Answer Area

Protect personal information and apply strong safeguards to keep data secure. Answer: Privacy and security

Make AI solutions understandable by explaining how and why decisions are made. Answer: Transparency

Design AI solutions that are accessible to people of all abilities and experiences. Answer: Inclusiveness

Involve human oversight in the control of AI solutions. Answer: Accountability

Microsoft’s Responsible AI principles provide a practical framework for building and deploying trustworthy AI systems.

Privacy and security is the principle focused on protecting personal information and ensuring strong safeguards—such as least privilege access, encryption, DLP controls, secure storage, and auditing—so data remains protected throughout collection, processing, and usage.

Transparency is about making AI systems understandable. This includes communicating when AI is being used, explaining system capabilities and limitations, and providing clarity on how outputs are produced (for example, what data sources are used, what assumptions apply, and why certain recommendations are generated). Transparency reduces confusion and helps users calibrate trust appropriately.

Inclusiveness ensures AI solutions are designed to benefit people of diverse abilities, backgrounds, and experiences. Practically, this includes accessibility (assistive technologies, readable outputs), inclusive UX design, and testing across diverse user groups so the solution does not exclude or disadvantage certain populations.

Accountability emphasizes that humans and organizations remain responsible for AI outcomes. Involving human oversight is a direct expression of accountability: setting governance, defining who owns decisions, establishing escalation paths, and ensuring there are controls for review, intervention, and correction when AI outputs are unsafe or incorrect.