The CHI26 Workshop on the Future of Cognitive Personal Informatics

2026-01-21

AI Summary

This study addresses the challenge of translating highly context-dependent cognitive data—marked by significant individual differences—into interpretable and actionable personal metrics without oversimplifying the underlying cognitive processes. To this end, it proposes the first cognitive personal informatics (CPI) interpretation framework explicitly designed to accommodate individual variability, integrating wearable cognitive sensing, generative AI, and human-computer interaction design through a neurodiversity-informed lens. Emphasizing inclusive design and user empowerment, the research synthesizes insights from interdisciplinary expert discussions to identify key challenges and future directions for CPI in usability, explainability, and inclusivity, thereby advancing cognitive tracking technologies toward everyday, personalized applications.

Technology Category

• Cognitive Modeling & Cognitive Systems: Affective Computing
• Humans and AI: Intelligent User Interfaces
• Intelligent Robots: Cognitive Robotics

Application Category

• User Modeling, Personalization and Recommendation: Explainable and interpretable methods for personalization
• Economics, Online Markets and Human Computation: Fairness, privacy, and diversity in economic environments
• Security and Privacy: Data transparency and provenance

Abstract

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

Problem

• Cognitive Personal Informatics
• cognitive data
• generative AI
• neurodiversity
• data sensemaking

Innovation

• Cognitive Personal Informatics
• Generative AI
• Wearable Cognitive Tracking
• Neurodiversity
• Data Sensemaking