Dust Off Kindle Highlights With Quologue: Surfacing Personal Data With Generative AI for Reflective Experiences

要旨

People’s annotations on books can serve as valuable traces for people to revisit their past thoughts, emotions, and other experiences. For e-books, however, the lack of physicality and their e-reading infrastructure make it difficult for people to revisit them as these traces continue to accumulate in digital archives. In this paper, we describe the design and deployment of Quologue, an LLM-powered web application that allows users to reconnect with their e-book highlights through ongoing dialogue and stepwise interactions. We conducted a field study with 10 participants over 8 weeks. Our aim was to investigate the reflective and self-expressive potentialities of personal e-book metadata; and to learn about any opportunities and tensions that emerge from surfacing one’s data with a generative AI model. Findings revealed that Quologue generated diverse reflective experiences and influenced participants’ current digital highlighting practices. We conclude with implications and opportunities for future HCI studies and practice.

著者
Sol Kang
Simon Fraser University, Surrey, British Columbia, Canada
William Odom
Simon Fraser University, Surrey, British Columbia, Canada
Amy Yo Sue Chen
A Life Enspired Studio, Palo Alto, California, United States
Carman Neustaedter
Simon Fraser University, Surrey, British Columbia, Canada

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: Affective Agents & Reflective Data

Area 1 + 2 + 3: theatre
7 件の発表
2026-04-14 20:15:00
2026-04-14 21:45:00