Stay informed with our newsletter.
.webp){kind=spacer}
EN
Economist Tyler Cowen explores how artificial intelligence exposes deep structural failures in the education system, from outdated teaching models to ineffective credentialing. He challenges the traditional notion of educational expertise and urges a rethinking of pedagogy in an age where AI can outperform human instruction in many areas. Cowen advocates for embracing AI as a collaborative tool, reforming teacher training, and shifting education’s focus from rigid processes to critical thinking, adaptability, and meaningful student engagement.
Renowned economist and public intellectual Tyler Cowen has long been a sharp observer of the intersections between technology, economics, and institutional design. As artificial intelligence continues to reshape industries, Cowen has turned a critical eye toward education, arguing that the sector is suffering from deep structural failures, failures that AI is both exposing and intensifying.
At the core of Cowen’s critique is a central question: Why has the education system, despite enormous investment and countless reforms, struggled to improve outcomes and adapt to technological change?
Cowen asserts that education, particularly in the U.S. and other advanced economies, suffers from a kind of institutional stagnation. While fields like finance, medicine, and logistics have leveraged technology to become more productive, the classroom remains stubbornly static. Students still sit in rows, teachers still follow rigid curriculums, and schools continue to rely on outdated methods of instruction and assessment.
He argues that bureaucracy and credentialism have hardened education into a system that rewards process over results. Teachers must obtain certifications that often have little to do with effective instruction, and schools are evaluated on standardized metrics that encourage conformity rather than creativity. This rigidity makes it nearly impossible for innovation, technological or otherwise, to take hold.
In Cowen’s words, education suffers from “expertise ossification”, where those who are seen as the experts are entrenched in systems that resist disruptive improvement.
One of Cowen’s most provocative arguments is that our concept of educational expertise is deeply flawed. He critiques the idea that professional educators, often trained in schools of education, possess a monopoly on knowing how to teach effectively. While respecting the complexity of teaching, Cowen suggests that much of what passes for pedagogical theory is untested or based on shaky empirical foundations.
With the rise of AI tools, like language models capable of tutoring, writing, and problem-solving, Cowen believes it’s time to ask uncomfortable questions: Are these AI tools already better than average teachers in some domains? If so, what does that say about the true value of “expertise” in education?
He suggests that AI could democratize access to high-quality instruction, providing tailored support at scale in a way traditional education has failed to do. Yet institutions continue to ignore or resist these tools, preferring the comfort of human-led, familiar systems, even when those systems underperform.
Cowen does not romanticize AI. He acknowledges the risks, ethical concerns, overdependence, data privacy, and the potential for misuse. However, he sees in AI a mirror that reflects education’s failings more clearly than ever.
When a free chatbot can explain calculus more patiently than a human tutor, or a generative AI can help a student write an essay better than they learned in school, we are forced to confront what the education system is failing to deliver: individual attention, engagement, feedback, and relevance.
Cowen argues that AI’s competence in these areas exposes education’s lack of scalability and its failure to deliver consistent quality. Good teaching exists, but it is unevenly distributed. AI, by contrast, can offer uniformity in areas where human instruction is weakest. If nothing else, AI forces us to reevaluate what education is really trying to achieve and whether it’s succeeding.
One of Cowen’s central contributions as an economist is his focus on incentives, what motivates behavior and decision-making in institutions. He argues that educational systems are poorly aligned with outcomes. Teachers often lack the incentives to innovate or improve; school administrators may be more focused on compliance than creativity; and students are conditioned to perform for grades rather than learning for mastery.
Cowen warns that AI will upend these incentive structures. For example, if students can use AI to write papers or do assignments, grading systems lose their meaning. If AI tutoring becomes freely available, the need for traditional classroom lectures diminishes. Unless schools rethink their core objectives, away from credentialism and toward curiosity, problem-solving, and adaptability, they risk irrelevance.
Despite his sharp critiques, Cowen is not advocating for a machine takeover of education. Instead, he believes AI should free humans to focus on what they do best, mentorship, critical discussion, emotional support, and fostering lifelong learning.
In Cowen’s view, the teacher of the future isn’t a lecturer or grader, but a curator of experiences, a guide through complex questions, and a facilitator of deep thinking. AI can assist with the routine and repetitive; humans should double down on the uniquely human.
This, however, demands a radical reconfiguration of teacher training and school structure. Teachers must be trained not just in curriculum, but in philosophy, design, communication, and technology integration. Cowen argues that the longer institutions delay this shift, the more they risk being leapfrogged by informal learning environments that are more adaptive and engaging.
Cowen frequently speaks about the idea of “intelligence as a commodity.” With AI tools capable of simulating reasoning, writing, and problem-solving, intelligence itself becomes abundant. The scarcest resources now are wisdom, judgment, and context, skills that are cultivated, not taught.
This reframes education’s purpose. If knowledge is cheap and accessible, schools must focus on cultivating discernment, helping students ask better questions rather than memorizing answers. AI tools will be with students for life, so teaching them how to interact with, evaluate, and critically use AI is more important than resisting it.
Cowen’s broader worry is that schools are stuck in a knowledge-scarcity mindset while the world has already shifted to knowledge abundance. The danger is not ignorance, but shallow understanding, students who can produce answers but lack the tools to evaluate or apply them meaningfully.
What does Cowen propose in response to these structural failures?
Tyler Cowen’s critique of education in the age of AI is not a rejection of the profession or the people who commit their lives to teaching. It is a wake-up call. The tools are changing, the landscape is shifting, and the assumptions of the last century no longer hold.
Education must move beyond its outdated models and embrace a future where AI is not a threat, but a collaborator. The real failure would be to ignore this moment, to cling to expertise that no longer serves its purpose, and to institutions that have forgotten how to evolve.
In Cowen’s view, the future of learning belongs not to those who resist change, but to those who redefine expertise for the age of intelligence.
For questions or comments write to contactus@bostonbrandmedia.com
.jpg)
