Accountable

Accountability means that humans, not machines, are responsible for what AI does. People must be able to explain how AI decisions and tasks are complete, and we must take responsibility when things go wrong. Accountable teams help build trust and help us to follow rules and laws.

How will we use this principle?

• We will assign clear human oversight for every AI use case and system to ensure that qualified individuals are responsible for each stage of AI design, use, and outcomes.

• We will maintain complete audit trails to enable traceable decisions, data changes, and AI use across the AI lifecycle.

• We will define roles and responsibilities within the organisation to clarify who is accountable, and informed throughout AI development, adoption, and use.

• We will train our team in ethical and legal responsibility to equip them to make informed, accountable choices when building or using AI technologies.

• We will implement explainability protocols to ensure that users and regulators can understand the rationale and reasoning behind our use of AI, including AI-generated decisions, designs, and procurement.