Responsible AI & Governance
A practical grounding in responsible AI, built on the NIST AI Risk Management Framework, the EU AI Act, and the OECD and UNESCO principles.
Transparency and human oversight
People should know when AI is involved Transparency runs through every major framework, and it is one of the easiest things to get right. It has three practical layers. 1. Disclosure Tell people when they are interacting with an AI system rather than a person, and when content was AI-generated. The EU AI Act makes […]
Who is accountable when the system is wrong
“The system decided” is not an answer anyone accepts An AI system produces a wrong outcome that affects someone. The question that follows is never technical. It is: who is answerable, and what can the affected person do about it? Organisations that cannot answer that in advance discover, at the worst possible moment, that everyone […]
The questions worth asking every time
Responsible AI is a habit, not a document Most organisations write principles and then struggle to connect them to Tuesday. The connection is a short set of questions asked routinely — in the meeting where someone proposes a tool, not in an annual review. The six Who is affected by this, and were they asked? […]