Response to our reviewers
We would like to thank the authors of the commentaries for their critical appraisal of our feature article, Who is afraid of black box algorithms?1 Their comments, suggestions and concerns are various, and we are glad that our article contributes to the academic debate about the ethical and epistemi...
| Authors: | ; |
|---|---|
| Format: | Electronic Article |
| Language: | English |
| Check availability: | HBZ Gateway |
| Journals Online & Print: | Drawer...
|
| Fernleihe: | Fernleihe für die Fachinformationsdienste |
| Published: |
BMJ Publ.
2021
|
| In: |
Journal of medical ethics
Year: 2021, Volume: 47, Issue: 7, Pages: 514 |
| Online Access: |
Presumably Free Access Volltext (lizenzpflichtig) Volltext (lizenzpflichtig) |
| Summary: | We would like to thank the authors of the commentaries for their critical appraisal of our feature article, Who is afraid of black box algorithms?1 Their comments, suggestions and concerns are various, and we are glad that our article contributes to the academic debate about the ethical and epistemic conditions for medical Explanatory AI (XAI).We would like to bring to attention a few issues that are common worries across reviewers. Most prominently are the merits of computational reliabilism (CR)—in particular, when promoted as an alternative to transparency—and CR as necessary but not sufficient for delivering trust. We finalise our response by addressing concerns about the place and role of artificial intelligence (AI) in medical decision-making and the physician’s responsibilities.We understand the concerns and reservations that some of the reviewers express regarding the epistemic merits of CR. We believe that, in part, this is due to a practice too deeply rooted in transparency. But on … |
|---|---|
| ISSN: | 1473-4257 |
| Contains: | Enthalten in: Journal of medical ethics
|
| Persistent identifiers: | DOI: 10.1136/medethics-2021-107531 |