Responsible AI: Fairness, Transparency, and Accountability
Responsible AI: Fairness, Transparency, and Accountability Responsible AI means building systems that treat people fairly, explain decisions, and can be held to account. This approach touches technology, policy, and everyday life. It starts with clear goals and ends with trustworthy outcomes. Fairness has many parts. A fair system should avoid harming groups, measure outcomes by different groups, and show how decisions are made. Teams can check for unequal error rates, calibrate scores across attributes, and test changes before launch. Practical steps include setting fair objectives, auditing data quality, and documenting model reasoning in plain language. ...