AI skepticism – Outgoing Girls Who Code CEO Tarika Barrett says the unease young people—including many women and girls—feel about artificial intelligence should not be dismissed. Instead, she argues their caution can shape how AI is built, adopted, and used responsibly as cod
For more than a decade. Girls Who Code has worked to prepare young women for careers in the tech industry and push for greater gender parity in computer science. Now. as artificial intelligence ushers in a new era—along with pressure to keep up—Tarika Barrett says the organization is confronting an uncomfortable reality: many students are skeptical. and that skepticism is showing up in how they talk. what they avoid. and what they fear.
Barrett, the outgoing CEO of Girls Who Code, will be leaving the organization this summer. In an interview edited for length and clarity. she described how uneasiness about AI is not just a misunderstanding that can be corrected with upbeat messaging. She says it’s grounded in concerns students genuinely carry—errors. energy use. and the possibility that the technology strengthens the already-massive influence of tech billionaires. Her argument is simple and pointed: people shouldn’t disregard those worries; they should be harnessed to guide what comes next.
The pushback appears early and publicly. Many young graduates, Barrett said, aren’t excited about working with AI. Students—shaped by tech executives’ claims that frontier labs may automate away large numbers of jobs—are booing graduation speakers who bring up large language models (LLMs). Even computer science majors who still want to reach Silicon Valley face a different kind of uncertainty. as AI rapidly reduces the number of coders companies actually need.
In Barrett’s telling, a further split runs along gender lines. Women, she said, seem disproportionately biased against using AI. She connected that apprehension to multiple forces: anxiety about AI making errors. being turned off by AI’s energy demands. and concern about how AI could amplify the influence of tech billionaires. The result, she said, is a gap in AI usage that appears particularly along gender lines.
Barrett pointed to studies that suggest the gap is measurable. She referenced data from Harvard Business School indicating women adopt AI tools at 25% lower rate than men. But she also stressed the issue isn’t simply lower enthusiasm or slower uptake. Women, Barrett said, have reported feeling limited, feeling prohibited, and being uncertain about their employer’s AI policy. In her view, the uncertainty matters: what happens when an employer’s policy isn’t clear?. She framed it as an incentive structure—risk-takers often move quickly. while those approaching AI with intention and care hold back.
She also described another barrier her organization saw in its research: participants reported being actively discouraged from pursuing skill development unrelated to their work. That was “really kind of crazy” in Barrett’s words. given how much AI knowledge is out there and how people are trying to get information wherever they can.
At the center of Girls Who Code’s approach is social capital—built through community. Barrett said the organization has reached 860. 000 students. and that its model is rooted in sisterhood and connections that often become the way people land their first jobs. She said that same pattern is showing up in AI adoption: knowledge and who gets to share it are not spreading evenly. She added that respondents to their survey saw the value of mentors. but that it becomes harder to sustain relationships as people move up their career trajectories.
Barrett also questioned whether the newest wave of LLM companies is matching the level of urgency seen in earlier diversity efforts. She noted new-generation companies like OpenAI and Anthropic. along with others. and described how her Alumni Advisory Council visited Girls Who Code’s office. The council includes a group of twentysomething women who she said have become a “huge resource.” Listening to what they share. Barrett said Girls Who Code isn’t seeing the same passion that once existed for bringing everyone along.
She attributed the hesitation partly to the speed of the AI arms race. In her account. she said the problem isn’t that people aren’t aware of the need for inclusion; it’s that the inclusion work can get buried under the urgency to “do it as quickly as possible” and push the follow-up to later. Barrett said that mindset doesn’t produce the kind of technology she wants to see.
When she described what happens when young people—especially people from historically underrepresented groups—come to the table. she linked it directly to outcomes. She said the resulting technology meets needs more effectively. At the same time. she said young people’s attitudes about AI are mixed. and large swaths of them aren’t excited. She pointed to the idea that exposure is critical. but she warned that if educators and industry aren’t careful. they could lose an entire generation that was once told tech was the answer.
“The fear,” in Barrett’s framing, is not just about feelings—it’s about opt-outs. If students believe there aren aren’t viable prospects, she said they may step away from tech. Their opting out, Barrett added, would mean the industry loses access to voices that could shape high-impact technology.
That loss, she argued, would be especially dangerous when the concerns driving skepticism are actually thoughtful. She offered a hypothetical young woman: someone worried about ethical challenges raised by AI. thinking about environmental or electricity use. or fearing mistakes on the job. Barrett said she would tell that person that paralysis and careful concern can be a superpower because it usually means they won’t use AI “willy-nilly.” She said it signals that a young person is thinking about environmental impact and is acting as a careful user. consumer. and decipherer of what they’re getting.
Barrett urged that reticence shouldn’t be judged too harshly. She described reticence as discernment—especially for women. That discernment, she said, is part of how thoughtful use will happen, and she encouraged young people to seek out mentors and peers who are thoughtfully using AI.
She also returned to what Girls Who Code believes young people need most: mentors who bring them along and talk through good use cases. or what a game-changing outcome with AI could look like. At the same time, Barrett said the goal shouldn’t be total opt-out. If someone decides not to use AI right now, she said maybe that decision has a good reason. But she urged young people to keep their eyes and ears open because opportunities exist.
Her message lands with a practical confidence. Barrett said that when a young person feels concerned—especially women—it’s often something worth listening to. She suggested that concern about AI could be what ultimately saves the deployment of the technology. If people’s voices are missing, she said, “we’re in trouble.”.
The sequence of her argument holds together tightly: students’ public booing and career anxiety sit alongside gendered gaps in adoption and uncertainty at work. From there. her solution keeps circling back to the same lever—mentorship and intentional use—so skepticism becomes a guide rather than a dead end.
Girls Who Code Tarika Barrett AI skepticism large language models gender parity women in tech computational thinking AI adoption gap mentorship workforce automation