Accountability
There is unambiguous ownership over AI systems, their impacts and resulting outputs across the AI lifecycle.
Data Protection
Use of data in AI systems is consistent with permitted rights, maintains confidentiality of business and personal information and reflects ethical norms.
Reliability
AI systems are aligned with stakeholder expectations and continually perform at a desired level of precision and consistency.
Security
AI systems, their input, and output data are secured from unauthorized access, and resilient against corruption and adversarial attack.
Transparency
Appropriate levels of disclosure regarding the purpose, design and impact of AI systems is provided so that stakeholders, including end users, can understand, evaluate and correctly employ AI systems and their outputs.
Explainability
Appropriate levels of explanation are enabled so that the decision criteria and output of AI systems can be reasonably understood, challenged and validated by human operators.
Fairness
The needs of all impacted stakeholders are assessed with respect to the design and use of AI system and their outputs to promote a positive and inclusive societal impact.
Compliance
Ensures the design, implementation and use of AI systems and their outputs comply with relevant laws, regulations and professional standards.
Sustainability
Considerations of the impacts of technology are embedded throughout the AI lifecycle to promote physical, social, economic and planetary well-being.