Adequate data quality is a crucial precondition to all AI system operations.
The AI System Owner should ensure that the organization designs and entrenches appropriate workflows and technical arrangements for
1) gathering and producing information on data quality, and
2) ensuring that the data (including the training, validation, and testing data) is of adequate quality and sufficiently relevant, complete, and representative.
Data quality analyses should also include an analysis of additional data needs.