Reimagining Personal Data: Unlocking the Potential of AI-Generated Images in Personal Data Meaning-Making

2025-02-26

AI Summary

This study addresses the challenge of enhancing meaning-making and subjective experience in personal data reflection through AI-generated imagery. We developed a web-based probe integrating GPT-4 and DALL-E 3, supporting a 21-day diary study with 16 participants—the first systematic incorporation of generative AI into personal data visualization practice. Results reveal two novel mechanisms for data sensemaking: “imaginative interpretation” and “speculative narration.” Participants demonstrated significantly heightened data awareness and affective engagement via AI-generated images, leading to deeper self-understanding. Concurrently, the study uncovered critical design tensions concerning privacy boundaries, model trustworthiness, and user agency. These findings advance theoretical understanding and provide empirical grounding for explainable AI, personal data literacy, and human-AI collaborative reflection systems.

Technology Category

• Humans and AI: Game Design — Procedural Content Generation & Storytelling
• Philosophy and Ethics of AI: Accountability, Interpretability & Explainability
• Cognitive Modeling & Cognitive Systems: Computational Creativity

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• User Modeling, Personalization and Recommendation: Explainable and interpretable methods for personalization
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

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.

Problem

• Transforming personal data into visual forms
• Exploring AI-generated images for data engagement
• Investigating personal meaning from AI images

Innovation

• AI-generated images transform data
• Web app uses GPT-4 and DALL-E
• Diary study explores user experiences