Responsible AI
Responsible AI
AI that works on other people’s data has to earn trust. These are the principles this concept is built around.
Transparency
Sources, queries and assumptions are shown with every answer.
Human oversight
People review and approve anything published or shared.
Data minimisation
Read-only access, and only the data needed for the task.
Public frameworks
Two widely referenced frameworks shape good practice: the EU AI Act (Regulation (EU) 2024/1689), which sets risk-based obligations for AI systems placed on the EU market, and the US NIST AI Risk Management Framework (AI RMF 1.0, 2023), a voluntary guide organised around the functions Govern, Map, Measure and Manage. Where personal data is involved, data-protection law such as the GDPR also applies.
Client to provide · Compliance statements
Any formal compliance commitments, certifications or policies, as confirmed by the client and its advisers.