Reliable decision-making with AI: finding bias, monitoring performance and making compliance demonstrable.
As soon as AI takes part in decisions — about people, money or safety — the highest requirements apply: explainable, fair and auditable. For many applications the AI Act also makes this a legal requirement.
Trust is demonstrability: not saying that the model is fair, but showing it — with monitoring, audit trails and reports that convince a regulator.
Testing and auditing rested on one assumption: the same system gives the same answer to the same question. For AI that assumption does not hold. It removes the floor under classic acceptance testing — you cannot sign off on something that will respond differently tomorrow.
Into that gap steps a discipline of its own: demonstrability. Not claiming the model is fair, but showing it — with bias measurements, drift monitoring and audit trails that let you reconstruct last month's decision in front of a client or a regulator.
You set up monitoring and accountability for an AI decision application — a real or realistic scenario from your organisation.
An analyst sees prediction quality slowly declining and pinpoints exactly which population shift is behind it.
An HR adviser audits the selection model for unequal treatment and redesigns the features.
A risk manager builds the dashboard with which the organisation can demonstrate every quarter that it is in control.
You take this module the way you take the whole programme: classes every other week on Friday and Saturday, with a study load of 15–20 hours per week, of which 10–15 hours are self-study. The teaching is a mix of classroom lessons, practice-based learning, blended learning and working groups or study teams — taught by lecturers who practise the profession themselves every day.
You conclude each theme with a professional product or a technical solution based on a real situation in your own work, which you discuss in an assessment with the lecturer. This way your portfolio grows with real work — and your employer benefits directly.
The format is not new: the teaching approach and the AI modules have been running for three years at the AI Proeflokaal — with business, with government, and across part-time modules and minors. What you meet in class here has already been worn in elsewhere.
After this module you deliver a monitoring and accountability setup with which an AI decision system runs in an auditable way.
Email or call the programme — we're happy to help you think it through.