Garbage In, Garbage Out: Why Training Data Matters for AI Learning

The quality of the data you use to train AI systems determines how well they perform. High-quality training data ensures accurate, fair, and reliable results, while poor-quality data can lead to flawed outputs. For example, studies show that cleansing mislabeled data can boost AI accuracy from 59.7% to 61.1%. On more refined test sets, accuracy jumps ev…