Glossary: Application and Credential Attacks, and AI Risks

bias

When an AI's outputs are consistently unfair to some people or groups, usually because the training data held unfair past decisions or left some groups out. For example, a credit model trained mostly on city cafés might give small rural cafés lower limits even when their payment history is the same.