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The Unexpected Harms of Artificial Intelligence in Healthcare: Reflections on Four Real-World Cases

Authors: Denecke, Kerstin; Lopez-Campos, Guillermo; Rivera-Romero, Octavio; Gabarron, Elia;

The Unexpected Harms of Artificial Intelligence in Healthcare: Reflections on Four Real-World Cases

Abstract

Introduction: Rapid advances in Artificial Intelligence (AI), especially with large language models, present both opportunities and challenges in healthcare. This article analyzes real-world AI-related harms in healthcare. Methods: We selected four recent AI-related incidents from the AIAAIC Repository. Results: The incidents discussed include: Whisper’s harmful hallucinations; UNOS’s algorithm delaying transplants for black patients; the WHO’s S.A.R.A.H. chatbot providing inaccurate health information; and Character AI’s chatbot promoting disordered eating among teens. Discussion and conclusion: These incidents highlight diverse risks, from misinformation to safety concerns, involving both industry and institutional providers. The article emphasizes the need for systematic reporting of AI-related harms, concerns about security, privacy, and ethics, and calls for a centralized health-specific database to enhance patient safety and understanding.

Keywords

Artificial intelligence, Patient safety, Digital health interventions, Artificial Intelligence, Medical Informatics Computing, Adverse events, Digital technology, Humans

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green
hybrid
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