\n EDITOR\u2019S NOTE:\u00a0 The writer is a junior at Yale University in New Haven, Connecticut, and spoke to her peers about their experience with AI usage in class for this article.\n<\/p>\n
\n At this point in her senior year at Yale University, Amanda knows that many of her classmates turn to AI chatbots<\/a> to write papers and other homework assignments.\n <\/p>\n \n But she started noticing something bizarre in her smaller seminar classes: Her classmates sit behind laptops with polished talking points and arguments, but the conversations that follow often fall flat across subjects.\n <\/p>\n \n In one class, \u201cthe conversation came to a halt, and I looked to my left, and I saw someone typing ferociously on their laptop, asking (a chatbot) the question my professor just asked about the reading,\u201d Amanda told CNN.\n <\/p>\n \n Amanda, and two other students \u2014 Jessica and Sophia \u2014 attend Yale University. They requested anonymity for fear of retribution from their classmates and professors, so CNN agreed to change their names for this article.\n <\/p>\n \n Amanda said she was taken aback. Until that day, she didn\u2019t realize that her peers were using chatbots in class and sharing what it spits out in the classroom. Now she notices the impact that tendency is having on class discussions.\n <\/p>\n \n \u201cEveryone now kind of sounds the same,\u201d she said. \u201cI feel like during my freshman year in college, I would sit in seminars where everyone had something different to contribute. Although people would piggyback off each other, they approached from different angles and offered different commentary.\u201d\n <\/p>\n \n As AI becomes increasingly integrated with education, educators and researchers are finding that it may be eroding students\u2019 capacity for original thought and expression.\n <\/p>\n \n A paper published in March in Trends in Cognitive Sciences<\/a> found that large language models are systematically homogenizing human expression and thought across three dimensions \u2014 language, perspective and reasoning \u2014 and students and educators say they are seeing the effects of that trend in their classrooms.\n <\/p>\n \n And that makes a lot of students sound the same.\n <\/p>\n \n Jessica, a senior at Yale, told CNN that she uses AI every day for her classes. In an economics seminar in which the professor cold-calls students, \u201cat the beginning of class, you could see every single person putting every single PDF\u201d into a chatbot.\n <\/p>\n \n She also uses AI when she has trouble turning her thoughts into words. \u201cI want to comment, and I have this concept, but I don\u2019t know how to formulate the sentence myself,\u201d she said. So she asked a chatbot \u201cto make it sound more cohesive.\u201d\n <\/p>\n \n A Yale University spokesperson replied that \u201cStudents continue to experiment with using AI in class\u201d and they are aware of the ways AI is used in the classroom, including those described in this article.\n <\/p>\n \n \u201cTo support learning and engagement, we are seeing a broader trend of faculty designing courses with limited or no laptop use, emphasizing print-based materials, original thinking, and direct engagement with peers and instructors,\u201d the spokesperson told CNN.\n <\/p>\n \n Thomas Chatterton Williams, a visiting professor of the humanities and senior fellow at the Hannah Arendt Center at Bard College, has seen the impact of students\u2019 decisions.\n <\/p>\n \n Students\u2019 reliance on AI \u201c has paradoxically raised the floor of class discussion to a generally better level in courses with difficult concepts, but has also tended to preclude stranger, more eccentric and original thoughts,\u201d said Williams, who is also a nonresident fellow at the American Enterprise Institute, a think tank that includes research on education.\n <\/p>\n \n \u201cMy biggest concern is that many bright young people will never achieve a voice of their own \u2014 indeed that a surprising number of them won\u2019t even fully appreciate the value of authorship and ownership of a point of view.\u201d\n <\/p>\n \n Thomas Chatterton Williams\n <\/p>\n \n Jessica admitted that she\u2019s felt herself become lazier since she started using a chatbot to help with her classes.\n <\/p>\n \n \u201cI have thought about how much I stopped working, like my work ethic has completely diminished from high school,\u201d she said.\n <\/p>\n \n Large language models, or LLMs, are trained to predict the next most statistically likely word given everything that came before it, said Zhivar Sourati, a doctoral student at the University of Southern California and first author of the paper.