Bias is a critical challenge in predictive and generative AI that involves images of humans. People have a variety of body shapes, skin tones and other features that can be challenging to represent completely in training data. Without attention to bias risks, ML systems have the potential to treat people unfairly, and even to make humans more likely to do so. In this talk, we will examine the ways in which bias can arise in visual AI systems. We’ll share techniques for detecting bias and strategies for minimizing it in production AI systems.