미국 명문대 학생들이 수업 중 교수의 질문을 AI 챗봇에 입력해 답변을 그대로 발언하는 등 과도하게 AI에 의존하는 현상이 나타나고 있습니다. 연구 결과와 교육자들은 AI가 학생들의 창의적 사고와 표현을 획일화시켜 토론의 다양성을 떨어뜨린다고 지적하며, 이에 따라 일부 대학들은 노트북 사용을 제한하는 등 원천적인 사고력 회복에 나섰습니다.
번역된 본문
일부 학생들은 교수의 질문을 AI 챗봇에 입력한 뒤, 그 출력 결과를 수업 중 발언의 핵심 논거로 사용하고 있다.
(에디터 노트: 필자는 코네티컷주 뉴헤이븐에 위치한 예일 대학교 3학년으로, 이 기사를 위해 동급생들에게 수업 시간 중 AI 사용 경험에 대해 물어보았다.)
예일 대학교 4학년인 아만다(Amanda)는 자신의 동료 상당수가 논문 및 기타 과제를 작성하기 위해 AI 챗봇을 사용한다는 사실을 이미 알고 있다. 하지만 그녀는 소규모 세미나 수업에서 기이한 현상을 발견하기 시작했다. 동료들이 노트북 앞에 앉아 세련된 논점과 주장을 펼치지만, 그 뒤를 이어지는 토론은 주제에 상관없이 심심하게 흐지부지 끝나버리곤 했다.
아만다는 CNN과의 인터뷰에서 "한 수업에서 대화가 멈췄고, 왼쪽을 보니 한 친구가 미친 듯이 노트북 자판을 두드리며 교수가 방금 읽기 과제에 대해 방금 했던 질문을 (챗봇에게) 입력하고 있었다"고 말했다.
아만다와 다른 두 학생인 제시카(Jessica), 소피아(Sophia)는 예일 대학교에 재학 중이다. 그들은 동료나 교수로부터 보복받을까 두려워 익명을 요청했으며, CNN은 이 기사를 위해 이들의 이름을 변경하는 데 동의했다.
아만다는 큰 충격을 받았다고 말했다. 그날까지 그녀는 학우들이 수업 중에 챗봇을 사용하고 그 결과를 그대로 수업에서 공유한다는 사실을 깨닫지 못했다. 이제 그녀는 그런 경향이 수업 토론에 미치는 영향을 감지하고 있다.
그녀는 "이제는 모두가 비슷하게 들린다"며 "대학 1학년 때 세미나에 앉아있으면 모두가 각자 다른 것을 발굴해 내곤 했다. 사람들이 서로의 의견에 기대어 발전시키긴 했어도 각기 다른 각도에서 접근해 다른 해설을 제공했다"고 말했다.
AI가 교육과 점점 더 깊게 융합됨에 따라, 교육자와 연구자들은 AI가 학생들의 독창적인 사고와 표현 능력을 갉아먹고 있을 수 있다는 사실을 발견하고 있다. 3월에 '인지과학 동향(Trends in Cognitive Sciences)' 저널에 발표된 논문은 대형 언어 모델(LLM)이 언어, 관점, 추론이라는 세 가지 차원에서 인간의 표현과 사고를 체계적으로 획일화(homogenizing)하고 있다고 밝혔다. 학생과 교육자들은 교실에서 이러한 추세의 영향을 직접 목격하고 있다고 전했다. 그 결과, 많은 학생들의 발언이 똑같아지고 있다.
왜 학생들은 수업에서 AI를 사용할까? 예일 대학 4학년인 제시카는 CNN과의 인터뷰에서 수업을 위해 매일 AI를 사용한다고 말했다. 교수가 무작위로 학생을 지목해 질문하는(cold-calls) 경제학 세미나의 경우, "수업 시작할 때 모든 사람이 모든 PDF를 (챗봇에) 집어넣는 것을 볼 수 있다"고 설명했다. 그녀는 또한 자신의 생각을 말로 표현하는 데 어려움을 겪을 때 AI를 사용한다. 제시카는 "내가 발언을 하고 싶고 어떤 개념은 있는데, 스스로 문장을 만들어내는 방법을 모를 때" 챗봇에게 "문장을 좀 더 응집력 있게 만들어 달라"고 요청한다고 말했다.
예일 대학교 대변인은 "학생들은 계속해서 수업에서 AI를 사용하는 실험을 하고 있으며, 본 기사에 설명된 내용을 포함해 수업에서 AI가 사용되는 방식을 인지하고 있다"고 답변했다. 그는 "학습과 참여를 지원하기 위해 교수진들이 노트북 사용을 제한하거나 금지하며 인쇄물 기반 자료, 독창적 사고, 동료 및 교수와의 직접적인 소통을 강조하는 방향으로 수업을 설계하는 광범위한 추세를 보고 있다"고 덧붙였다.
