Rogue Artificial Intelligence in der Anästhesie: Ursachen, mögliche Auswirkungen und Lösungsansätze = Rogue artificial intelligence in anaesthesia : causes, potential impacts and solution strategies
Methods For a narrative review, a PubMed and a Google Scholar search were conducted with the strings “Artificial intelligence / Machine learning AND/OR Rogue AI“ as well as a Google search for exemplary cases of rogue AI. Scientific articles, journalistic reports as well as grey litera ture were inc...
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| Autores principales: | , , , |
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| Formato: | Article (Journal) |
| Lenguaje: | alemán |
| Publicado: |
März/April 2026
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| In: |
Anästhesiologie & Intensivmedizin
Year: 2026, Número: 2, Pages: 59-73 |
| ISSN: | 1439-0256 |
| DOI: | 10.19224/ai2026.059 |
| Acceso en línea: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.19224/ai2026.059 Verlag, lizenzpflichtig, Volltext: https://www.ai-online.info/archiv/2026/02-2026/rogue-artificial-intelligence-in-der-anaesthesie-ursachen-moegliche-auswirkungen-und-loesungsansaetze.html 
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| Notas de Autor: | A. Luckscheiter, W. Zink, U. Hoppe, V. Schneider-Lindner |
| Sumario: | Methods For a narrative review, a PubMed and a Google Scholar search were conducted with the strings “Artificial intelligence / Machine learning AND/OR Rogue AI“ as well as a Google search for exemplary cases of rogue AI. Scientific articles, journalistic reports as well as grey litera ture were included. - Results A total of 12 exemplary scientific artic les, one case and three security reports, one professional association communi cation and 9 journalistic reports were identified. These included manipulative or extortionate behaviour of AI models, misdiagnoses caused by hallucinations or insufficiently trained or validated mo dels, examples of racist bias due to in adequate datasets, refusals to execute input commands, and unsolvable en cryptions. In the field of cybersecurity, studies reported on hidden backdoors, hacking, and manipulation of source code or training data. The control of eco nomic processes by AI could also lead to potential financial losses. No rogue AI was found to be directly implemented in the medical field. In anaesthesiology, for example, this could lead to problems affecting doctorpatient interactions, the malfunction or takeover of medical de vices by AI, over or undertreatment due to bias issues, misdiagnoses, and a disrupted doctorAI or patientAI inter action. - Conclusion The fundamental aspects of the rogue AI problem already exist today. In the fu ture, the problem could worsen with self learning and selfoptimising AI systems that are interconnected at all levels within hospitals. Approaches needed to solve these problems consist in comply |
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| Notas: | Gesehen am 07.06.2026 |
| Descripción Física: | Online Resource |
| ISSN: | 1439-0256 |
| DOI: | 10.19224/ai2026.059 |