The record expansion of artificial intelligence (AI) has triggered global debates about its revolutionary potential to reshape firms, labor markets, and social conventions. The most consequential—and underestimated—challenge, though, could be how it can rethink the practice and purpose of education. Drawing inspiration from philosopher Hannah Arendt’s seminal 1954 essay, The Crisis in Education, this moment of technological upheaval invites us to confront foundational questions about what education should achieve in an era where human and machine intelligence increasingly intersect. Arendt’s assertion that crises compel societies to revisit ossified assumptions offers a timely framework for re-examining educational priorities amid AI’s disruptive rise.
Arendt’s Crisis: Authority, Responsibility, and Renewal
Arendt’s objection to education in the mid-20th century was that it undermined tradition and authority, which were, in her opinion, the necessity to provide intergenerational continuity. Teachers, to her mind, had a twofold obligation: to provide for the world as it is and educate successive generations to make it over again. She cautioned against child-centered approaches that prioritized individualism over shared responsibility, noting that the practice endangered to isolate children from the common cultural and intellectual heritage necessary to make societies meaningful.
At the heart of Arendt’s case was the proposition that education must move beyond utilitarian purposes. Instead of educating students only for skills, it should foster an understanding of humankind’s shared heritage and enable learners to critically reflect on—and eventually reimagine—that heritage. Such a vision positioned schools as a nexus between past and future, where authority did not stem from control but from teachers’ dedication to retaining and reinterpreting knowledge.
AI as Break: From Tool to Agent
AI is a paradigmatic break from previous technological innovations. In contrast to previous tools, like writing or calculators, that amplified human abilities but did not work independently, AI systems work as autonomous agents that can make decisions independently and improve themselves. Historian Yuval Noah Harari makes this distinction, suggesting that the agency of AI alters the mutual dependence between humans and technology, undermining conventional hierarchies of knowledge and work.
In education, this pause most starkly appears in arguments about the role of AI in classrooms.
Applications such as ChatGPT have raised issues of academic integrity, with teachers racing to identify AI-generated assignments and prohibit “cheating.” But this defensive approach, aimed at maintaining assessment structures, hides a more profound, frequently untested assumption: that the main purpose of education is to sort students into meritocratic rankings. This limited vision, Arendt would say, overlooks the larger challenge of working towards virtuous interaction with the world. Beyond Meritocracy: Questioning the Instrumental Lens. Contemporary education frameworks, including those that place the greatest premium on critical thinking, continue to be ensnared by instrumental ends.
The Organization for Economic Co-operation and Development (OECD), for example, is adding “global competence” to its Programme for International Student Assessment (PISA), with an emphasis on skills such as intercultural comprehension and problem-solving.
Likewise, the International Baccalaureate (IB) encourages whole-person, humanist schooling towards building “global citizens.” But each model has undertones of selectivity, situating learners as human capital to optimize economic performance. This instrumentalism will benefit neither an AI-facilitated future. In a world in which automation remakes labor markets and makes many of the occupations of the past obsolete, education should educate students not just for work but for civic and moral life in societies where human agency exists alongside—and at times in tension with—machine intelligence. Canadian computer scientist Mark Daley argues that attempts to prevent AI-aided cheating are wide of the mark: “Rather than looking for technological silver bullets, teachers must confront the tougher questions: Why are students cheating?
How do we create a culture of learning and not of grade-grubbing?
Realignment of Purpose: Teaching as Ethical Stewardship. In order to solve these issues, educators need to reengineer education as a space in which students can live the complexity of the world, be skilled at disentangling uncertainty, and be equipped with compassion to solve crises of society. This will involve going beyond transactional forms of learning (e.g., memorization, testing) to transformational methods emphasizing inquiry, collaboration, and moral thought.”
At the heart of this shift is destroying the structural incentives that turn education into a competition. If testing is less about brute recall and more about original thinking and critique, then the notion of “cheating” makes no sense. Project-based learning, for instance, where students work on actual problems, resists the AI shortcut naturally by emphasizing process over product. In the same vein, integrated, interdisciplinary curricula with ethics, technology, and environmental studies can bring students to position AI within wider social contexts.
Schools as Sanctuaries: Protecting Thought During an Era of Crisis
Arendt had envisioned education as a haven where youth perceive the richness and paradoxes of the world. Scholar Mario Di Paolantonio builds on this idea, with schools as “unique human dwellings” where teachers and students together conserve and reinterpret intellectual and cultural heritage. In these places, attention is diverted from individual accomplishment to cooperative inquiry, creating a culture of stewardship for common knowledge.
This vision requires curricular and pedagogical innovations. For example, the incorporation of AI literacy, not technical expertise but ethical consideration of its uses, can enable students to critique algorithmic bias or fight for fair tech policies. Similarly, encouraging “slow learning” spaces, where deliberation and discussion are valued over efficiency, can resist the commodification of education.
The Stakes: Democracy, Equity, and Human Flourishing
The cost of inaction amid change goes well beyond the schoolhouse. As AI reproduces power among technocratic elites and bureaucratizes state decision-making, education must take center stage to equip future citizens with the capacity to resist AI-driven surveillance, manipulation, and worker exploitation. That must be achieved by producing critical citizens who can challenge AI-enabled surveillance, manipulation, and exploitation of workers.
Other than that, shared access to AI-enabled learning is most critical. Without a clear policy, AI will widen inequality, favoring richer students who possess sophisticated equipment and leaving the poor behind. Closing that gap entails shifting “access” not just into access to hardware but also into access to a means of making technology creative and ethical.
Conclusion: Toward an Arendtian Future
Hannah Arendt’s urging to bring education back to renewal and responsibility rings fresh in the AI era.
By reframing this technology disruption as a challenge instead of a threat, teachers can reassert their role as guardians of the common knowledge. That requires moving beyond Band-Aid solutions—be they AI sensors or revised tests—to address some fundamental questions: What does it mean to teach in an era where machines simulate human thought? How do we get students ready to care for a world struggling with climate meltdown, inequality, and democratic vulnerability? The solutions are not in holding on to spent models but in envisioning schools as laboratories for moral experimentation. By doing so, education can reach its highest potential: to instill a passion for the renewal and preservation of the world such that every passing generation receives not only knowledge but also the wisdom to implement it.
Source: The Conversation