Summary
Specifies processes and methodologies for identifying and addressing bias in algorithm development, including validation-data selection, documentation of intended application boundaries, communication of system limitations, and management of user expectations.
Healthcare Implications
Healthcare AI developers, health systems, and evaluators can use the standard to structure bias testing, subgroup validation, intended-use boundaries, documentation, and user communication for clinical and administrative algorithms.