A Dutch government website that brings together the legal requirements, recommended measures and supporting tools for responsible use of algorithms and AI, organised by lifecycle phase, role and topic.
| Full name | Algoritmekader (Dutch government Algorithm Framework) |
| Website | https:// |
| Source code | https:// |
| Developed by | Dutch Ministry of the Interior and Kingdom Relations (MinBZK) |
| Type | Framework: Website with filterable requirements, measures and tools |
| Lifecycle phase | Design, Development, Evaluation, Deployment |
| FUTURE-AI | Traceability, Fairness, General recommendations |
| For | Policy makers and managers, AI developers |
| Facilitation | No facilitator needed |
| Skills needed | none |
| Cost | Free |
| Languages | Dutch |
| Maturity | Established |
| Licence | EUPL-1.2 |
What it is¶
The Algoritmekader links each legal requirement (for example from the GDPR, the AI Act and non-discrimination law) to practical measures and to tools such as the IAMA and the AI Impact Assessment. You can filter by lifecycle phase, from problem analysis to decommissioning, by role, such as project leader, jurist or developer, and by topic, such as privacy, discrimination or procurement. It also has a section on the AI Act, with timelines and help to classify your system. The content is developed in the open on GitHub and updated in numbered releases; the site is in Dutch.
In healthcare¶
It targets Dutch government bodies rather than health care, but public health organisations can use it to find which rules and measures apply at each stage of a clinical AI project.
Where to use it in The ELSA Way¶
Legal and regulatory considerations › Country-specific frameworks: For Dutch projects it is the government’s own map of which laws apply to an algorithm and what you need to do to comply with each one.
Governance and accountability › Governance structures: Its role-based view shows who in the organisation is responsible for which measures, which helps you set up oversight and change management.
Related tools¶
IAMA: A structured discussion guide that helps a public organisation decide whether and how to use an algorithm, with a step-by-step check of its effects on fundamental rights.
AI Impact Assessment: A question set that walks a multidisciplinary team through the purpose, impact, technical design, data and risks of an AI system, and records the decision whether to use it.
ALTAI: A self-assessment checklist from the EU High-Level Expert Group on AI that helps you test an AI system against the seven requirements for trustworthy AI and spot where you need extra measures.