METHOD FOR TRACKING LACK OF BIAS OF DEEP LEARNING AI SYSTEMS

摘要

A method including receiving data including an unknown vector including a data structure populated with unknown features describing a first user and a score predicted by a MLM trained using a prediction data set. The score represents a prediction regarding the first user. The prediction data set includes the unknown vector stripped of a biased data set. The data also includes a prediction whether the first user belongs to the cohort. The method also includes hashing information types used by the primary MLM and the supervisory MLM to produce a first hashed data, the information types including at least the unknown vector, the score, and the prediction. The method also includes combining the first hash and a schema to produce a compliance document. The method also includes hashing the compliance document to produce a second hashed data. The method also includes storing the second hashed data in a blockchain.