{"entity":{"id":"idea-data-subgroup-performance-reporting-mandate","kind":"idea","name":"Mandatory subgroup performance reporting for cancer AI","aka":[],"tldr":"Every AI tool would have to report how well it works for women and men, different ethnic groups, ages, scanner types and hospitals, not just an overall score.","summary":"Cancer AI is often validated on populations that do not match deployment populations; performance gaps by skin tone (dermatology), breast density, ethnicity and scanner vendor are documented. The proposal requires, for clearance and in the model registry, performance reporting across a standard set of subgroups with minimum sample sizes and confidence intervals, and labelling restrictions where performance is unknown or inadequate.","asOf":"2026-09-08","links":[{"label":"Bottleneck evidence (AI that is built but not validated or deployed): Wu et al., How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals (Nature Medicine 2021)","url":"https://doi.org/10.1038/s41591-021-01312-x"}],"tags":[],"related":[],"cancers":[],"sections":["ai-computation"],"technologies":["dermoscopy-ai","mammography"],"targets":[],"drugs":[],"companies":[],"institutions":[],"pathways":[],"terms":[],"trials":[],"people":[],"bottlenecks":["b-ai-validation","b-trial-diversity"],"keyPapers":["paper-wu-nat-med"],"journals":[],"dependsOn":[],"notes":[],"hypothesis":"Mandatory subgroup reporting will reveal clinically meaningful performance disparities in a substantial share of cleared cancer AI and lead to label restrictions or retraining for those models.","rationale":"Pulse oximetry's racial bias went unrecognised for decades because subgroup performance was not required; AI will repeat this at scale unless reporting is mandatory.","test":"Evaluate ten cleared cancer AI devices on the standard subgroup set using sequestered data; publish disparities; track subsequent label changes.","maturity":"speculative","actor":"regulator","cost":"small","horizonYears":2},"route":"/ideas/idea-data-subgroup-performance-reporting-mandate/","neighbours":{"section":[{"id":"ai-computation","kind":"section","name":"AI & Computation","route":"/fronts/ai-computation/"}],"technology":[{"id":"dermoscopy-ai","kind":"technology","name":"Dermoscopy, total-body photography & AI skin analysis","route":"/technologies/dermoscopy-ai/"},{"id":"mammography","kind":"technology","name":"Mammography & tomosynthesis","route":"/technologies/mammography/"}],"bottleneck":[{"id":"b-ai-validation","kind":"bottleneck","name":"AI that is built but not validated or deployed","route":"/bottlenecks/b-ai-validation/"},{"id":"b-trial-diversity","kind":"bottleneck","name":"Trials do not represent the people who get cancer","route":"/bottlenecks/b-trial-diversity/"}],"paper":[{"id":"paper-wu-nat-med","kind":"paper","name":"How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals","route":"/key-papers/paper-wu-nat-med/"}]}}