The AI Zombification of Universities
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僵尸化
21 岁的芝加哥大学哲学系学生 Owen Yingling 认为，人工智能在校园里的广泛使用不仅是学术作弊的工具，而是一种"癌症"，威胁着大学作为人文学术机构的根基。他指出，老一代人未能意识到人工智能已渗透到学生生活的方方面面——从课程作业到社交互动——正在把知识精英"僵尸化"。
Yingling 描述了在 University of Chicago 上人工智能使用的演变：起初从"business economics"专业开始，他把该专业形容为学术上的"海滩度假"，机械记忆式的学习方式让学生更容易用 AI 替代真正的努力。问题很快蔓延到经济学系，有学生在考试时用手机拍试卷并把内容输入大型语言模型。最终，这股潮流也冲进了人文学科，据报道，随着更先进 AI 模型的出现，兄弟会的抄袭案件减少了，而成绩却上升了。
他强调了一个关键时刻：校刊 The Maroon 发表了两篇完全由 AI 生成的文章，数月都没有被察觉。此事表明，AI 的使用已超出单纯的学术不端，延伸到了学生出版物和媒体领域。 Yingling 观察到，讲座、带回家的测验和学生之间的闲聊里都充斥着千篇一律的平行句式，表明校园生活中的思想和表达正在趋于同质化。
尽管人工智能日益普及，精英大学仍不断宣布对 AI 研究和整合的大规模投入。 Yingling 指出，University of Chicago 收到了 5000 万美元的捐赠，Harvard 、 Yale 和 Columbia 也有类似举措，他将这些举动比作 1980 年代的 Pravda 文章，认为它们与真实情况脱节。他认为，这些机构一面鼓吹"AI 整合"，一面却出现了作弊案件的大幅上升，例如 Princeton 的纪律处分在一年内几乎翻了一番。
Yingling 把对 AI 的依赖比作"僵尸蚂蚁真菌"，认为学生正逐步把生活的各个方面交给 AI——从作业和电子邮件到健身计划和情感短信。他援引了一个关于"低语耳环"的寓言：耳环最终控制了佩戴者的每一个动作，用来说明 AI 如何能从有用的工具演化为全面掌控人类行为的机制。
他质疑 AI 能否真正融入教育，认为现实障碍太多、收益太少，尤其在人文学科课程中更是如此。他批评把 AI 说成能"民主化"教育的观点，称这对那些自诩不惜一切代价的精英机构本身就是矛盾。 Yingling 强调，教学本质上是一种人际关系，用 AI 取代它将导致那些真正能够激发思辨的古怪而富有挑战性的教师逐渐消失。
Yingling 警告说，AI 的整合会导致教育的同质化和中心化，使顶尖学校愈发趋同，并把它们绑在资本密集、监管严格的技术上。他设想一个未来：独立的教育机构被改造成按社会需要训练学生的大工厂，这一前景令他恐惧。尽管有人可能把当下大学体系的崩溃视为重建的机会，Yingling 对西方知识传统可能的流失深感痛惜——包括博士师承谱系与精心保存的图书馆。
他在结尾呼吁大学对 AI 使用采取更强硬的立场，并非认为这能解决高等教育的所有问题，而是为了防止真正的学习突然变得无关紧要。他承认二战后兴起的研究型大学正在衰落，但希望新出现的不会是一所没有目标、没有纪律、没有原创性的"undead university"。 Yingling 的这篇文章是对人文学术教育的热情捍卫，反对他眼中人工智能带来的去人性化影响。
The Great Zombification
Owen Yingling, a 21-year-old philosophy student at the University of Chicago, argues that the widespread use of artificial intelligence on college campuses is not merely a tool for academic cheating but a "cancer" that threatens to destroy the university as a humanist institution. He contends that the older generation fails to recognize the extent to which AI has permeated every aspect of student life, from coursework to social interactions, creating a "zombification" of the intellectual elite.
Yingling describes the progression of AI use at UChicago, starting in the "business economics" specialization, which he characterizes as an academic "beach vacation" where rote learning made it easy for students to substitute AI for genuine effort. He notes that the problem quickly spread to the economics department, where students were observed using phones to photograph exams and input them into large language models during tests. The issue eventually reached the humanities, where fraternity plagiarism cases reportedly decreased as grades rose following the release of more advanced AI models.
The author highlights a pivotal moment when the university newspaper, The Maroon, published two articles entirely generated by AI, which went unnoticed for months. This incident revealed that AI use had moved beyond simple academic misconduct into the realm of student publications and media. Yingling observes that "perfect parallel constructions" now fill lecture halls, take-home tests, and student chatter, suggesting a homogenization of thought and expression across campus life.
Despite the proliferation of AI, elite universities continue to announce massive investments in AI research and integration. Yingling points to a $50 million gift at UChicago and similar initiatives at Harvard, Yale, and Columbia, which he compares to "1980s Pravda articles" for their disconnect from the reality on the ground. He argues that these institutions are promoting "AI integration" while simultaneously experiencing dramatic increases in cheating cases, such as at Princeton where disciplinary actions nearly doubled in one year.
Yingling draws a parallel between AI dependency and the "zombie ant-fungus," suggesting that students are gradually surrendering all aspects of their lives to AI, from homework and emails to gym routines and romantic messages. He references a prophetic story about a "whispering earring" that eventually controls its wearer's every movement, illustrating how AI can evolve from a helpful tool to a mechanism of total control over human behavior.
