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PAP. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 202 pp. Englisch.

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This dissertation explores the complex role of explainability in AI-driven medical decision-making. While AI offers significant benefits in improving diagnostic accuracy and support, its opaque nature challenges user trust-particularly among medical professionals and patients. Explainability is seen as a key solution, but its impact is not straightforward.Through one conceptual and three empirical studies, the research shows that explanations can increase transparency, trust, and user understanding, encouraging greater adoption of AI systems. They also help users maintain confidence after AI errors and can reduce privacy concerns by clarifying data use. However, explanations can also have negative effects, such as increasing cognitive load, overwhelming users in high-stakes settings, and even heightening privacy concerns.To address these mixed outcomes, the dissertation proposes a procedural model for integrating explanations during the pre-use, use, and post-use phases. This model helps balance transparency, cognitive demands, and privacy considerations in practical applications like clinical decision support tools and symptom checkers.Overall, the work contributes to Human-AI interaction literature by offering theoretical, empirical, and practical guidance on designing explainable AI systems that are both trustworthy and user-centered.…

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This dissertation explores the complex role of explainability in AI-driven medical decision-making. While AI offers significant benefits in improving diagnostic accuracy and support, its opaque nature challenges user trust-particularly among medical professionals and patients. Explainability is seen as a key solution, but its impact is not straightforward.Through one conceptual and three empirical studies, the research shows that explanations can increase transparency, trust, and user understanding, encouraging greater adoption of AI systems. They also help users maintain confidence after AI errors and can reduce privacy concerns by clarifying data use. However, explanations can also have negative effects, such as increasing cognitive load, overwhelming users in high-stakes settings, and even heightening privacy concerns.To address these mixed outcomes, the dissertation proposes a procedural model for integrating explanations during the pre-use, use, and post-use phases. This model helps balance transparency, cognitive demands, and privacy considerations in practical applications like clinical decision support tools and symptom checkers.Overall, the work contributes to Human-AI interaction literature by offering theoretical, empirical, and practical guidance on designing explainable AI systems that are both trustworthy and user-centered.Cuvillier Verlag, Nonnenstieg 8, 37075 Göttingen 202 pp. Englisch.…

Taschenbuch. Etat : Neu. A Double-Edged Sword: Explainable Artificial Intelligence for Medical Applications.Conceptual and Empirical Insights into the Interaction of Medical Stakeholders with Artificial Intelligence Explanations | Aycan Aslan | Taschenbuch | Göttinger Wirtschaftsinformatik 124 | Englisch | 2025 | Cuvillier | EAN 9783689526528 | Verantwortliche Person für die EU: Cuvillier Verlag, Nonnenstieg 8, 37075 Göttingen, info[at]cuvillier[dot]de | Anbieter: preigu Print on Demand.…