Data Labeling
The process of annotating data with informative tags or categories to provide ground truth for supervised machine learning training.
In plain language
Humans tagging data to teach AI what things are. Looking at thousands of photos and marking 'cat' or 'dog' so the AI can learn to tell them apart. It's tedious but essential.
Why this matters
Data labeling quality directly affects model accuracy and fairness; biased or inconsistent labels propagate through the entire AI system. Your governance framework should include quality assurance standards for labeling, documented labeling guidelines and audits to ensure consistency and fairness.
Relevance
ImplementationData labeling is a critical quality control point that directly influences model accuracy and bias; governance must include standards for labeler selection, training and quality assurance.
Related terms
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