Develop an AI that complies with the GDPR? Strategies and advice from the CNIL

1. GDPR and AI, a dynamic duo

The marriage between GDPR and AI is often seen as tumultuous. However, far from stifling innovation, the GDPR seeks to frame it so that technological progress is in harmony with people's rights. The CNIL demystifies the idea that the RGPD would be a brake on innovation in artificial intelligence in Europe. Rather, she points out that the real challenge lies in the use of “personal data”, those fragments of information about real individuals that, if mismanaged, can invade privacy.

The aim is therefore to navigate the ocean of AI while staying focused on data protection, thus ensuring that AI systems develop. with respect for everyone's rights and freedoms.

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2. The recommendations of the CNIL: a roadmap for responsible AI

Faced with questions from designers and developers of AI on the concrete application of the RGPD, the CNIL is positioning itself as a beacon in the regulatory fog. Its recommendations offer a precise framework for the development of AI systems that process personal data. This framework applies both to systems based on machine learning What for multi-purpose systems (general purpose AI), whether they learn on an ad hoc or continuous basis.

By wanting to be complementary to the new European regulation on AI, these recommendations aim to ensure regulatory coherence, thus allowing professionals to navigate confidently between data protection requirements and innovative ambitions.

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3. The importance of clear goals

For any AI project, defining a clear objective is the essential starting point. It's not just a question of direction; it's a requirement to limit the use of personal data to what's strictly necessary.

The CNIL insists on the fact that each AI system using personal data must be developed for a specific purpose. Whether the operational use of the system has already been determined or whether the system is intended for multiple applications, the purpose guides the collection and processing of data.

This approach helps to frame the use of data from the design stage, ensuring that system development remains true to the principles of the GDPR while exploring the vast possibilities offered by AI.

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4. Navigating responsibilities: who does what?

In the vast ocean of AI, figuring out who is in control is crucial. The CNIL clarifies the distinction between the roles of “data controller” And of “subcontractor”, essential for navigating the regulatory waters of the GDPR.

In short:

• If you decide why and how personal data is processed, you are the captain of the ship, i.e. the data controller.
• If you act on instructions from a third party, you are instead in the role of the crew, acting as a subcontractor.

This distinction directly influences how GDPR obligations should be implemented, ensuring that each entity plays its part with due diligence to protect personal data.

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5. The legal basis for data processing

For the AI journey in compliance with the GDPR to be smooth, choosing a solid legal basis for the processing of personal data is essential. It's a bit like selecting the right sail to navigate according to the wind: that determines the legitimacy and security of your journey.

Consent, contract, legitimate interest... Each legal basis offers a different framework for data processing. The CNIL encourages in-depth reflection to ensure that the chosen base is perfectly aligned with the specificities of the AI project, thus guaranteeing harmony between the exploitation of data and the respect of the rights of individuals.

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6. The art of minimization: using just what you need

In the world of AI, less can often mean more. Data minimization, a principle dear to the GDPR, is a compass that guides us to the essentials: collecting only the data strictly necessary for the objective pursued. This approach eliminates the superfluous, focusing efforts on what is truly useful and relevant for system development.

In practice, this means sharpen your discernment to distinguish essential data from accessories, an approach that, far from limiting the power of AI, makes it more respectful of individuals and therefore more sustainable.

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7. Define a shelf life

Just as every story comes to an end, personal data should not be retained indefinitely. Setting a retention period is an exercise in balance between the usefulness of the data for the project and the respect of the privacy of the persons concerned.

The CNIL recalls that this duration must be justified by the purpose of the treatment and communicated transparently, thus ensuring that data does not remain in circulation beyond its necessity.

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8. In the Field: Conducting an Impact Assessment

Before setting sail, do a Data Protection Impact Assessment (AIPD) is like checking the weather and currents: it makes it possible to anticipate risks and to prepare the appropriate measures for safe browsing.

For AI projects, where the privacy implications can be complex and subtle, the AIPD is a valuable tool for mapping risks and defining strategies to mitigate them, ensuring that AI development is not only innovative but also respectful of fundamental rights.

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The recommendations of the CNIL for the development of AI systems in compliance with the RGPD chart a clear path to reconcile technological innovation and the protection of personal data. By setting specific goals, clarifying responsibilities, choosing the legal basis for data processing wisely, practicing minimization, determining an appropriate retention period, and conducting a rigorous impact analysis, AI designers can navigate to waters where innovation rhymes with respect for the individual. It is a demanding journey, but essential for building an ethical and responsible digital future.