바드 칼리지(Bard College) 해나 아렌트 센터의 인문학 방문 교수이자 수석 연구원인 토머스 채터턴 윌리엄스(Thomas Chatterton Williams)는 학생들이 AI를 사용하기로 한 결정이 미치는 영향을 직접 목격했다. 교육 연구를 수행하는 씽크탱크인 미국기업연구소(AEI)의 비상주 연구원이기도 한 윌리엄스는 학생들의 AI 의존이 "역설적으로 어려운 개념이 포함된 강좌의 토론 수준을 전반적으로 끌어올렸지만, 동시에 더 기발하고 독특하며 독창적인 사고를 배제하는 경향이 있다"고 말했다.
제시카는 수업을 돕기 위해 챗봇을 사용하기 시작한 이후 자신이 더 게을러졌다는 것을 인정했다. 그녀는 "(내 사고력에 미칠 영향에 대해) 생각해 본 적이 있다..."라고 말을 이었다.
Some students are typing in professors' questions into AI chatbots and using the outputs as their talking points in class. AI Student life See all topics Facebook Tweet Email Link Threads Link Copied! Follow EDITOR’S NOTE: 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. At this point in her senior year at Yale University, Amanda knows that many of her classmates turn to AI chatbots to write papers and other homework assignments. 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. In one class, “the 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,” Amanda told CNN. Amanda, and two other students — Jessica and Sophia — 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. Gen Z is outsourcing hard conversations to AI. Why it matters 8 min read Amanda said she was taken aback. Until that day, she didn’t 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. “Everyone now kind of sounds the same,” she said. “I 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.” As AI becomes increasingly integrated with education, educators and researchers are finding that it may be eroding students’ capacity for original thought and expression. A paper published in March in Trends in Cognitive Sciences found that large language models are systematically homogenizing human expression and thought across three dimensions — language, perspective and reasoning — and students and educators say they are seeing the effects of that trend in their classrooms. And that makes a lot of students sound the same. Why students use AI in class 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, “at the beginning of class, you could see every single person putting every single PDF” into a chatbot. She also uses AI when she has trouble turning her thoughts into words. “I want to comment, and I have this concept, but I don’t know how to formulate the sentence myself,” she said. So she asked a chatbot “to make it sound more cohesive.” A Yale University spokesperson replied that “Students continue to experiment with using AI in class” and they are aware of the ways AI is used in the classroom, including those described in this article. “To 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,” the spokesperson told CNN. 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’ decisions to use AI. Students’ reliance on AI “ 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,” said Williams, who is also a nonresident fellow at the American Enterprise Institute, a think tank that includes research on education. Jessica admitted that she’s felt herself become lazier since she started using a chatbot to help with her classes. “I have thought about how much I stopped working, like my work ethic has completely diminished from high school,” she said. Why does AI make people sound the same? 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. The data those models train with overrepresents dominant languages and ideas, so their answers to users’ questions naturally “mirror a narrow and skewed slice of human experience,” the researchers wrote in their study. The result is “a narrowing of the conceptual space in which models write, speak, and reason.” AI-induced homogenization happens across three dimensions: language, perspective and reasoning strategies, the authors explained. That’s because AI models tend to reproduce what researchers call “WEIRD” viewpoints — Western, educated, industrialized, rich and democratic — even when explicitly prompted to represent other identities. One possible consequence, Sourati said, is that WEIRD language and perspectives could become perceived as more credible and “more socially correct,” 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. When a group repeatedly interacts with AI systems, Sourati explained, it flattens the group’s creativity compared to the same group without AI assistance. This flattening raises concerns in educational institutions at all levels. 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. 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, “they wouldn’t learn how to even think by themselves and have their own perspectives.” 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 “quite scary.” “If people lose diversity” in the way they think, “or get into intellectual laziness, of course, that is going to affect our society greatly,” said Dehghani, who is a coauthor of the paper. 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’t know. “I think creativity is dwindling because we lose the ability to make connections,” she added. 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. As more people use AI models to write and think, those outputs are reabsorbed into human discourse — and eventually into the data used to train the next generation of models —so the homogenization keeps compounding, the paper’s authors said. “If we’re offloading our reasoning onto these models, then we can easily be persuaded by what the models tell us,” he said. In education, Dehghani is concerned about a generation of students who are learning with AI and being tutored by AI. “They would be more homogenous in the way they think, in the way they write, so this is going to have long-term influences,” he said. In this photo illustration, ChatGPT app is seen displayed on a smartphone. ChatGPT to start showing users ads based on their conversations 3 m