Deployment and monitoring
Strategy and development
Modeling
Data enablement
Evaluation
Human-centric
Transparency
AI solutions should include responsible disclosure to provide stakeholders with a clear understanding of what is happening in each solution across the AI lifecycle.
AI solutions should be developed and delivered in a way that answers the questions of how and why a conclusion was drawn from the solution.
Explainability
of 3
1
Human oversight and responsibility should be embedded across the AI lifecycle to manage risk and comply with applicable laws and regulations.
Accountability
3
2
of 3
AI solutions should be designed to reduce or eliminate bias against individuals, communities, and groups.
Fairness
3
AI solutions should be designed to be energy efficient, reduce carbon emissions, and support a cleaner environment.
Sustainability
2
AI solutions should be designed to comply with applicable privacy and data protection laws and regulations.
Privacy
1
Values-led
of 4
Robust and resilient practices should be implemented to safeguard AI solutions against bad actors, misinformation, or adverse events.
Security
3
AI solutions should consistently operate in accordance with their intended purpose and scope and at the desired level of precision.
Reliability
2
Data used in AI solutions should be acquired in compliance with applicable laws and regulations and assessed for accuracy, completeness, appropriateness, and quality to drive trusted decisions.
Data integrity
1
Trustworthy
AI solutions should be designed and implemented to safeguard against harm to people, businesses, and property.
Safety
4
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Values-led
Trustworthy
Human-centric