History suddenly became alive when Castilleja history teacher Brigitte Charaus said, “Women’s voices have not been recognized or heard for so long. Why give them away again?”
Charaus was not talking about the past. She was talking about artificial intelligence. This new perspective stuck with many students.
In classrooms, politics and everyday life, women have historically had to fight to be heard. Even now, studies from the National Association for Research in Science Teaching show that in mixed-gender classrooms, boys are called on more often than girls. For Charaus, AI introduces a new version of an old problem: When students let something else speak for them, the voices that disappear first are often the ones that have historically been ignored.
“At a point in time where women finally have greater power in corporations [and] politics, why turn your voice over?” Charaus asked. “Not even to another person, but to code?”
Considering Castilleja’s motto of “Women Learning, Women Leading,” where leadership and independent thinking are at the core of everything we do, this question becomes even more relevant. Charaus’s concern isn’t just about plagiarism or academic honesty. It’s about practice.
Writing and thinking are not just ways to produce answers; they are how people process ideas, reflect on experiences and form perspectives. Thinking, she explained, is like training a muscle, and if you stop using it, its effectiveness weakens.
Reflecting back on this conversation, it became clear that when AI handles writing and even idea generation, students lose the opportunity to struggle through their own thoughts, the same struggle that builds confidence, originality and leadership, which Castilleja stands on.
“We lose emotion. We lose authenticity,” Charaus said. “And the more we use AI to do even simple tasks, the more our brain muscle gets lazy.”
Charaus also emphasized how AI shapes relationships. A nationwide survey from Common Sense Media suggests some students, especially those who might feel socially anxious, are turning to AI chatbots for conversations. These systems are designed to agree, validating students’ ideas rather than challenging them. Real people don’t work this way. Discomfort, disagreement and compromise are essential parts of learning how to think critically and how to relate to others. Removing this friction changes what meaningful relationships feel like.
Bias is another issue. AI can sound confident while being wrong, especially when information is missing. Charaus described watching AI generate incorrect historical information simply because key sources were not digitized. Without background knowledge or context, it is easy to mistake confidence for truth. Because AI systems are trained on existing data, they often reflect dominant perspectives and historical gaps rather than challenging them.
“Who builds these systems matters,” Charaus said, “What data they choose matters.”
French teacher Béatrice Dumas approached AI from a different angle but arrived at a similar conclusion. After attending a conference on AI in education, she said the biggest realization was how late schools already are. AI didn’t slowly enter classrooms. “It just landed,” Dumas explained. Teachers are now trying to catch up to something students are already using.
For her, debating whether AI belongs in school misses the point. “That’s like asking what we think about the internet,” she said. “It’s here. The question is, how do we use it?”
In language classes, AI can be genuinely helpful. Dumas sees value in conversation tools that give students a “very safe” space to practice speaking without fear of embarrassment. Language learning is performative, she explained, and teachers don’t always see how uncomfortable those situations can be. AI can help students build confidence before stepping into real conversations.
But she is clear about its limits. Culture, she said, does not come from generated responses. It comes from lived experiences. AI can help with grammar and structure, but it cannot teach how people actually interact, understand nuance, or connect emotionally. Those elements of language are human, which AI cannot replace.
Dumas also cautioned students against treating AI as a shortcut. AI doesn’t know what teachers will test, and it doesn’t know what students actually need to learn. Writing, like thinking, is part of the learning process, not just the final product.
The conversation highlighted the important distinction between using AI and being defined by it, especially for women. History shows how easily women’s voices can be minimized, edited, or erased. Overreliance on AI risks erasing our individuality, without even realizing what we’re losing.
While AI is becoming an important part of our lives, it’s equally important that women use their voices as their most powerful tool and become builders of AI and not just the end users. AI systems should learn from us and not the other way around.
