Equity and transfer

Area: definition. Apply the shared measurement protocol.

Estimated progress toward AI-managed medicine

15% complete — judgment-based estimate as of November 7, 2026. Confidence: low. The scale starts at 0% before ChatGPT's public release in 2022 and ends at 100% when AI manages the field's continuing advancement without human participation. This rates the outcome's contribution to that transition, not the percentage of tasks solved, a measured fraction of the field, or time remaining.

The shared scoring rubric uses five equally weighted dimensions: execution, breadth, agenda-setting, validation, and sustained autonomous improvement. Points for this outcome are 5 + 5 + 0 + 5 + 0 = 15/100, in that order; each dimension has a maximum of 20. These component judgments make the estimate inspectable, but are not independently measured scores.

Reason for the estimate: Age and density subgroup evidence supports limited transportability. Broader demographic and institutional outcome equality cannot be inferred from it. The dated baseline below supplies the findings and source links used for this assessment. Unmeasured components receive no demonstrated-progress credit; missing evidence does not prove a missing capability.

What would move the score: Validate in additional institutions and devices; report absolute subgroup errors and patient outcomes with uncertainty, including underrepresented populations. Higher autonomy scores additionally require AI to select worthwhile work, validate results and improve the process over repeated cycles without human research management, repair or adjudication. Lower the score if replication fails, quality regresses or previously hidden human assistance is found. Preserve this dated estimate when adding future assessments.

Measurement and acceptance rule

Outcome and error differences across relevant demographic groups, institutions, devices, and disease severities.

Evidence requirements

Evaluate the complete clinical workflow prospectively, preferably with randomized allocation where feasible. Compare with current care, not an artificially weak clinician baseline. Separate AI alone from clinician-plus-AI. Prespecify clinically meaningful differences and non-inferiority margins, use adequate power, and conduct follow-up sufficient to detect delayed harms. A higher detection rate alone does not establish longer survival.

Related milestones

See the area's proposed milestones. Proposed targets are distinct from the dated evidence below.

Baseline as of November 7 2026

Status: Subgroup evidence; wider transportability unknown. Sources accessed November 7, 2026. This is a documentary baseline, not an independent replication or an assertion of the worldwide best result. An unknown measurement is not zero.

Dated findings

January 31, 2026: MASAI reports sensitivity improvement consistent across age and breast-density groups. MASAI randomized screening trial follow-up.

Interpretation and tracking value

Within-trial subgroup consistency is not evidence of equal outcomes across ethnicities, countries, scanners or clinical systems; small subgroups may conceal uncertainty.

Next comparable measurement

Validate in additional institutions and devices; report absolute subgroup errors and patient outcomes with uncertainty, including underrepresented populations. Preserve this dated observation; append future results with their model/system version, denominator, budget and evidence level rather than overwriting it.