\n <\/p>\n \n The data those models train with overrepresents dominant languages and ideas, so their answers to users\u2019 questions naturally \u201cmirror a narrow and skewed slice of human experience,\u201d the researchers wrote in their study. The result is \u201ca narrowing of the conceptual space in which models write, speak, and reason.\u201d\n <\/p>\n \n AI-induced homogenization happens across three dimensions: language, perspective and reasoning strategies, the authors explained. That\u2019s because AI models tend to reproduce what researchers call \u201cWEIRD\u201d viewpoints \u2014 Western, educated, industrialized, rich and democratic \u2014 even when explicitly prompted to represent other identities.\n <\/p>\n \n One possible consequence, Sourati said, is that WEIRD language and perspectives could become perceived as more credible and \u201cmore socially correct,\u201d marginalizing other viewpoints. A similar phenomenon is observed in reasoning, in which the popular technique of walking models through step-by-step logical thinking may be crowding out more intuitive, culturally specific and creative ways of working through a problem.\n <\/p>\n \n When a group repeatedly interacts with AI systems, Sourati explained, it flattens the group\u2019s creativity compared to the same group without AI assistance.\n <\/p>\n \n This flattening raises concerns in educational institutions at all levels.\n <\/p>\n \n When students were asked open-ended, subjective questions with no single, correct answer, teachers could expect a wide range of responses. But if all students rely on AI, their answers may become more polished but fall into just a handful of similar categories, Sourati said. They will lose the diversity of thinking that classroom discussions are meant to encourage.\n <\/p>\n \n Sourati is most concerned that homogenization is happening to people who are developing their ability to creatively generate new ideas. If students continue to use AI instead of developing their own thought processes, \u201cthey wouldn\u2019t learn how to even think by themselves and have their own perspectives.\u201d\n <\/p>\n \n Morteza Dehghani, a professor of psychology and computer science at the University of Southern California, said that he has heard of people using AI to determine who to vote for in an election, which he finds \u201cquite scary.\u201d\n <\/p>\n \n \u201cIf people lose diversity\u201d in the way they think, \u201cor get into intellectual laziness, of course, that is going to affect our society greatly,\u201d said Dehghani, who is a coauthor of the paper.\n <\/p>\n \n Sophia, a junior at Yale, believes that her fellow anthropology students are using AI to draft scripts for what to say in class because people are insecure about what they don\u2019t know.\n <\/p>\n \n \u201cI think creativity is dwindling because we lose the ability to make connections,\u201d she added.\n <\/p>\n \n If people continue to offload their reasoning to AI, Dehghani agrees that communities will lose creative innovation and the ability to critique mainstream ideas or even political candidates.\n <\/p>\n \n As more people use AI models to write and think, those outputs are reabsorbed into human discourse \u2014 and eventually into the data used to train the next generation of models \u2014so the homogenization keeps compounding, the paper\u2019s authors said.\n <\/p>\n \n \u201cIf we\u2019re offloading our reasoning onto these models, then we can easily be persuaded by what the models tell us,\u201d he said.\n <\/p>\n \n In education, Dehghani is concerned about a generation of students who are learning with AI and being tutored by AI. \u201cThey would be more homogenous in the way they think, in the way they write, so this is going to have long-term influences,\u201d he said.\n <\/p>\n \n Sophia, who tries to resist using AI in school, said she believes people are deprioritizing their own thinking \u201cin favor of having really big words.\u201d\n <\/p>\n \n \u201cI would literally rather just tell the professor, \u2018I don\u2019t know what we\u2019re talking about.\u2019 Even if you put every reading into (a chatbot), it doesn\u2019t have your past experiences that make you a critical thinker,\u201d she said.\n <\/p>\n \n \u201cI feel like people had a lot more to say because they actually feel tied to the material,\u201d Amanda agreed. \u201cNow classroom discussions are not really digging deep. I think a lot of that has to do with the AI chatbots, but also, there\u2019s no longer as much of a drive to connect with the material personally.\u201d\n <\/p>\n \n Disappointed, she added, \u201cI think it\u2019s boring to be in a class where everyone has the same thing to say, and no one wants to dig deeper or push against what is directly said in the text or the norm.