The Despair of the Professor in the Age of A.I. by Jay Caspian Kang

“Was it always the case that half of our students would cheat if it were easy enough?”

This article's central claim is that generative AI has created not just a cheating problem, but an existential crisis for university teaching. Jay Caspian Kang argues that many professors feel they're losing faith in the educational process itself because AI allows students to bypass the intellectual work that education is meant to cultivate.

Here are the main arguments:

The crisis is about learning, not just plagiarism

The professors Kang interviews are less concerned with catching cheaters than with a deeper question: if students can outsource reading, writing, and thinking to AI, what exactly are they learning? The traditional model of higher education assumes that struggling through difficult material develops judgment and intellectual maturity. AI threatens to short-circuit that process.

Writing is valuable because it is thinking

The article repeatedly returns to the idea that essays are not simply a way to demonstrate knowledge—they are how students clarify, test, and develop their own ideas. If an AI produces the prose, students may receive a polished product without having gone through the cognitive work that gives writing its educational value.

Professors are grieving the loss of authentic engagement

Many instructors describe an emotional response that goes beyond frustration. They feel that conversations with students have become less genuine because they cannot be sure whether submitted work reflects the student's own thinking. Several describe a sense of mourning for the kind of mentorship and intellectual discovery that originally drew them into academia.

Current solutions don't scale well

Professors have experimented with: oral examinations, handwritten assignments, in-class writing, highly personalized projects, redesigned assessments.

But these approaches are often feasible only in small seminars, not in large lecture courses with hundreds of students. The article argues that AI has exposed structural constraints in higher education, especially large class sizes and heavy teaching loads.

AI exposes existing weaknesses in higher education：Kang suggests AI didn't create every problem. Universities had already become increasingly: credential-focused, transactional, driven by efficiency, dependent on standardized assessments.

AI amplifies these trends by making it easier for students who primarily want the credential to complete assignments with minimal intellectual engagement.

Not all professors reject AI outright：The article is more nuanced than a blanket anti-AI argument. Some faculty members: use AI productively in their own work, believe students will need AI professionally, are experimenting with incorporating it into teaching.

Even these professors, however, worry about students becoming dependent on AI before they've developed their own analytical abilities.

The deeper question is the purpose of university education：The article ends by asking whether higher education can still justify traditional assignments—and perhaps even its broader mission—if machines can produce competent essays instantly. Rather than predicting the end of universities, Kang portrays professors as searching for a new conception of education in which human intellectual development remains central.

The article's underlying thesis

The essay is ultimately less about AI technology than about what education is for. It assumes that the point of college is not merely to produce correct answers or polished writing, but to cultivate habits of thought through effort, uncertainty, and revision. AI challenges that assumption by making the product of thinking available without necessarily requiring the process of thinking. That tension, the article argues, explains why so many professors describe the current moment not simply as a technological disruption but as a crisis of purpose.

（26.5.2026 The New Yourker， The Despair of the Professor in the Age of A.I.By Jay Caspian Kang Chinese Translation）

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Comment by 用心涼Coooool 9 hours ago: [iCONADA Research Team]MIT President's Open Letter: Higher Education Has Reached a Watershed Moment! If AI Can Already Serve as a Teaching Assistant, What Value Does a University Still Offer?

As professors begin considering whether AI agents could replace undergraduate research assistants, MIT President Sally Kornbluth has issued a rare open letter to the entire university community, candidly acknowledging that generative AI has brought higher education to a watershed moment—and posing a difficult question that every university will have to confront.

Less than four years after the emergence of generative AI, virtually every industry is facing unprecedented change. The education system is no exception. Indeed, it is confronting an especially profound challenge: if AI can already answer most university-level examination questions with remarkable accuracy and produce well-structured reports, why should students still spend four years—and pay substantial tuition—to attend university?

In an open letter to the MIT community released this year, MIT President Sally Kornbluth examined both the opportunities and risks that generative AI is bringing to education, describing the moment as a watershed not only for MIT but for higher education around the world.

The letter, together with a report released by MIT’s newly established Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training, reveals the anxieties confronting leading universities in the age of AI while also pointing toward possible directions for educational transformation.
AI Brings Superpowers—and Anxiety About Being Replaced

Kornbluth stated candidly in her letter that AI is like a kind of superpower. In experimental research, it is dramatically expanding the boundaries of discovery and accelerating the pace of innovation. At the same time, however, it introduces unsettling risks.

This anxiety is not merely hypothetical. One of the most widely discussed issues on campus is the report’s revelation that some faculty members have already considered using AI agents to replace undergraduate students as research assistants. This has caused students to worry that their own place in the academic research environment may be displaced.

Meanwhile, everyday academic practices—from traditional assignments to study groups—are also being fundamentally disrupted by AI. When knowledge and answers are readily available at one's fingertips, many students are beginning to wonder how they can demonstrate that they have genuinely learned something.

Redefining the University: The Ultimate Product of Education Is the Human Being

As the process of acquiring knowledge becomes increasingly effortless, the report raises a thought-provoking question:

“If we care only about efficiency, what are the people gathered together on campus actually here to do?”

Kornbluth’s answer echoes the founding spirit of MIT: the mission of a university is to help students develop the ability to discover problems and solve them. Instilling this spirit in every student is ultimately what gives a university its reason for existing.

Therefore, regardless of the field in which students conduct research, they must have opportunities to try things for themselves, make mistakes, and revise their approaches. Only through this process can they truly develop the mindset required to tackle difficult problems.

If the pursuit of efficiency deprives students of the opportunity to learn through doing—and of the freedom to make mistakes along the way—it could become one of the greatest disasters facing education.

Responding to the Impact of AI: Three Directions Proposed by the MIT Report

In seeking to redefine the role of higher education, the report proposes three concrete directions for action:
1. Build “AI-aware” educational processes

Every course should re-examine its learning objectives and assessment methods. Rather than simply attempting to block or prohibit AI, universities should adopt a backward-design approach: first clarify what students actually need to learn, and then establish clear guidelines for how AI may be used in each course.

2. Put “people and community” at the center

As access to knowledge becomes ubiquitous, the distinctive value of a physical campus will increasingly lie in human relationships and connections. Universities therefore need to invest more resources in residential life and community experiences in order to counter the sense of isolation that can easily emerge in the age of AI.

3. Establish mechanisms for continuous reflection and iteration

Given the rapid evolution of AI, MIT argues that universities must develop teams and processes capable of continuously reviewing and revising educational experiments. Responses to AI should evolve alongside the technology rather than being reduced to a fixed set of rules that is expected to remain effective indefinitely.

The University as a Training Ground for the Human Mind

MIT President Kornbluth’s open letter can be seen as a valuable lesson in reflection for educators and business leaders around the world.

As AI becomes increasingly capable of handling the retrieval, processing, and production of knowledge, both higher education and workplace talent development will need to move beyond the traditional model of simply transmitting information.

The university—and perhaps the workplace as well—will increasingly need to become a training ground for the human mind: a place devoted to cultivating critical thinking, empathy, judgment, creativity, collaboration, and other qualities that cannot be reduced to the efficient production of answers.

In the age of AI, these distinctly human capacities may well be among the most important “superpowers” in which we can invest.

（Source：MIT Organization Chart、Report)