学术报告

How Experience Moderates the Impact of AI Suggestions on Researchers’ Perceptions of Their Ideas
发布时间:2025-11-04 浏览次数:10

Title: How Experience Moderates the Impact of AI Suggestions on Researchers’ Perceptions of Their Ideas

题目:经验如何调节人工智能建议对研究人员创意感知的影


Speaker: Sen ChaiMcGill University, Desautels Faculty of Management

Time:  2025124日 下午3:00

Host: 周斯凡

Place: 管理学院一楼第二教室


Abstract: At the heart of scientific discovery are researchers who identify ideas worthy of inquiry. In performing research tasks, researchers are increasingly using generative artificial intelligence (AI) technologies—large language models, in particular. However, little is known about how generative AI assists researchers with one of the most fundamental tasks in science—the generation of initial research ideas, and their willingness to adopt the technology for such purpose. We show that one’s research experience is key in understanding how researchers receive generative AI suggestions when formulating new research ideas: experience negatively moderates the effect of generative AI on perceived novelty and impact of the researcher’s idea, and on views of one’s own research agendas. By focusing on the critical moment of idea generation, we extend prior findings showing how generative AI affects various task performance. We provide an initial understanding of how researchers respond to generative AI at a moment when the paradigm of human knowledge production may be shifting from a human only to a joint human-AI model. Our findings have implications for researchers, organizations, and policy, as individuals and industry producing knowledge need to balance building their own expertise and incorporating generative AI into the research process to advance knowledge.


Bio:Sen Chai是麦吉尔大学德索泰管理学院(Desautels Faculty of Management)战略与组织学终身副教授,并担任德索泰学院学者(Desautels Faculty Scholar),获哈佛商学院技术与运营管理博士(PhD)。她的研究成果发表在Organization Science3篇)、Strategic Management JournalResearch Policy3篇)等管理与创新领域顶级学术期刊上,并被《NatureNewsMIT Sloan Management Review等媒体报道。她的研究聚焦创造性创新从构想到商业化的完整过程,旨在帮助管理者和政策制定者更有效地支持创新,同时识别、规避并管理失败,从而提升组织产生突破性创意的概率。她目前的项目包括研究预先预判在失败管理中的作用,涵盖重大创新挫败和众筹活动两类情境;同时,她也在探索人工智能工具如何影响科研中的创意生成。在加入麦吉尔大学之前,她曾在巴黎ESSEC高等商学院任终身副教授,并在美国国家经济研究局(NBER,剑桥市马萨诸塞州)完成博士后研究。在攻读博士学位之前,她曾在德勤咨询(Deloitte Consulting LLP)旧金山和西雅图办公室担任咨询顾问,协助客户优化业务流程。她还通过了CFA项目的全部三级考试。


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