\u201d\n <\/p>\n \n Daniel Buck, a research fellow at the American Enterprise Institute and a former English teacher at four K-12 schools over seven years, said he is concerned that students are circumventing the cognitive work required to engage in classroom discussions and complete homework.\n <\/p>\n \n \u201cA lot of learning happens in the boring minutia, the struggle,\u201d Buck said. Students retain only what they have actually spent time consciously processing, he continued. If a student outsources thinking to AI, they may be able to reproduce a talking point in class, but they haven\u2019t built the underlying skills to apply that knowledge elsewhere.\n <\/p>\n \n Buck draws a sharp distinction between AI and the shortcut technology that preceded it: SparkNotes. When students relied on the popular website to find chapter-based summaries of literary works, teachers could easily detect it, he added.\n <\/p>\n \n AI is a \u201csupercharged version of SparkNotes\u201d that \u201ccan answer any question that you pitch to it,\u201d Buck said. Whereas SparkNotes offered a fixed set of analyses, AI can respond to whatever a teacher asks, making it much harder to identify when students are not doing the thinking themselves.\n <\/p>\n \n The difference is in how people reason. Instead of being used as just a reference, such as books or search engines, AI is an active participant in \u201cproblem solving and perspective-taking,\u201d Dehghani clarified.\n <\/p>\n \n \u201cWhat we are seeing now is fundamentally different than other periods of homogenization of expression and thought,\u201d Williams said. \u201cIf even professional writers are finding it exceedingly difficult to resist outsourcing the difficult work of wrestling with words and ideas \u2014 as we know they are \u2014 I don\u2019t see how the younger generations who have not experienced a world before highly sophisticated, on-demand AI writing will be able to do this, not at scale.\u201d\n <\/p>\n \n Buck worries that students will graduate without having developed relationships with professors, as well as the habit of sustained cognitive work. That means they will struggle to solve problems in the real world.\n <\/p>\n \n \u201cThere\u2019s so much delight in reading original student essays,\u201d he said. \u201cEven if it isn\u2019t quite as well -argued or as solid as I wish it would have been, you\u2019re seeing these young students, for the first time, start to think for themselves, to analyze, to think critically. It\u2019s almost like watching my own children walk for the first time, where they stumble and fall, and that\u2019s amazing. Keep doing that.\u201d\n <\/p>\n \n Reading and interacting with students\u2019 original thoughts in class helps teachers understand how students think and articulate.\n <\/p>\n \n \u201cThere\u2019s an interpersonal exchange that I think gets overlooked when you get to know your students, they get to know you, they start to trust you and your feedback,\u201d he said. \u201cI think that gets lost too when it\u2019s just everything is through AI.\u201d\n <\/p>\n \n Sun-Joo Shin, a philosophy professor at Yale, said, \u201cIt is a big homework for anyone who is involved in teaching\u201d to keep exploring ways to ensure students continue to think critically and creatively in the age of AI.\n <\/p>\n \n \u201cWe are in an interesting and exciting transition. I want my students to understand the material of the class, which is constant before and after the appearance of AI,\u201d she said. \u201cAt the same time, I want them to use this exciting tool to their advantage, not be a victim of it. A dilemma of an instructor is how to help, or force, students to learn the material and to think creatively without running away from the AI tools or without copying them.\u201d\n <\/p>\n \n Until the fall semester of 2024, she said she was not worried about how AI would affect students\u2019 understanding of the material in her mathematical logic class. Her teaching team had tested the problem sets against the AI models at the time, and they were unable to solve her problems.\n <\/p>\n \n But since then, \u201cAI has been catching up,\u201d and models can answer questions \u201cpretty well\u201d if students upload class handouts and learning materials. She started thinking about additional requirements in the class beyond problem set submissions.\n <\/p>\n \n \u201cAfter all, it would be extremely unfair to give good grades to AI answers,\u201d Shin said.\n <\/p>\n \n Yale has guidance on AI usage for both students and faculty. \u201cGenerative AI use is subject to individual course policies,\u201d one of the university websites<\/a> states. \u201cWe encourage all instructors to adapt our model policies for their specific course and learning goals. AI Detection tools are unreliable and not currently supported.\u201d\n <\/p>\n