Steve Jobs, Bill Gates, Elon Musk, Jeff Bezos – the technology industry is dominated by men. In 2021, 75% of employed computer scientists and 84% of employed engineers in the United States were men.
And that’s cause for concern. Consider exploiting generative artificial intelligence tools for video. Deepfake porn overwhelmingly targets women and, surprisingly, some teenage girls as well. Can you trust an all-male team of software engineers to make responsible and informed decisions about such tools? Software engineers make up a small portion of the world’s population, but the products they create make a difference to the rest of society. can have a significant impact on parts of
Compared to men, women generally express ethical and privacy-related concerns about AI and place greater emphasis on safety and accountability. The technology industry needs more diverse perspectives to prevent the real harm that AI technologies can bring to our world.
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However, my latest research as a psychologist and education researcher has revealed major obstacles to achieving a more representative workforce. It’s a stereotype about technology that appears very early in a child’s development. In a study published this month, my colleagues and I found that at age 6, children already view girls as inferior to boys in computer science and engineering.
We also found that gender stereotypes are not the same across all STEM subjects (science, technology, engineering, and math). In fact, math stereotypes are far less gender-based than many researchers often assumed. This nuance helps point to new ways to broaden participation in STEM fields. Most previous research has focused on the stereotype that girls are “bad at math.” But my colleagues at the Institute of American Studies and the University of Cambridge and I found that there is mixed evidence about whether children really hold that belief. Some studies show that children absorb the stereotype that girls are worse at math than boys, while other studies find just the opposite.
We embarked on a five-year study to synthesize more than 40 years of previous research on children’s gender stereotypes regarding their abilities in STEM. We compiled a large dataset of over 145,000 children from 33 countries who measured stereotypes in a variety of ways. For example, a study might ask children, “Are girls or boys better at computer coding?”
A clear pattern emerged. Technology stereotypes are much more male-biased than math stereotypes. In other words, children are more likely to think that computer and engineering skills are “for boys” than math skills.
And this disparity between STEM fields starts early. For example, 52 percent of six-year-olds think boys are better at engineering, while 10 percent think girls are better at engineering, giving an initial male bias of 42 percentage points. In computing, a male bias is also present, albeit to a lesser extent, as early as 6 years of age. However, when it comes to math, the percentage of 6-year-olds who say boys are better at math (28 percent) and the percentage of 6-year-olds who say girls are better at math (32 percent) are about the same. It has been shown that there is no clear winner. (The remaining children did not think one group was better than the other.) These differences reflect related patterns in adults. For example, in the United States, 40 percent of employed mathematicians are women, but only 16 percent of employed engineers are women. Still, it’s surprising that children as young as 6 years old have such nuanced beliefs about different STEM fields. Does a 6-year-old even know what an “engineer” is?
Viewed in the broader context, the mathematics findings are not all that surprising. For example, girls do better in math than boys. Additionally, research shows that children generally think success in school is a “girl thing.” These contextual characteristics may reduce male bias toward mathematics, especially when mathematics is perceived as a school subject.
On the other hand, children’s stereotypes about technology are more likely to come from outside the classroom, such as depictions of male computer geeks in movies, news media, and television shows. Of course, young children can also misunderstand the work of computer scientists and engineers. For example, many English-speaking children assume that engineers repair car engines because the word “engineer” includes the word “engine.” That way, kids can pass on masculine stereotypes about auto mechanics to engineers.
Girls at a young age are to some extent isolated from these masculine stereotypes. It’s due to a phenomenon that developmental psychologists call in-group bias. Have you ever heard a girl exclaim, “Girls rule, boys drool”? Children between the ages of 5 and 7 tend to have a strong preference for their own gender. Mathematics is one example. Generally, when asked in early childhood which one is better at a subject, boys prefer boys and girls prefer girls.
This in-group bias protects the youngest girls from stereotypes about technology to some extent. For example, among 6-year-old girls, 34 percent say girls are better at computing, but only 20 percent say boys are better, indicating a female bias. Masu.
However, this pattern changes rapidly with age as cultural stereotypes give way to in-group prejudice. Between the ages of 8 and 10, more girls say that boys are better at computing than say the opposite. This male bias increases even more in middle school and high school. These rapid changes could limit girls’ future aspirations in high-demand technology fields such as AI.
In contrast, boys of all ages, on average, consistently favor boys in all STEM fields. Despite this relatively stable trend in STEM, boys rapidly learn stereotypes that get in the way of reading and writing. By the third year of high school, a clear majority of boys (72 percent) believe that girls have better language skills, and only a minority (10 percent) believe that boys have better language skills. ) only.
Overall, our findings point to the need for targeted action. Efforts to address “math girls” and “STEM girls” may not be enough to address the most persistent stereotypes. Rather, these efforts require a strategic focus on the most male-biased sectors, such as technology.
The gender gap in the tech industry is not static. In 1984, women made up 37% of computer science college graduates, the highest percentage at any other time. However, this number currently hovers around 20%. Cultural changes, such as marketing computers to boys, may have pushed girls and women out of the field. If the change is cultural, why can’t we turn back the clock on that particular aspect?
Addressing stereotypes about technology requires a national commitment to expand high-quality engagement in these areas in early childhood and primary education. Research shows that early positive experiences with programming and robotics can ignite curiosity and interest in girls before stereotypes take hold and drive them away. Free apps like ScratchJr allow kids ages 5 to 7 to learn the basics of coding by programming interactive stories and games. But more research is needed to see what early approaches actually reduce the gender gap.
With early positive experiences, girls may rely less on stereotypes to guide future decisions, such as when choosing high school electives. In other words, engaging with technology early on lays the foundation for success in later grades and career stages. These steps to expand participation in STEM will benefit both technology and society. Consider Rebecca Portnoff, director of data science at the nonprofit Thorn. She uses her computer science expertise to develop AI tools and safety-focused design guidelines aimed at stopping the creation and dissemination of child sexual abuse images. AI technology has great potential to transform society. Having diverse voices in the technology industry helps us harness that power for social good.
Are you a scientist specializing in neuroscience, cognitive science, or psychology? And have you read any recent peer-reviewed papers you’d like to write about? Submit your proposal scientific americanDaisy Yuhas, editor of Mind Matters dyuhas@sciam.com.
This is an opinion and analysis article, and the views expressed by the author are not necessarily those of Scientific American.
