Chen Youjie, Wang Yingying, Wüstenberg Torsten, Kizilcec Rene F, Fan Yiwen, Li Yanfei, Lu Bin, Yuan Meng, Zhang Junlai, Zhang Ziyue, Geldsetzer Pascal, Chen Simiao, Bärnighausen Till
Department of Information Science, Cornell University, Ithaca, USA.
Heidelberg Institute of Global Health (HIGH), Faculty of Medicine and University Hospital, Heidelberg University, Heidelberg, Germany.
Trials. 2025 Jul 11;26(1):244. doi: 10.1186/s13063-025-08950-3.
BACKGROUND: The advancement of generative artificial intelligence (AI) has shown great potential to enhance productivity in many cognitive tasks. However, concerns are raised that the use of generative AI may erode human cognition due to over-reliance. Conversely, others argue that generative AI holds the promise to augment human cognition by automating menial tasks and offering insights that extend one's cognitive abilities. To better understand the role of generative AI in human cognition, we study how college students use a generative AI tool to support their analytical writing in an educational context. We will examine the effect of using generative AI on cognitive effort, a major aspect of human cognition that reflects the extent of mental resources an individual allocates during the cognitive process. We will also examine the effect on writing performance achieved through the human-generative AI collaboration. METHODS: This study is a randomized controlled lab experiment that compares the effects of using generative AI (intervention group) versus not using it (control group) on cognitive effort and writing performance in an analytical writing task designed as a hypothetical writing class assignment for college students. During the experiment, eye-tracking technology will monitor eye movements and pupil dilation. Functional near-infrared spectroscopy (fNIRS) will collect brain hemodynamic responses. A survey will measure individuals' perceptions of the writing task and their attitudes on generative AI. We will recruit 160 participants (aged 18-35 years) from a German university where the research will be conducted. DISCUSSION: This trial aims to establish the causal effects of generative AI on cognitive effort and task performance through a randomized controlled experiment. The findings aim to offer insights for policymakers in regulating generative AI and inform the responsible design and use of generative AI tools. CLINICALTRIALS: gov NCT06511102. Registered on July 15, 2024. https://clinicaltrials.gov/study/NCT06511102.
背景：生成式人工智能（AI）的发展在许多认知任务中展现出提高生产力的巨大潜力。然而，有人担心使用生成式人工智能可能因过度依赖而损害人类认知。相反，也有人认为生成式人工智能有望通过自动化琐碎任务并提供扩展认知能力的见解来增强人类认知。为了更好地理解生成式人工智能在人类认知中的作用，我们研究大学生如何在教育背景下使用生成式人工智能工具来支持他们的分析性写作。我们将研究使用生成式人工智能对认知努力的影响，认知努力是人类认知的一个主要方面，反映了个体在认知过程中分配的心理资源的程度。我们还将研究通过人机协作使用生成式人工智能对写作表现的影响。 方法：本研究是一项随机对照实验室实验，比较使用生成式人工智能（干预组）与不使用生成式人工智能（对照组）对作为大学生假设写作课程作业设计的分析性写作任务中的认知努力和写作表现的影响。在实验过程中，眼动追踪技术将监测眼球运动和瞳孔扩张。功能近红外光谱（fNIRS）将收集大脑血液动力学反应。一项调查将测量个体对写作任务的看法以及他们对生成式人工智能的态度。我们将从德国一所进行该研究的大学招募160名参与者（年龄在18 - 35岁之间）。 讨论：本试验旨在通过随机对照实验确定生成式人工智能对认知努力和任务表现的因果效应。研究结果旨在为政策制定者在监管生成式人工智能方面提供见解，并为生成式人工智能工具的负责任设计和使用提供参考。 临床试验：gov NCT06511102。于202年7月15日注册。https://clinicaltrials.gov/study/NCT06511102 。
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