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Critical Pedagogy

created 2026-08-16 · updated 2026-09-30

Critical Pedagogy — an educational approach, rooted in the work of Paulo Freire and later critical theorists such as Henry Giroux, that treats teaching and learning as inherently political acts. Rather than merely transmitting skills or knowledge, critical pedagogy asks who benefits from education, whose knowledge is privileged, and how schooling reproduces or resists systems of power and oppression. In AI-in-education, critical pedagogy interrogates the corporate and capitalist logics shaping AI adoption, centers the voices and epistemologies of marginalized communities, and treats AI literacy as a practice of resistance and social transformation rather than mere technical competence.

Questions to Consider

  • Who does your education — or the AI tools in it — actually serve? Critical pedagogy insists this question is unavoidable, not optional. What's your honest answer?
  • Critical thinking asks 'is this reasoning sound?' Critical pedagogy asks 'who does this education benefit, and whose knowledge counts?' How are those two questions different, and when does one need the other?
  • Some scholars describe generative AI's spread into education as a form of 'colonization' that extracts data, labor, and resources from marginalized communities. Does that framing feel extreme, or does it name something real?
  • Critical AI literacy can include 'resisting AI' — refusing the inevitability of tech as a solution. In what situations might strategic refusal or non-use be a more responsible choice than adoption?
  • Who gets to decide what counts as authoritative knowledge? If AI systems are positioned as authoritative, what happens to learners' own lived and community epistemologies?
  • Under critical pedagogy, a teacher is not a neutral transmitter of AI skills but a facilitator who helps Learners interrogate the politics of AI. How comfortable are you with that role, and what would it ask of you?

Introduction

Critical pedagogy is distinct from Critical Thinking. Critical thinking is a cognitive skill — evaluating arguments, questioning assumptions, and reasoning carefully — that can be practiced within almost any framework. Critical pedagogy, by contrast, is a political and ethical stance that connects those skills to questions of power, justice, equity, and social transformation. The knowledge base treats them as related but distinct concepts: critical thinking asks "is this reasoning sound?", while critical pedagogy asks "who does this education serve, and whose knowledge counts?".

Critical pedagogy and AI in education

AI in education raises sharp questions for critical pedagogy, and the knowledge base documents several strands:

  • Critique of the "AI colonization" of education. Critical and feminist scholars argue that generative AI is reshaping education in ways that repeat patterns of colonial exploitation and extraction — of data, labor, and natural resources — enriching the powerful at the expense of marginalized communities.(Can we disrupt the momentum of the AI colonization of science education?) This framing rejects the "techno-utopia" narrative that presents AI as a neutral silver bullet.

  • From compliance to human flourishing. A socialist-humanist review reframes AI literacy as transformation rather than compliance, naming "AIgemony" — AI reinforcing corporate power asymmetries — and the "ghost work" of invisible human labeling labor, and urging the "being" mode of active engagement over the "having" mode of possession (Rose (2026)).

  • Feminist and justice-centered AI. A feminist approach to AI prioritizes justice over profit, asks critical questions about the nature and ownership of knowledge, who benefits from AI, and who is accountable when systems fail. It calls for critical AI literacy framed within feminist pedagogies.(Can we disrupt the momentum of the AI colonization of science education?)

  • Resisting AI as a critical literacy practice. Critical AI Literacy (CAIL) can encompass "resisting AI" — a stance that refuses the inevitability and techsolutionism of dominant discourse, and instead cultivates collective Learner Agency through dialogic, collaborative pedagogies that imagine alternative futures.(Reorienting Critical AI Literacy: A Community-Rooted Praxis of “Resisting AI”)

  • Multimodal AI composition as critical AI literacy pedagogy. Burriss et al. (2026) document a classroom unit in which 22 eleventh-grade students composed video public service announcements about AI Ethics issues of their choosing, translating surveillance, data consent and algorithmic accusation into 90-second to 3-minute films built from sound, image, text and their own bodies. Framed by Critical Posthumanist Literacy, the work shows the political stance in practice: across all seven films harm emerged from tangled human–machine responsibility rather than from a villainous tool, and students still closed on Learner Agency — "the solution is in our reach" — even as one participant dissented that youth "completely lack any kind of credibility." The authors argue that creative, collaborative composition is itself a form of critical AI literacy, and that existing AI literacy scales and competency frameworks, which assume individually measurable performance, systematically exclude it.

  • Redistributing epistemic authority. Community-based AI learning grounds AI engagement in learners' lived and community epistemologies, challenging the positioning of AI systems as authoritative knowledge sources.(Community-Based AI Learning: Redistributing Artificial Intelligence's Epistemic Authority in Education) This involves epistemic fine-tuning, redistribution of authority, and situated discernment.

