Responsible AI & ethics
Accountability is not a brake on innovation — it is what makes AI usable and durable.
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Whether an AI use is responsible is not decided once but again and again: at design, at training, at every decision the system supports. Organisations that get this right do not have thick ethics reports — they have working agreements: who decides, what is logged, when a human intervenes, how we explain what the system does.
What you get
- Setting up AI governance: roles, policy, decision-making and oversight — sized to your organisation
- Guidance on impact assessments: IAMA, FRIA, DPIA — as one integrated process, avoiding duplicate work
- Ethical analysis of concrete uses, including facilitation of moral deliberation
- Tailored AI frameworks: from principles to testable design requirements (explainability, human oversight, bias control)
Mini-case: The Decision Advisory System (BAS) at the CIZ was all about these questions: how do you keep a human in the loop for decisions that directly affect citizens, and how do you make a model's advice explainable? Read the case.