Agenda

Dive into the world of AI Bias. This talk explores the pervasive issue of AI bias and its implications. Understand various forms of bias, from data and perception bias to survivorship and availability bias, and how they influence AI models. Learn practical strategies to counteract these biases, such as A/B testing, bias detection during model training, and comprehensive monitoring during model scoring. The talk concludes with a focus on action steps post-detection, including model retraining and selection of challenger models, intending to achieve equitable outcomes, enhance transparency, and meet evolving regulatory requirements.