Anonymisation
AIGP glossary · Last reviewed: · By Victor Humenhuk (AIGP certified)
Anonymisation - Removing items that could identify individuals, such as names and addresses; complete anonymisation is difficult.
In the AIGP body of knowledge, Anonymisation comes up under Module 5: Existing Laws & AI · BoK III.A; Module 6: Governing AI Development · BoK III.B.
Anonymisation in context
- Three provisions intersect most with AI: ==Article 22== (automated decisions), ==Article 35== (DPIAs) and ==Recital 26== (anonymisation). (The GDPR and AI)
- Recital 26 territory: ==anonymisation removes data from the GDPR entirely==, while ==pseudonymisation is still personal information== so GDPR obligations apply. (Anonymisation, Pseudonymisation and PETs)
- Five considerations turn raw data into model-ready data without trampling privacy: cleansing, labelling, anonymisation and minimisation. (Wrangling the Data)
Where Anonymisation is covered in the AIGP study notes
Related terms
- Pseudonymisation
- Scraping problem
- Differential privacy
- Homomorphic encryption
- Secure multi-party computation
- Data cleansing
- Data labelling
- Purpose specification & minimisation
- Federated learning
Test yourself on Anonymisation
Recognising a definition is not the same as applying it in an exam scenario. Work through the free AIGP practice questions, or read the full AIGP study guide - every study note is free.