  • Critical engagement is the exception, not the norm. Across 42 classroom episodes in a Romanian lower-secondary study, 15 (35.71%) were AI-dependent and 16 (38.10%) AI-enhanced, leaving only 11 (26.19%) AI-critical — which motivates Voicu's (2026) six-checkpoint developmental-critical model for interpretive autonomy.

  • Digital mediation as critical practice under resource constraint. Sithole (2026) applies Critical Digital Pedagogy with decolonial epistemologies of the South to academic development in South African Historically Disadvantaged Institutions, where developers filter institutional AI rhetoric through the question of what it means "for our students from poor schools." Their mediation is intervention rather than facilitation — interrogating rather than adopting tools, asking what is gained and whose labor disappears, and treating context as an epistemic principle rather than a design preference. The author's analytical contribution is to separate digital inequality from algorithmic coloniality and to insist, following Adams, that calls to decolonize AI stay material rather than metaphorical.

  • Situated and cultural-historical ethics. Critical approaches also argue that AI ethics in education must be situated — grounded in cultural-historical and ecological context rather than abstract principles.(Situated AI ethics: a cultural-historical and ecological framework for education)

  • Sustainability as a value-based project. AI's effect on educational sustainability is conditional and governance-mediated, not intrinsic: a value-critical analysis holds that AI supports sustainable education only when adoption is subordinated to explicit educational values and undermines it when technologization and commodification erode them (Alsuhami & Atallah (2026)).

  • Efficiency-first alignment discourse as an erasure of context. McInnes et al. (2026) apply Fairclough's three-dimensional model to 14 pieces of gray literature (November 2022 – April 2025) advising higher-education practitioners to use generative AI for constructive alignment, and find a techno-solutionist discourse in which the tool is anthropomorphized as "an educational expert and assistant" and academic staff are positioned as supplying "subject matter expertise" while the system performs the pedagogical work. The analysis names the erasure of situated, disciplinary and critical context as one of three failure modes — alongside performativity (alignment that only looks aligned) and shallow alignment that conflates the constructive dimension with the aligned one — evidence that even advice about course design, ostensibly a neutral technical matter, carries the depoliticising logic critical pedagogues critique elsewhere.

  • Design remedies are not enough on their own. Human-centered design approaches such as value-sensitive design are insufficient: they leave the systemic drivers — workforce-productivity framings and economic incentives — untouched, and Learner Agency may be zero-sum, so capability handed to the tool is capability the learner does not retain (Prieto & Dimitriadis (2026)).

  • Human rights education as the test case for AI governance as formation. Kasa-Mälksoo (2026) works through the UN's about, through, for framework in a law program and locates the difficulty not in the technology but in the pedagogy: students submitted polished written work and polished session designs without the engagement those artifacts are supposed to evidence, and the most critical thinking appeared in end-of-course writing rather than in class dialogue. Her conclusion shifts the educator's role rather than shrinking it — AI governance becomes a professional responsibility students are trained to contest, and the tool is directed rather than banned.

The role of the educator

Under critical pedagogy, educators are not neutral transmitters of AI skills but critical interlocutors and facilitators who help learners interrogate the politics of AI. This connects to the knowledge base's Teaching and AI Literacy concepts, and to the broader concern with Equity and Reducing AI Misuse. The educator's task is to cultivate spaces where communities can collectively question, appropriate, or refuse AI — keeping education a site of imagination and social transformation. Burriss et al. (2026) add a practical condition to that role: open-ended critical AI literacy work does not require educators to arrive as AI experts, only to be willing to explore alongside students — a joint student–teacher investigation of one specific system, electronic "hall passes" (not all of which are AI), surfaced and worked through Misconceptions about AI while deepening technical knowledge. Miles, Haber-Curran and Arar (2026) give that role a constructionist, ethics-of-care shape: they treat prompt literacy as a rhetorical, ethical and reflective process rather than a technical optimization skill, and the framework's closing phase has students co-design a Personal AI Use Policy with their instructor, so the norms governing classroom AI use are authored by the people they govern rather than issued to them.

Connected Concepts

Connected Articles

Connected Resources

  • Pressing Prompts
    Openly accessible higher-education activities and resources for pressing critical questions about AI, organised into three thematic clusters.

Metadata

Learning and instructionCritical Pedagogy
Equity, ethics, and responsible useEquity, Ethics
Foundations of AI in educationLearner Agency, AI Literacy, Critical Thinking, Reducing AI Misuse
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