AI Assisted Data Labeling with Interactive Auto Label

Authors

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

DOI:

https://doi.org/10.1609/aaai.v36i11.21714

Keywords:

Human Computer Interaction, HCI, Data Labeling, Productivity Tools, Machine Learning

Abstract

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.

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Published

2022-06-28

How to Cite

Desmond, M., Brachman, M., Duesterwald, E., Dugan, C., Nath Joshi, N., Pan, Q., & Spina, C. (2022). AI Assisted Data Labeling with Interactive Auto Label. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 13161-13163. https://doi.org/10.1609/aaai.v36i11.21714