This article explores the various sources of bias in AI, highlighting how biases originate from training data, annotators, and algorithm design. Experts Tessa Charlesworth and William Brady discuss the importance of skepticism towards AI outputs and the risks of unchecked bias, including potential feedback loops that can worsen inaccuracies over time.