As artificial intelligence transforms classrooms, workplaces, and daily life, one Oxford academic says schools are at risk of teaching the wrong lessons.
Professor Rebecca Eynon, from the Oxford Internet Institute and the University of Oxford’s Department of Education, says educators must go beyond preparing students to cope with technology — and instead help them shape it.
“AI is not just something to react to, but something that people should actively shape in relation to the kinds of education, and indeed society, we want,” Eynon wrote on Monday. “This requires a proactive, not reactive, response to AI in schools.”
Her research at Oxford’s Towards Equity-Focused EdTech project found that many young people aren’t as digitally savvy as adults assume.
Students often struggled with basic skills, such as managing files or sending emails, and teachers were uncertain about where or how digital literacy should be integrated into the curriculum, she said.
Eynon said that AI education shouldn’t just focus on technical skills but should also cultivate critical thinking, inclusion, and responsibility.
1. Teach criticality — not just coding
Eynon said digital literacy must go beyond identifying misinformation or learning to use AI tools safely.
Students should understand the social, political, and economic systems that shape the technology they use.
“It is important that young people are not positioned as ‘end users’ of fixed AI technologies,” she wrote. “Instead, they should be supported in becoming citizens who can use and engage with technology critically in the richest sense — including awareness of economic, political, and cultural issues.”
That means teaching students how bias enters algorithms, how tech companies profit from data, and how misinformation spreads — giving them the tools to question and challenge AI systems rather than simply accept them.
2. Design for inclusion
AI literacy, Eynon said, should include a hands-on design element that helps students connect technology with social realities.
“Design is a key aspect of digital literacy, offering students ways to reflect on and make visible social injustices while examining how technology’s affordances and values can support or hinder inclusion,” she wrote.
She suggests projects that allow students to explore bias in AI or build digital tools that serve their communities.
Embedding these principles across subjects — not just computer science — can help more students see themselves as part of the digital future.
3. Share responsibility
While students should learn to question and critique generative AI, Eynon cautioned against offloading the responsibility for fixing flawed systems onto them.
“There is a societal responsibility that does not just fall on young people to find ways to better govern, regulate, and change AI,” she wrote.
She said that governments, educators, and tech companies must share accountability for the environmental, ethical, and legal challenges that come with AI, rather than expecting individuals to navigate them alone.
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