The author challenges the notion that AI can be successfully integrated into education, arguing that the practical hurdles are too great and the benefits too low, particularly in humanities courses. He criticizes the idea that AI will "democratize" education, calling it a contradiction in terms for elite institutions that claim to spare no expense. Yingling emphasizes that teaching is fundamentally a human relationship, and replacing it with AI will lead to the extinction of the eccentric, challenging educators who truly stimulate intellectual growth.
Yingling warns that AI integration will lead to the homogenization and centralization of education, making top schools more interchangeable and tying them to capital-intensive, heavily regulated technology. He envisions a future where independent educational institutions are transformed into factories designed to train students according to societal needs, a prospect he finds terrifying. While some might see the collapse of the current university system as an opportunity to rebuild, Yingling expresses sadness at the potential loss of the Western intellectual tradition, including doctoral genealogies and carefully preserved libraries.
The author concludes by advocating for a harder line on AI use in universities, not because it will solve all the problems facing higher education, but because it will prevent the sudden irrelevance of genuine learning. He acknowledges that the post-WWII research university is already dying, but hopes that what emerges will not be an "undead university" devoid of purpose, discipline, or originality. Yingling's essay serves as a passionate defense of humanist education against what he sees as the dehumanizing effects of artificial intelligence.
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讨论的核心观点是：现代大学体系已发生根本性偏离，把学位认证和信号功能置于真正教育之上。许多与会者认为，AI 只是加速了这一既有趋势——学生把学位当作通往就业的交易性门槛，而非智力成长的机会。
• 大学的主要功能已经从教育转向认证：如今大多数非体力劳动岗位都要求学位，几十年前关于"以学习为本"的斗争就已失利。
• AI 被视为一种高风险工具，可能让人不劳而获地获取文凭，但根本问题是社会更看重可量化的成绩和排名，而非实际知识的获得。
• 尽管像 UChicago 这样的学校一向强调"学会如何思考"和人格培养，但更普遍的趋势是走向过度专业化，学生把大学当作白领职业培训学校。
• 精英学位的价值更多来自筛选效应和人脉网络，而非教学本身；在线课程和 AI 并未改变这一局面。
• 为应对 AI 作弊，许多人主张回归"无技术"做法：现场监考、蓝皮书考试和口试等——这些曾是几百年来的评估标准。
• 有人担心，如果 AI 削弱了学位的信号价值，高等教育带来的工资溢价可能瓦解，大学的地位或将变得无关紧要。
• 有人建议把教育与认证分离：大学专注于批判性思维培养，技术培训则交给学徒制和职业学校。
• 尽管前景令人担忧，一些学生和教育者发现 AI 作为苏格拉底式导师或用于制作个性化学习工具仍很有价值，前提是学生在学习中保持主动。
• 讨论暴露出两种分歧观点：一种认为 AI 是一种"僵尸化"力量，会制造永久性的下层阶层；另一种则认为，通过自动化死记硬背的工作，AI 能让学生把精力转向人文学科。
对话表明人们对当前高等教育深感怀疑，普遍认为该体系更看重门槛和地位，而非培养独立思想。尽管 AI 被视为破坏性力量，但许多人认为它只是揭示了以证书为核心的文化的既有缺陷。提出的对策从回归传统严格的评估方法，到彻底重塑社会如何看待和构建高等教育不等。 The discussion centers on the idea that the modern university system is fundamentally broken because it prioritizes credentialing and signaling over genuine education. Many participants argue that AI is merely accelerating an existing trend where students treat degrees as a transactional requirement for employment rather than an opportunity for intellectual growth.
• The primary function of university has shifted from education to certification, as degrees are now required for most non-manual-labor jobs, making the "battle for learning" one that was lost decades ago.
• AI is viewed as a high-risk tool for obtaining credentials without work, but the real issue is a culture that values measurement and grades over the actual acquisition of knowledge.
• While some institutions like UChicago historically emphasized "learning how to think" and personal enrichment, the broader trend is toward hyper-professionalism, where students view college as a white-collar vocational school.
• The value of an elite degree is often attributed to selection effects and networking rather than the quality of instruction, a dynamic that online courses and AI have failed to disrupt.
• To combat AI cheating, many suggest a return to "no-tech" solutions like in-person proctored exams, blue books, and oral assessments, which were the standard for centuries.
• There is a concern that if AI devalues the signaling power of a degree, the wage premium for higher education will collapse, potentially making universities irrelevant.
• Some argue that the solution is to decouple education from credentialing, suggesting that universities should focus on critical thinking while technical training moves to apprenticeships and trade schools.
• Despite the doom, some students and educators find AI useful as a Socratic tutor or for creating personalized learning tools, provided the student remains intentional about the learning process.
• The discussion highlights a divide between those who see AI as a "zombifying" force that creates a permanent underclass and those who believe it could free students to focus on humanist pursuits by automating rote knowledge work.
The conversation reveals a deep skepticism about the current state of higher education, with participants largely agreeing that the system is more concerned with gatekeeping and status than with fostering independent thought. While AI is seen as a disruptive force, many argue it is simply exposing the pre-existing flaws of a credential-focused culture. The proposed solutions range from a return to traditional, rigorous assessment methods to a complete overhaul of how society values and structures post-secondary education.