Categories

Explore techniques organized by their primary assurance goals. Each category represents a key aspect of responsible AI development.

Cross-cutting techniques that support any assurance goal.

Understanding how AI systems make decisions and what factors influence their outputs.

Ensuring AI systems treat different groups and individuals equitably.

Protecting personal data and maintaining confidentiality in AI systems.

Building AI systems that perform consistently and predictably.

Ensuring AI systems operate safely and do not cause harm.

Protecting AI systems from malicious attacks and unauthorized access.

Making AI systems and their decision-making processes open and understandable.