Reimagining Personal Data: Unlocking the Potential of AI-Generated Images in Personal Data Meaning-Making
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arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866910845730029568 |
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| author | Park, Soobin Kim, Hankyung Lim, Youn-kyung |
| author_facet | Park, Soobin Kim, Hankyung Lim, Youn-kyung |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_18853 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Reimagining Personal Data: Unlocking the Potential of AI-Generated Images in Personal Data Meaning-Making Park, Soobin Kim, Hankyung Lim, Youn-kyung Human-Computer Interaction Artificial Intelligence H.5.0 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. |
| title | Reimagining Personal Data: Unlocking the Potential of AI-Generated Images in Personal Data Meaning-Making |
| topic | Human-Computer Interaction Artificial Intelligence H.5.0 |
| url | https://arxiv.org/abs/2502.18853 |