What do EU AI Act Articles 10 and 11 require, and why do they create tension with anonymization?

Article 10 demands high-quality training data; Article 11 demands full data lineage — both of which anonymization can undermine.

The AI Act adds obligations for AI systems that pull against privacy engineering:

• Article 10 — Data Quality: training, validation, and testing datasets must be relevant, representative, free of errors, and complete.
• Article 11 — Data Lineage: you must trace the full data journey, from source through every processing step to the final output.

The tension: anonymization deliberately modifies data. Generalizing ages into ranges or suppressing values can hurt representativeness (Art. 10) and, because it transforms records, can complicate lineage/traceability (Art. 11). A mature pipeline addresses this head-on by documenting the anonymization tactics, parameters, and versions as part of lineage — so privacy and governance coexist instead of colliding.

Go deeper:

• EU AI Act Article 10 — Data and data governance — the relevance/representativeness/error-free requirement.
• EU AI Act Article 11 — Technical documentation — the lineage/traceability obligation.