Responsibility Gaps and Black Box Healthcare AI: Shared Responsibilization as a Solution
Benjamin H Lang, Sven Nyholm, Jennifer Blumenthal-Barby · 2023
Read Responsibility Gaps and Black Box Healthcare AI: Shared Responsibilization as a Solution by Benjamin H Lang, Sven Nyholm, Jennifer Blumenthal-Barby (2023) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11003475.txt.
Description
Benjamin Lang, Sven Nyholm, and Jennifer Blumenthal-Barby take on who bears blame when opaque health software errs, in work from twenty twenty-three. Health care uses smart software more and more for diagnosis and forecasts. Some tools are black boxes whose inner steps no one can inspect. When such a tool errs, no human may seem to be at fault. That blank space is called a responsibility gap.
The authors argue that black box health tools do create such gaps. Left alone, those gaps pose real moral harm for patients and staff. Their fix is for key parties to take on shared blame by choice. Each party accepts some moral weight for outcomes it did not strictly cause. If that step is taken, the authors argue, black box tools can be used fairly. The paper works through each claim in order to defend the fix.
Catalog record
| CREATOR | Benjamin H Lang, Sven Nyholm, Jennifer Blumenthal-Barby |
|---|---|
| YEAR | 2023 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 52 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |