Reimagining Personal Data: Unlocking the Potential of AI-Generated Images in Personal Data Meaning-Making
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Abstract (arXiv)
Image-generative AI provides new opportunities to transform personal data into alternative visual forms. In this paper, we illustrate the potential of AI-generated images in facilitating meaningful engagement with personal data. In a formative autobiographical design study, we explored the design and use of AI-generated images derived from personal data. Informed by this study, we designed a web-based application as a probe that represents personal data through generative images utilizing Open AI's GPT-4 model and DALL-E 3. We then conducted a 21-day diary study and interviews using the probe with 16 participants to investigate users' in-depth experiences with images generated by AI in everyday lives. Our findings reveal new qualities of experiences in users' engagement with data, highlighting how participants constructed personal meaning from their data through imagination and speculation on AI-generated images. We conclude by discussing the potential and concerns of leveraging image-generative AI for personal data meaning-making.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 15 of its 134 references that are in the map. First posted on arXiv 26 Feb 2025.
Builds on
15 of 134 references.
References · 15
- 2023A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPTcited by 612
- 2021Design Guidelines for Prompt Engineering Text-to-Image Generative Modelscited by 216
- 2024Design Principles for Generative AI Applicationscited by 57
- 2023MindfulDiary: Harnessing Large Language Model to Support Psychiatric Patients' Journalingcited by 50
- 20223DALL-E: Integrating Text-to-Image AI in 3D Design Workflowscited by 41
- 2021Machine Learning Uncertainty as a Design Material: A Post-Phenomenological Inquirycited by 14
- 2024Sketch2Prototype: Rapid Conceptual Design Exploration and Prototyping with Generative AIcited by 13
- 2024AI Should Challenge, Not Obeycited by 11
- 2024Machine Learning Processes as Sources of Ambiguity: Insights from AI Artcited by 7
- 2020Mirror Ritual: An Affective Interface for Emotional Self-Reflectioncited by 5
- 2024Metamorpheus: Interactive, Affective, and Creative Dream Narration Through Metaphorical Visual Storytellingcited by 4
- 2020Activity River: Visualizing Planned and Logged Personal Activities for Reflectioncited by 2
3 more
- 2023Message Ritual: A Posthuman Account of Living with Lampcited by 2
- 2024Studying Self-Care with Generative AI Tools: Lessons for Designcited by 2
- 2017A Field Study of On-Calendar Visualizationscited by 1
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Citing papers per year: 2025: 1; 2026: 1.
2 papers.