AiGet: Transforming Everyday Moments into Hidden Knowledge Discovery with AI Assistance on Smart Glasses

Runze Cai, Nuwan Janaka, Hyeongcheol Kim, Yang Chen, Shengdong Zhao*, Yun Huang, David Hsu*

*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

4 Downloads (CityUHK Scholars)

Abstract

Unlike the free exploration of childhood, the demands of daily life reduce our motivation to explore our surroundings, leading to missed opportunities for informal learning. Traditional tools for knowledge acquisition are reactive, relying on user initiative and limiting their ability to uncover hidden interests. Through formative studies, we introduce AiGet, a proactive AI assistant integrated with AR smart glasses, designed to seamlessly embed informal learning into low-demand daily activities (e.g., casual walking and shopping). AiGet analyzes real-time user gaze patterns, environmental context, and user profiles, leveraging large language models to deliver personalized, context-aware knowledge with low disruption to primary tasks. In-lab evaluations and real-world testing, including continued use over multiple days, demonstrate AiGet's effectiveness in uncovering overlooked yet surprising interests, enhancing primary task enjoyment, reviving curiosity, and deepening connections with the environment. We further propose design guidelines for AI-assisted informal learning, focused on transforming everyday moments into enriching learning experiences. © 2025 Copyright held by the owner/author(s).
Original languageEnglish
Title of host publicationCHI '25: Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems
EditorsNaomi Yamashita, Vanessa Evers, Koji Yatani
PublisherAssociation for Computing Machinery
ISBN (Print)9798400713941
DOIs
Publication statusPublished - Apr 2025
Event2025 ACM CHI Conference on Human Factors in Computing Systems (CHI 2025): IkiCHI - PACIFICO Yokohama, Yokohama, Japan
Duration: 26 Apr 20251 May 2025
https://chi2025.acm.org/

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2025 ACM CHI Conference on Human Factors in Computing Systems (CHI 2025)
Abbreviated titleCHI'25
Country/TerritoryJapan
CityYokohama
Period26/04/251/05/25
Internet address

Funding

This research is supported by the National Research Foundation Singapore and DSO National Laboratories under the AI Singapore Programme (Award Number: AISG2-RP-2020-016). The CityU Startup Grant (9610677) also provides partial support. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the author(s) and do not reflect the views of the National Research Foundation, Singapore. We extend our gratitude to the Lee Kong Chian Natural History Museum and NUS Museum for their invaluable assistance with our user studies and to all members of the Synteraction Lab for their help in completing this project. We also thank the reviewers for their valuable feedback.

Research Keywords

  • AI
  • HMD
  • human-ai interaction
  • incidental learning
  • informal learning
  • knowledge discovery
  • large language model
  • multimodal information
  • smart glasses
  • wearable-AI assistance

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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