get offered a new job and try to negotiate better compensation, it might backfire (in extreme cases, it might even cost you your job offer).

Maybe it's not surprising that it's hard for women to fix gender bias at work on their own. HR departments don't do much better: There's basically no proof that the $8 billion that corporations spend on diversity training workshops have any effect. In some cases, they even make things worse by reinforcing stereotypes. Companies spend millions more on leadership training that also doesn't seem to help women.

Instead of trying to change how biased minds work, a new book argues that companies should redesign systems at the workplace—effectively making it harder for flawed humans to screw up. In What Works: Gender Equality By Design, Harvard economist Iris Bohnet lists a few dozen evidence-based design interventions that could help make workplaces more equal.

Compassionate Eye Foundation/David Oxberr

People are inherently biased; it's how we process information. (Take the Implicit Association Test if you want to better understand how biased you actually are). And, as Bohnet explains, it's nearly impossible to eliminate our biases—gender or otherwise—even if they're directly pointed out to us.

"Our minds tend to be relatively stubborn," Bohnet says. "Behavioral design can make it easier for the minds that we've got to make the right decision."

When hiring managers interview candidates, Bohnet suggests that they try comparing people to each other rather than thinking about each one individually. It's a hack that can help managers circumvent bias. In one experiment, researchers asked people to "hire" someone for a math task. People were twice as likely to choose men when they looked at candidates as individuals. But when they compared two candidates to each other, people started choosing the candidate with the best math scores. Suddenly women were being chosen as often—and, critically, the person doing the hiring ended up with the most qualified person.

"This is not just the right thing to do in terms of equality and fairness, but also the smart thing to do," says Bohnet. "Because most companies in fact would say that they want to hire the best people to do the job, and not people who look the best."

She also suggests that companies take demographic information off resumes before hiring managers review them. This is something that also helps deal with racism, as people with names potential employers might associate with African Americans are also less likely to get called for interviews (John gets a lot more callbacks than Jamal). And when interviews happen, they should be structured—i.e., every candidate gets asked the same questions, in the same order, rather than a random conversation.

"I don't know any study that I've found that suggests unstructured interviews are a good predictor of future performance," she says. "They're also the place where bias creeps in." Companies can also test candidates on the actual work they'll be doing, something that's a better predictor of performance than an interview. Others could try using algorithms—this company is using them to find entrepreneurs who are ignored by traditional venture capital, for instance—to help take bias out of the decision-making process.

With all of this, Bohnet says it's crucial for companies to measure what they're doing so they can understand both what problems they have and how their interventions are helping. Google, for example, has studied everything from the optimal number of interviews (four, for them) to the problem of why female employees were twice as likely to quit. When they realized that women were leaving when they became parents, they changed the amount of maternity leave; now, new mothers don't quit any more often than the average employee.

Other companies have made flex time the default for everyone, because they realized that women weren't likely to ask for it—but the lack of the option was also making them leave.

The book lists dozens of other suggestions for experiments that companies can try. "Every leader should be a behavioral designer," Bohnet says.

loading