Responsibility Gaps and Black Box Healthcare AI: Shared Responsibilization as a Solution.
Responsibility Gaps and Black Box Healthcare AI: Shared Responsibilization as a Solution.
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责任差距和黑匣子医疗保健人工智能:共享责任作为解决方案。
DOI:
10.1007/s44206-023-00073-z
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发表时间:
2023
期刊:
影响因子:
--
通讯作者:
Blumenthal-Barby,Jennifer
中科院分区:
文献类型:
--
作者:
Lang,BenjaminH;Nyholm,Sven;Blumenthal-Barby,Jennifer
As sophisticated artificial intelligence software becomes more ubiquitously and more intimately integrated within domains of traditionally human endeavor, many are raising questions over how responsibility (be it moral, legal, or causal) can be understood for an AI’s actions or influence on an outcome. So called “responsibility gaps” occur whenever there exists an apparent chasm in the ordinary attribution of moral blame or responsibility when an AI automates physical or cognitive labor otherwise performed by human beings and commits an error. Healthcare administration is an industry ripe for responsibility gaps produced by these kinds of AI. The moral stakes of healthcare are often life and death, and the demand for reducing clinical uncertainty while standardizing care incentivizes the development and integration of AI diagnosticians and prognosticators. In this paper, we argue that (1) responsibility gapsaregenerated by “black box” healthcare AI, (2) the presence of responsibility gaps (if unaddressed) creates serious moral problems, (3) a suitable solution is for relevant stakeholders to voluntarilyresponsibilizethe gaps, taking on some moral responsibility for things they are not, strictly speaking, blameworthy for, and (4) should this solution be taken, black box healthcare AI will be permissible in the provision of healthcare.