Data labelling means adding the correct answer to data so that an AI can learn from it.
Example
People mark every bicycle in photos so that a model learns to recognise bicycles.
For pros
Labels come from experts, crowd workers or increasingly from AI under human control. Clear guidelines and double checks are needed, otherwise the model learns errors and bias. Working conditions in the labelling industry are a subject of public debate.
