What is Responsible AI?

Building and using AI in ways that are fair, safe, private, transparent and accountable.

In plain English

Different organisations phrase the principles differently. Microsoft, for example, lists six: fairness, reliability and safety, privacy and security, inclusiveness, transparency and accountability. In practice this means testing for unfair outcomes, protecting data, explaining how the system is used, keeping people in the loop for important decisions and naming who is accountable.

Example

A hiring tool is tested to see whether it scores equally qualified candidates differently by gender, and a person makes the final decision.

Easy to confuse with

• Bias in AI: Bias is one problem. Responsible AI is the whole set of practices for managing risks like it.

Where you will meet it

This idea belongs to the subject area of these practice tests. We do not publish or predict real exam questions.

• IAPP AIGP practice tests
• ISACA AI Fundamentals practice tests
• Microsoft AI-901 practice tests
• CompTIA SecAI+ practice tests

Related terms

• Bias in AI: Results that are systematically unfair to some people or groups.
• Hallucination: When an AI model states something false or invented as if it were true.
• AI agent: An AI system that pursues a goal by deciding on steps and using tools, not only by answering one question.

Written and checked by the Be Ready Education team, last reviewed 2 November 2026. General study information, not professional advice. Providers change names and rules, so confirm details on the official documentation. Not affiliated with, endorsed by or sponsored by any certification vendor or exam body. Certification names, exam codes and product names are trademarks of their respective owners and are used only to identify the exam a practice product prepares for. Our questions are original and are not actual exam questions.