AI-Generated Images for Representing Individuals: Navigating the Thin Line between Care and Bias

Julia C. Ahrend; Björn Döge; Tom M. Duscher; Dario Rodighiero

doi:10.48550/arXiv.2509.03071

2025 · Conference Paper
IEEE VIS Arts Program (VISAP)

AI-Generated Images for Representing Individuals: Navigating the Thin Line between Care and Bias

Julia C. Ahrend, Björn Döge, Tom M. Duscher, Dario Rodighiero

https://doi.org/10.48550/arXiv.2509.03071

@inproceedings{ahrend2025ai,
  author      = {Julia C. Ahrend and Björn Döge and Tom M. Duscher and Dario Rodighiero},
  title       = {AI-Generated Images for Representing Individuals: Navigating the Thin Line between Care and Bias},
  booktitle   = {IEEE VIS Arts Program (VISAP)},
  year        = {2025},
  doi         = {10.48550/arXiv.2509.03071}
}

This research discusses the figurative tensions that arise when using portraits to represent individuals behind a dataset. In the broader effort to communicate European data related to depression, the Kiel Science Communication Network (KielSCN) team attempted to engage a wider audience by combining interactive data graphics with AI-generated images of people. This article examines the project’s decisions and results, reflecting on the reaction from the audience when information design incorporates figurative representations of individuals within the data.