Healthy skepticism in AI: a data visualization research agenda
Research in data visualization of artificial intelligence (AI) models has historically focused on enhancing trust through visual explanations of AI. The trustworthiness line of work was built at least partially on an assumption that humans were critical users unlikely to adopt AI technology. It is increasingly clear that human trust levels in AI span, in fact, a wide range from critical to over-reliant. There is an urgent need to support both trust and healthy skepticism in AI solutions. We argue that it is healthy for humans to adopt a skeptical view both on the results of AI models and on the use of such AI models. We share our thoughts on the rising phenomenon of over-reliance on AI mo...
| Authors | G. Elisabeta Marai, Marc Baaden, Michael Behrisch et al. |
|---|---|
| Primary category | cs.HC |
| Published | 7 October 2026 |
| Last updated at source | 7 October 2026 |
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