A system for bias estimation in Artificial Intelligence (Al) models using a pre-trained unsupervised deep neural network, comprising a bias vector generator implemented by at least one processor that executes an unsupervised DNN with a predetermined loss function. The bias vector generator is adapted to store a given ML model to be examined, with predetermined features; store a test-set of one or more test data samples being input data samples; receive a feature vector consisting of one or more input samples; output a bias vector indicating the degree of bias for each feature, according to said one or more input samples. The system also comprises a post-processor which is adapted to receive a set of bias vectors generated by said bias vector generator; process said bias vectors; calculate a bias estimation for every feature of said ML model, based on predictions of said ML model; provide a final bias estimation for each examined feature.
A SYSTEM AND A METHOD FOR BIAS ESTIMATION IN ARTIFICIAL INTELLIGENCE (AI) MODELS USING DEEP NEURAL NETWORK