AI Assisted Data Labeling with Interactive Auto Label

We demonstrate an AI assisted data labeling system which applies unsupervised and semi-supervised machine learning to facilitate accurate and efficient labeling of large data sets. Our system (1) applies representative data sampling and active learning in order to seed and maintain a semi-supervised learner that assists the human labeler (2) provides visual labeling assistance and optimizes labeling mechanics using predicted labels (3) seamlessly updates and learns from ongoing human labeling activity (4) captures and presents metrics that indicate the quality of labeling assistance, and (5) provides an interactive auto labeling interface to group, review and apply predicted labels in a scalable manner.

Authors

• Michael Desmond IBM Research
• Michelle Brachman
• Evelyn Duesterwald IBM Research
• Casey Dugan
• Narendra Nath Joshi
• Qian Pan IBM Research
• Carolina Spina

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