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| Home > Workflow collections > In process > From digital bench to bedside: exaggerated risks, realistic expectations, and genuine challenges of medical AI |
| Journal Article | FZJ-2026-04325 |
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2026
Springer
Heidelberg
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Please use a persistent id in citations: doi:10.1007/s00330-026-12812-0
Abstract: Artificial intelligence (AI) has become an increasingly prominent force in medicine, driven by rapid technical advances and a growing number of clinical applications. As the field matures, it now increasingly moves from experimental development toward a phase of broader implementation. However, debates surrounding medical AI are often shaped by exaggerated risks and overly optimistic expectations. This paper seeks to contribute to a more balanced and realistic discussion. Rather than framing AI as either an existential threat or a universal solution, we advocate for an open-minded, evidence-based understanding of AI as a tool to support healthcare and discuss current and emerging challenges related to clinical validation, human–AI interaction, bias and discrimination, education, agentic AI, and the development and maintenance of trust.
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