Human Annotation

Before AI-powered tools can identify objects or understand speech, they need people to teach them. The human-in-the-loop model assumes that machines improve their performance using data processed by humans. Only with people’s help can AI deliver relevant search results, recognize faces, recommend products, identify diagnoses, etc.Machine learning (ML) models become effective only when they learn from quality training datasets. Creating these datasets is called data annotation, which assumes that professionals mark texts, images, audio, or video files with specific tags. Though every data annotator uses advanced software for marking files, this process is also called manual annotation.