Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Ein externer Link zum Volltext ist derzeit nicht verfügbar.
From Code to Care: A Pilot Exploration of Scenario-Based Trust in Medical AI Among Digitally Native Youth
0
Zitationen
1
Autoren
2026
Jahr
Abstract
Background: Artificial intelligence is increasingly embedded in clinical workflows, yet public trust remains cautious and context-dependent. Most research on medical AI trust focuses on adult populations in high-income Western countries, leaving digitally native youth in emerging regions understudied. Objective: This exploratory pilot study investigates how young people from Central Asia and other regions perceive medical AI across concrete care scenarios. Methods: An online scenario-based survey (n=41) was administered to primarily 13–24-year-old respondents (53.7% Central Asia; 65.9% daily AI users). Results: Participants favored AI for rapid, low-risk access but strongly preferred human clinicians when AI conflicted with physician judgment. Attitudes toward AI for emotional support were polarized. Conclusions: These preliminary findings suggest context-dependent trust patterns among digitally native youth, with AI potentially serving as a "second-opinion catalyst" rather than a replacement for clinicians.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.418 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.288 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.726 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.516 Zit.