Data Quality

The measure of data's fitness for its intended use in AI systems, encompassing accuracy, completeness, consistency, timeliness, validity and uniqueness.

How good your data is for training AI. Garbage in, garbage out; if your data is incomplete, outdated or full of errors, your AI will learn the wrong things.

Data quality is the foundation of trustworthy AI. Your governance framework must include data quality standards, measurement processes and accountability structures because poor data quality is the root cause of many AI failures and biases.