Responsible AI
Responsible AI
We treat responsible AI as an operating discipline — policy, risk classification, human oversight, evaluation, monitoring and audit evidence woven into delivery.
Purpose and proportionality
AI should serve a clear decision or outcome, with methods proportionate to risk and benefit.
Human accountability
People remain accountable for high-impact decisions, exceptions and escalations.
Transparency
Stakeholders should understand where AI is used, what it influences and how to seek review.
Security and privacy
Data minimisation, access control and secure deployment are defaults, not add-ons.
Fairness and evaluation
Systems affecting people or public programmes require appropriate testing and documentation.
Continuous oversight
Monitoring, incident response and retirement pathways keep systems trustworthy over time.