The longer story
AI systems can exhibit bias, and frequently do. Bias typically enters through training data that reflects historical inequalities, design decisions that favour certain groups, or evaluation processes that fail to account for diverse populations. The result can be AI systems that discriminate in hiring, lending, policing, healthcare, and other high-stakes areas. Recognising and mitigating AI bias is an active area of research and a key component of responsible AI practice.