The AEPD's approach to AI: Smarter models, better compliance

By virtue of the privacy-by-design principle — a key premise of the EU General Data Protection Regulation — any new initiative within a company that involves personal data must incorporate privacy protections throughout the entire engineering life cycle, from initial design to final deployment.

With increasing AI expansion across all industries, ensuring such technology is developed under the privacy-by-design approach is crucial for safeguarding individual rights while leveraging the remarkable benefits it can offer.

Building on this premise, Spain's data protection authority, the Agencia Española de Protección de Datos, recently published an article questioning the common belief that more complex AI models are inherently superior. Instead, the AEPD demonstrates that well-designed, streamlined AI systems can not only strengthen compliance with data protection laws, but also deliver better outcomes, underscoring the importance of thoughtful, privacy-focused development.

A surprising experiment: One neuron vs. many

The AEPD suggests developing two different AI models — a single-neuron network and a multi-neuron network — to determine, as an example, whether someone is overweight using only height and weight. Comparing their results highlights how the choice of model can significantly impact both AI accuracy and compliance with GDPR principles.

A single-neuron model takes a straightforward approach, processing height and weight through a simple formula, then classifying individuals as either "overweight" or "not overweight." Surprisingly, even a small training set of just three samples can be enough for this model to generalize across different height-weight scenarios.