Can we disrupt the momentum of the AI colonization of science education?

Avraamidou (2024) critical COMMENT in the Journal of Research in Science Teaching: the uncritical uptake of Generative AI in science education amounts to an "AI colonization" — extraction of data without consent, algorithmic monoculture, dehumanized learning, and profit-centered reform. She calls for a critical, feminist, values-based disruption toward a human-centered AI that prioritizes justice over profit.

Lucy Avraamidou (2024) writes an explicitly critical COMMENT arguing that science education is being colonized by the generative AI industry. She contends that educational institutions are "buying into generative AI promises and hallucinations" as a silver bullet, and that this uncritical momentum reproduces colonial patterns of exploitation and extraction. The piece is a techno-utopia critique grounded in equity, accountability, and feminist values, aimed at the science education research community.

The AI colonization of science education

Avraamidou opens by cataloguing how AI tools are now used to extract data (usually without consent), replace research participants, read and summarize papers, write papers, design lesson plans, manage students, and assess students. She frames this as a techno-utopia and a "new world order" driven by the Anglo-American AI industry — an unsolicited reform that "lacks vision, is a-theoretical, is de-contextualized, [and] has profit instead of the learner at its center."

Central to the critique is the threat of algorithmic monoculture (Kleinberg & Raghavan, 2021): as all users converge on the same algorithmically-curated choices and preferences, scientific research and education risk losing the diversity and plurality of voices that make them robust. This parallels concerns about Bias Mitigation and the homogenization of thinking.

Dehumanization and standardization

Drawing on her own systematic review of AI in school science (Heeg & Avraamidou, 2023), Avraamidou finds that AI applications in science education are used mostly to automate existing practices and that the literature is atheoretical and lacks criticality. AI-driven tools, from virtual tutors and chatbots to automated assessment and learning analytics, are charged with:

Neglecting the social, relational, and embodied dimensions of learning;
Promoting a "convenience-food" approach of fast, bite-sized learning over slow learning;
Confusing education with training and students with input–output machines;
Standardizing thinking rather than celebrating "the infinite ways of becoming a science learner."

This is the mechanism by which generative AI can dehumanize learning — a direct challenge to the cognitive-only framing common across much of AI Education research and practice.

The imperative of a feminist AI

Avraamidou's constructive alternative is a feminist and human-centered AI that prioritizes justice over profit. Higher education institutions should develop visions for critical AI literacy framed within feminist pedagogies, rather than acting as consumers of what the AI industry offers. She poses six critical questions:

What is the nature of knowledge produced through generative and predictive AI?
Whose knowledge is it?
Who benefits from AI?
Based on what data are algorithms made available?
Can we afford the environmental impact of AI?
Who is held accountable when AI systems fail?

These questions tie directly to accountability, Ethics, and equity. The essay warns that AI systems perpetuate biases, racism, and existing systems of oppression, and carry a heavy environmental footprint (an AI prompt's carbon footprint is 4–5× a search-engine query). Science education, she argues, does not need an AI utopia driven by "corporate, neoliberal, and eugenics paradigms" (Gebru & Torres, 2024), but rather pedagogies of care, affect, and cultural sustainability — spaces "where humanization of science learning and social transformation that transcend the algorithm can happen."

The essay closes with an affirmative: "Can we disrupt the momentum of the AI colonization of science education? Yes, we can—once we step outside of corporate and capitalist visions of science education and imagine more sustainable and socially just futures."

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Citation

Avraamidou, L. (2024). Can we disrupt the momentum of the AI colonization of science education? Journal of Research in Science Teaching, 61(10), 2570–2574. https://doi.org/10.1002/tea.21961