Do Attractive Women Have More Pull With Investors? The Answer May Surprise You.
It's a complicated and crowded time to talk about gender and the workplace. But it's an important conversation nonetheless. Women are still vastly underrepresented in traditionally male (and high-paying) industries such as computer science, engineering, and science. And according to recent data, less than 13 percent of Silicon Valley engineers are female, women represent just 4.2 percent of senior venture capitalists, and a measly 3 percent of tech startups are founded by women. And then there's the ample anecdotal evidence detailing Silicon Valley's testosterone-fueled "brogrammer" culture.
The question of how to achieve better gender balance is a subject of hot debate. Proposals range from banning the word “bossy”, to creating active mentor networks, to counseling women against the dangers of “having a chip on their shoulder.” And then there are those who believe that the whole issue is simply overblown hype.
Judging by two new studies published last week in the Proceedings of the National Academy of Science, it’s really not. Gender bias against women in traditionally male dominated fields, both studies suggest, is both subtle and pervasive, an insidious influence that doesn't have an easy, one-stop antidote. (Banning "bossy" isn’t going to cut it.)
A man and woman deliver a pitch…
In the first study, researchers at Harvard Business School showed slideshows of U.S. entrepreneurial pitch competitions to experienced business investors. Some investors watched a slideshows narrated by a female, while some watched one narrated by a male. The investors couldn't actually see the person actually presenting; they could only hear his or her voice.
In both cases, the pitch script was identical. To try and ensure that results weren't affected by a presenter's public speaking ability, researchers also pilot tested the voiceovers so that male-and-female-narrated pitches didn't differ on variables like enthusiasm, confidence and pleasantness.
Again, the content of the pitches were identical. Despite this, "the male-narrated pitch was rated as more 'logical' and 'fact-based,'" says Alison Wood Brooks, the study's lead researcher and social psychologist at Harvard Business School. All in all, investors were 60 percent more likely to invest in a pitch presented by a man.
Adding another layer to the experiment, the investors were given a photo of a man or woman to accompany the narrated pitch. Turns out the attractiveness of the presenter mattered – just not for women. While a handsome man was more likely to attract investor dollars, an attractive female presenter held no advantage over her plainer peers.
While this initially surprised Brooks, she says the findings illustrate the 'lack of fit' theory. "When people imagine an entrepreneur, they often imagine a man, perhaps a physically attractive man," she says. "They don’t usually imagine a woman." For some investors, Brooks theorizes, a female presenter clashes against their preconceived picture of what an entrepreneur should look like – her attractiveness, therefore, is irrelevant.
For Woods, this study illustrates the difficulty of trying to achieve gender equality in traditionally male-dominated fields. "We think many people agree that men and women deserve equity in the workplace and in entrepreneurship," she says, but biases can be sneaky; often, they operate fully beneath our conscious awareness. How to fix this? Sadly, Woods says, there's really no easy solution. "It will be difficult to un-do subconscious biases like the one we’ve captured in our paper…they are culturally constructed over very long periods of time."
Who would you hire to do math?
In the second study, three business school professors took on the issue of gender bias and math by asking nearly 200 volunteers to evaluate 96 candidate pairs and hire one person to complete a series of arithmetic tasks that men and women, on average, performed equally well.
With no information other than the job candidates' appearance, the volunteers (or "managers") were twice as likely to pick a man over a woman. Interestingly, this was true for both male and female "managers."
Next, the experimenters allowed job candidates to predict how they would perform the task at hand. While men tended to boast and inflate their ability, women often downplayed theirs. Most managers, both male and female, didn't compensate for this and once again, they were twice as likely to hire a man as a woman.
Finally, the experimenters told the managers how each applicant had done on a previous math test. Even with this highly predictive, objective indicator of success, gender discrimination did not disappear altogether; managers were still 30 percent more likely to hire a man for the job. And when they knowingly chose the lower-performing candidate, two-thirds of the time they were choosing the male applicant.
Each manager was also given an “implicit association test,” or I.A.T., to measure their gender bias when it comes to math and science. “The more biased someone was against woman and math, the less they were able to adjust and recognize that men boast,” says Luigi Zingales, the study’s lead researcher. “If you are biased against women, you penalize them for a negative stereotype that they aren’t good at math but you don't penalize men for boasting.”
In economics, there is a distinction between rational discrimination (“Which sounds terrible, Zingales says, “but means that you are biased against a group of people because you have relevant information about them”) versus a complete stereotype, where the bias is unfounded.
You can see complete stereotyping at work in the third experiment. Despite the fact that managers had access to highly predictive data, many chose to ignore it. An unbiased person, Zingales says, will be able to choose a candidate based on past performance alone. But bias against woman and math can cloud a person’s ability to pick the best candidate. “You don’t update fully,” he says. “You are essentially resistant to processing information, which keeps you from making a decision based on predictive data.”
So what to do? Simply having more women in the office may also work to decrease gender bias; a lack of women, be it in a company, field or region (Silicon Valley) can be self-perpetuating. “An employer can only observe the performance the women he hires. If he hires twice as many men as women, he has much better information about the men than about the women, and he’s less likely to update his position.”
It’s a classic chicken or egg problem, but Zingales believes strides can be made if employers simply recognize that bias exists in the first place. If he was ever put in charge of running a firm, he says, he’d make it mandatory for those in charge of hiring to take an I.A.T test. Bias, while often subconscious, can nonetheless be powerful. “Awareness goes a long way,” he says.
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