“It Looks Sexy but it's Wrong.” Tensions in Creativity and Accuracy using genAI for Biomedical Visualization

We contribute an in-depth analysis of the workflows and tensions arising from generative AI (genAI) use in biomedical visualization (BioMedVis). Although genAI affords facile production of aesthetic visuals for biological and medical content, the architecture of these tools fundamentally limits the accuracy and trustworthiness of the depicted information, from imaginary (or fanciful) molecules to alien anatomy. Through 17 interviews with a diverse group of practitioners and researchers, we qualitatively analyze the concerns and values driving genAI (dis)use for the visual representation of spatially-oriented biomedical data. We find that BioMedVis experts, both in roles as developers and designers, use genAI tools at different stages of their daily workflows and hold attitudes ranging from enthusiastic adopters to skeptical avoiders of genAI. In contrasting the current use and perspectives on genAI observed in our study with predictions towards genAI in the visualization pipeline from prior work, we refocus the discussion of genAI's effects on projects in visualization in the here and now with its respective opportunities and pitfalls for future visualization research. At a time when public trust in science is in jeopardy, we are reminded to first do no harm, not just in biomedical visualization but in science communication more broadly. Our observations reaffirm the necessity of human intervention for empathetic design and assessment of accurate scientific visuals. Supplemental study materials are available at https://osf.io/genaixbiomedvis/.

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Publication Details

Journal
IEEE Transactions on Visualization and Computer Graphics
Published
2025-12-04
DOI
https://doi.org/10.1109/tvcg.2025.3633883
Primary Topic
Data Visualization and Analytics
Type
article
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article

“It Looks Sexy but it's Wrong.” Tensions in Creativity and Accuracy using genAI for Biomedical Visualization

Laura Garrison, Gaël McGill, Shehryar Saharan, Roxanne Ziman
IEEE Transactions on Visualization and Computer Graphics
Data Visualization and Analytics
article

“It Looks Sexy but it's Wrong.” Tensions in Creativity and Accuracy using genAI for Biomedical Visualization

Laura Garrison, Gaël McGill, Shehryar Saharan, Roxanne Ziman
article en

Abstract

We contribute an in-depth analysis of the workflows and tensions arising from generative AI (genAI) use in biomedical visualization (BioMedVis). Although genAI affords facile production of aesthetic visuals for biological and medical content, the architecture of these tools fundamentally limits the accuracy and trustworthiness of the depicted information, from imaginary (or fanciful) molecules to alien anatomy. Through 17 interviews with a diverse group of practitioners and researchers, we qualitatively analyze the concerns and values driving genAI (dis)use for the visual representation of spatially-oriented biomedical data. We find that BioMedVis experts, both in roles as developers and designers, use genAI tools at different stages of their daily workflows and hold attitudes ranging from enthusiastic adopters to skeptical avoiders of genAI. In contrasting the current use and perspectives on genAI observed in our study with predictions towards genAI in the visualization pipeline from prior work, we refocus the discussion of genAI's effects on projects in visualization in the here and now with its respective opportunities and pitfalls for future visualization research. At a time when public trust in science is in jeopardy, we are reminded to first do no harm, not just in biomedical visualization but in science communication more broadly. Our observations reaffirm the necessity of human intervention for empathetic design and assessment of accurate scientific visuals. Supplemental study materials are available at https://osf.io/genaixbiomedvis/.

IEEE Transactions on Visualization and Computer GraphicsVol. 32(1)
University of Toronto (CA), Digizyme (United States) (US), University of Bergen (NO)
Openalex Percentile: Top 60%
Data Visualization and Analytics
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“It Looks Sexy but it's Wrong.” Tensions in Creativity and Accuracy using genAI for Biomedical Visualization — Laura Garrison, Gaël McGill, et al. · IEEE Transactions on Visualization and Computer Graphics (2025) | TGRS Research Map | TGRS