Irem Karaman Sebin

From model failure to system harm: operationalizing a sociotechnical pathway for healthcare AI safety

Healthcare artificial intelligence (AI) is commonly evaluated using measures of discrimination, calibration, sensitivity, specificity, and benchmark accuracy. Although these metrics are necessary, safety ultimately depends on what occurs after an AI output enters a clinical system, whether it is noticed, trusted, verif...