New Model Reduces Bias And Enhances Trust In Ai Decision-making And

University of Waterloo researchers have developed a new explainable artificial intelligence (AI) model to reduce bias and enhance trust and accuracy in machine learning-generated decision-making and knowledge organization. The model aims to eliminate bias and pattern entanglement by untangling complex patterns from data to relate them to specific underlying causes unaffected by anomalies and mislabeled instances, thereby enhancing trust and reliability in Explainable Artificial Intelligence (XAI).