EDPB guidelines on privacy protection in the AI ;;era
Opinion published on the use of personal data for AI models
How to ensure compliance with European
privacy rules in the development of artificial intelligence
models.
The long-awaited opinion of the European Data Protection Board
(EDPB) on the use of personal data for the dissemination of AI
models has arrived.
Requested by the Irish Data Protection Authority (DPA) and
drafted in consultation with the European AI Office, the opinion
examines the issue from three perspectives. That of anonymity,
first of all.
The EDPB clarifies that an AI model is to be considered
anonymous if it is very unlikely to directly or indirectly
identify the people whose data were used to create the model and
extract such personal data from the model through queries.
The opinion then delves into the issue of legitimate interest,
providing general considerations that data protection
authorities should take into account when assessing whether
legitimate interest is an appropriate legal basis for processing
personal data for the development and use of AI models.
A three-step test helps assess the use of legitimate interest as
a legal basis. The EDPB provides examples of a conversational
agent to assist users and the use of AI to improve
cybersecurity. These services can benefit individuals and can
rely on legitimate interest as a legal basis, but only if the
processing is shown to be strictly necessary and the balancing
of rights is respected.
The opinion also includes a set of criteria to help data
protection authorities assess whether individuals can reasonably
expect certain uses of their personal data. Among the criteria
identified, the possibility of personal data being publicly
available, the nature of the relationship between the individual
and the controller, the nature of the service, the context in
which the personal data was collected, the source from which it
was collected, and the potential further uses of the model.
Finally, if an AI model was developed with unlawfully processed
personal data, this could have an impact on the legitimacy of
its use, unless the model has been duly anonymized.
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