Research on Cognitive Personal Informatics (CPI) is steadily growing as new wearable cognitive tracking technologies emerge on the consumer market, claiming to measure stress, focus, and other cognitive factors. At the same time, with generative AI offering new ways to analyse, visualize, and interpret cognitive data, we hypothesize that cognitive tracking will soon become as simple as measuring your heart rate during a run. Yet, cognitive data remains inherently more complex, context-dependent, and less well understood than physical activity data. This workshop brings together HCI experts to discuss critical questions, including: How can complex cognitive data be translated into meaningful metrics? How can AI support users' data sensemaking without over-simplifying cognitive insights? How can we design inclusive CPI technologies that consider inter-personal variance and neurodiversity? We will map

翻译：随着新型可穿戴认知追踪技术在消费市场的涌现，声称能够测量压力、专注度及其他认知因素，认知个人信息学的研究正稳步增长。与此同时，随着生成式AI为分析、可视化和解读认知数据提供了新方法，我们假设认知追踪将很快变得像测量跑步时的心率一样简单。然而，与身体活动数据相比，认知数据本质上仍然更为复杂、更依赖于情境且更难以理解。本次研讨会汇聚了人机交互领域的专家，旨在探讨以下关键问题：如何将复杂的认知数据转化为有意义的指标？AI如何能在不过度简化认知洞察的前提下支持用户的数据理解？我们如何设计包容性的认知个人信息学技术，以考虑人际差异和神经多样性？我们将绘制