DPIA for AI applications
We provide the technical input for your DPIA: data, model behaviour, risks and monitoring, working with your data protection officer. We’re working with LUMC on AI running on sovereign infrastructure.
Together with LUMC’s cairelab, we ensure AI in healthcare is managed securely, with control over data and models
LUMC wants to manage AI sustainably in everyday clinical practice, using sovereign, on-premises infrastructure to safeguard safety, privacy and control over data and models. Together, we’re working on model development, CI/CD, model serving, monitoring, maintenance and integration with clinical systems.
What will our DPO ask when the model is included in the DPIA?
A DPIA requires a description of the data processing, its purpose, the risks and the measures in place. For AI, that also covers training data, bias and explainability. We provide the technical details; the assessment remains yours.
Technical facts to include in the DPIA for each AI application
Which data, for what purpose
Which personal data the model uses during training and in use, where it comes from, what it is used for and what you can leave out.
How the model behaves
What the model predicts or generates, where it makes mistakes, whether its results vary between groups and how you explain a result.
Measures built into the system
For GVB, software counts passengers in camera footage that no one views or shares. We describe choices like these as measures for each risk.
Monitoring after launch
We measure whether the model’s data and outputs shift, so you can see when the DPIA needs updating.
The DPIA starts with model design, not just before go-live
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Describe the processing
Together with your data protection officer or privacy officer, we describe the data, purpose, model and who uses the output.
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Risks and measures
We test the model for errors and bias and propose a technical measure for each risk.
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Keep it up to date
When there is a new model, new data or a different use, we submit the changes for review.
Does our AI application require a DPIA, and what do you do—and not do?
A good fit if
You plan to use a model or AI application that processes personal data from customers, patients or employees, and your data protection officer asks for technical details you cannot readily provide.
Not a fit if
The AI does not process personal data, or you need someone to provide the legal assessment and approve the DPIA. That remains the responsibility of the data controller, working with a data protection officer or legal adviser.
What determines the scope
The number of models and data sources involved, whether the AI is built in-house or purchased, what documentation already exists and whether a FRIA is also needed.
Do you take over the DPIA?
No. Your organisation remains responsible for the DPIA and the decisions it involves. We do not provide legal advice; we provide the technical description, assessments and measures your data protection officer and legal adviser need to take it forward.
DPIA, IAMA or FRIA: which assessment does your AI application need?
A DPIA
Choose this if your application processes personal data and is likely to pose a high privacy risk. This follows from the GDPR; the AP sets out nine criteria for assessing it.
An IAMA alongside it
Choose this if you are a government body or public organisation. The AP recommends the IAMA for assessing human rights when using algorithms.
Prepare a FRIA
Choose this if you are a government body or public service planning to use high-risk AI. Our advice: use the technical findings from the DPIA; see the AI Act.
We document models as we build them, and that’s what a DPIA needs
Data Science Lab has worked with data and AI since 2016 as a Databricks Partner and Microsoft Partner. We build models and set up monitoring. We don’t provide legal advice, but we do provide the technical evidence.

Your AI application and your DPO’s questions are the focus of our first conversation
Stef Stoelwinder
Business DevelopmentStef is your point of contact. In our first conversation, we’ll discuss the AI application, what data goes into it and what your DPO has already asked.
E-mail info@datasciencelab.nl
Phone +31 (0)20 3636 724
Which model is your DPO asking for technical justification for right now?
Describe the application, the personal data and what your DPO or privacy officer has already asked. We’ll reply by email, or arrange an initial meeting.
Message sent
Thanks for your message. We’ll be in touch as soon as possible.
Frequently asked questions
According to the Autoriteit Persoonsgegevens (AP), an organisation must first carry out a DPIA if processing personal data is likely to pose a high privacy risk. On algorithms, the AP says that if you want to use algorithmic systems that process personal data, a DPIA is mandatory. This also applies to pilots, tests and trial projects.
The AP refers to Article 35 of the GDPR. A DPIA is part of your broader data governance.
The AP identifies three sources of guidance: the GDPR itself, the AP’s DPIA list and nine criteria set by EU privacy regulators. As a rule of thumb, you should carry out a DPIA if your processing meets two or more criteria. Examples include automated decisions, profiling, sensitive data, linked databases and new technology.
If you meet none or only one of the criteria, the AP says you must be able to explain clearly why you are not carrying out a DPIA.
According to the AP, it must include at least a systematic description of the processing and its purposes, an assessment of necessity and proportionality, an assessment of privacy risks and the proposed measures.
For algorithms, the AP calls for particular attention to technical aspects such as the choice of algorithm and bias, to transparency and explainability, and to rights such as erasure and rectification. The Model DPIA Rijksdienst sets out a DPIA in seventeen points.
The data controller must ensure that a DPIA is carried out and remains ultimately responsible, even if someone else carries it out. If your organisation has a data protection officer (DPO), the AP says you must seek their advice and include it in the report.
A processor must support you by providing the information you need. That is where our work fits in: providing the technical description of the data, model and measures.
According to the AP, the FRIA, the fundamental rights impact assessment under the AI Act, complements the DPIA. A DPIA focuses on privacy risks; a FRIA looks more broadly at all fundamental rights when a high-risk AI system is deployed. From December 2027, a FRIA will be mandatory for, among others, public-sector organisations planning to use certain high-risk systems.
Your legal adviser can assess what applies to you; see also the AI Act.
The AP describes a DPIA not as a one-off task but as a continuous process. Changes to the processing, the risks or the context require a new DPIA. In AI, this could mean a new model, new training data or a different use of the output.
That is why we link model version control and monitoring to the DPIA through MLOps. We also work with LUMC on monitoring and maintenance in this way.
The AP says you must then consult the AP before starting the processing. This is called prior consultation. For each high residual risk, describe the circumstances in which it arises, how likely it remains despite your measures and what harm people could suffer.
You can read about who makes which AI decisions under AI governance. We describe an AI management system under ISO 42001.
If the AI application does not process personal data, or if you have purchased software and the supplier provides the technical information your DPO requests. In those cases, your organisation’s existing DPIA process is sufficient.
If the algorithms must also be described publicly, read our page on the Algorithm Register.
Governance, roles or the register: what else do you need to arrange alongside a DPIA?
- Data governanceOwnership, definitions, access and agreements about data: the foundation of every DPIA.
- AI governanceWho makes decisions, who checks and who remains responsible for AI in your organisation.
- Algorithm registerDescribe government algorithms clearly, publish them and keep their records up to date.