AMA J Ethics. 2019;21(2):E125-130.
doi: 10.1001/amajethics.2019.125.
Abstract
Should an artificial intelligence (AI) program that appears to have a better success rate than human pathologists be used to replace or augment humans in detecting cancer cells? We argue that some concerns—the “black-box” problem (ie, the unknowability of how output is derived from input) and automation bias (overreliance on clinical decision support systems)—are not significant from a patient’s perspective but that expertise in AI is required to properly evaluate test results.
Here is an excerpt:
Automation bias. Automation bias refers generally to a kind of complacency that sets in when a job once done by a health care professional is transferred to an AI program. We see nothing ethically or clinically wrong with automation, if the program achieves a virtually 100% success rate. If, however, the success rate is lower than that—92%, as in the case presented—it’s important that we have assurances that the program has quality input; in this case, that probably means that the AI program “learned” from a cross section of female patients of diverse ages and races. With diversity of input secured, what matters most, ethically and clinically, is that that the AI program has a higher cancer cell-detection success rate than human pathologists.
