Jonas Ammeling
Biographic Data
| ID | 4465823 |
|---|---|
| NAME | Jonas Ammeling |
| GIVEN NAMES | Jonas |
| FAMILY NAME | Ammeling |
| SIGNATURE | AMMELING J |
| AFFILIATIONS | Technische Hochschule Ingolstadt |
| ORCID | 0000-0002-0335-1194 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 2 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Perceived responsibility in AI-supported medicine
In a representative vignette study in Germany with 1,653 respondents, we investigated laypeople’s attribution of moral responsibility in collaborative medical diagnosis. Specifically, we compare people’s judgments in a setting in which physicians are supported by an AI-based recommender system to a setting in which they are supported by a human colleague. It turns out that people tend to attribute moral responsibility to the artificial agent, alt…
An interdisciplinary perspective on AI-supported decision making in medicine
Artificial intelligence (AI)-supported medical diagnosis offers the potential to utilize the collaborative intelligence of context-sensitive humans and narrowly focused machines for patients’ benefit. The employment of machine-learning-based decision-support systems (MLDSS) in medicine, however, raises important multidisciplinary challenges that cannot be addressed in isolation. We discuss three disciplinary perspectives on the topic and their in…
An interdisciplinary perspective on AI-supported decision making in medicine
Artificial intelligence (AI)-supported medical diagnosis offers the potential to utilize the collaborative intelligence of context-sensitive humans and narrowly focused machines for patients’ benefit. The employment of machine-learning-based decision-support systems (MLDSS) in medicine, however, raises important multidisciplinary challenges that cannot be addressed in isolation. We discuss three disciplinary perspectives on the topic and their in…
An interdisciplinary perspective on AI-supported decision making in medicine
Artificial intelligence (AI)-supported medical diagnosis offers the potential to utilize the collaborative intelligence of context-sensitive humans and narrowly focused machines for patients’ benefit. The employment of machine-learning-based decision-support systems (MLDSS) in medicine, however, raises important multidisciplinary challenges that cannot be addressed in isolation. We discuss three disciplinary perspectives on the topic and their in…
Perceived responsibility in AI-supported medicine
In a representative vignette study in Germany with 1,653 respondents, we investigated laypeople’s attribution of moral responsibility in collaborative medical diagnosis. Specifically, we compare people’s judgments in a setting in which physicians are supported by an AI-based recommender system to a setting in which they are supported by a human colleague. It turns out that people tend to attribute moral responsibility to the artificial agent, alt…
Artificial Intelligence in Healthcare and Education (2 works) · Ethics and Social Impacts of AI (2 works) · Art (1 works) · Artificial Intelligence (1 works) · Clinical decision making (1 works) · Computer Science (1 works) · Engineering (1 works) · Engineering ethics (1 works) · Explainable Artificial Intelligence (XAI (1 works) · Family medicine (1 works)