Data Quality Control

Big AI companies need to do reinforcement learning from human feedbacks, to get high-quality labeling on images and other media data to train AIs for accuracy. Some companies usually do this in regions where labor is cheap. Labeling tasks like medical or legal, need expert to complete the job. It is crucial to verify that the labelers have sufficient knowledge and skills to accurately label in these domains, e.g., by proving they are indeed an MD or JD.

zkTLS-based data proofs are an efficient way to verify the eligibility of labelers and weed out the bad actors lying about their credentials and providing inaccurate training data in these specific domains. Automating credential verification with data proofs can improve the integrity of AI training data sets but also streamline operations, cutting costs and increasing trust in the data pipeline.