Percentages and reasons
AI explainability and ultimate human responsibility within the medical field
Bibliographic Data
| ID | 21703530 |
|---|---|
| Authors | Markus Herrmann (0000-0001-8893-9685, German Cancer Research Center, corresponding author), Andreas Wabro (0009-0006-0424-6181, Heidelberg University), Eva C Winkler (0000-0001-7460-0154, Heidelberg University) |
| Year | 2024 |
| Volume | 26 |
| Issue | 2 |
| Publication date | 2024-06-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Ethics and Information Technology (JOURNAL) |
| Journal identifiers | ISSN: 1388-1957 • E-ISSN: 1572-8439 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s10676-024-09764-8 |
| OpenAlex | W4394617203 |
| Language | EN |
| References cited | 25 |
With regard to current debates on the ethical implementation of AI, especially two demands are linked: the call for explainability and for ultimate human responsibility. In the medical field, both are condensed into the role of one person: It is the physician to whom AI output should be explainable and who should thus bear ultimate responsibility for diagnostic or treatment decisions that are based on such AI output. In this article, we argue that a black box AI indeed creates a rationally irresolvable epistemic situation for the physician involved. Specifically, strange errors that are occasionally made by AI sometimes detach its output from human reasoning. Within this article it is further argued that such an epistemic situation is problematic in the context of ultimate human responsibility. Since said strange errors limit the promises of explainability and the concept of explainability frequently appears irrelevant or insignificant when applied to a diverse set of medical applications, we deem it worthwhile to reconsider the call for ultimate human responsibility
Engineering ethics · Environmental ethics · Sociology · Artificial Intelligence in Healthcare and Education · Engineering · Ethics in Clinical Research · Explainable Artificial Intelligence (XAI · Mathematics · Philosophy · Psychology
The impossibility of moral responsibility
On the ethics of algorithmic decision-making in healthcare
Explainability, Public Reason, and Medical Artificial Intelligence
Learning to Live with Strange Error
Artificial Intelligence and Black‐Box Medical Decisions
Solving the Black Box Problem
Beyond generalization
| Citation velocity | historical |
|---|---|
| Highly cited | No |