Ευαίσθητα δεδομένα και inferences - Η εφαρμογή του ΓΚΠΔ στην εποχή και στο πλαίσιο της μηχανικής μάθησης
Sensitive data and inferences - GDPR application in the era and context of machine learning

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Keywords
Γενικός Κανονισμός Προστασίας Δεδομένων ; Τεχνητή νοημοσύνη ; Πράξη για την Τεχνητή Νοημοσύνη ; Ευαίσθητα δεδομένα ; Ειδικές κατηγορίες προσωπικών δεδομένων ; Inferences ; Συμπερασματικές συναγωγέςAbstract
The increasing complexity of AI systems favors their ability to create inferences about individuals, often from seemingly "innocent" or non-sensitive data. The information generated may reveal sensitive characteristics, such as political beliefs or sexual orientation, raising legal and ethical issues regarding the protection of personal data, individual autonomy, and protection from discrimination. This thesis examines the legal nature of inferences and whether they fall within the concept of personal data as defined in the GDPR. It also assesses the protection provided by the current legal framework for personal data protection against the new risks and challenges posed by the use of AI and the creation of inferences, identifying relevant gaps and making relevant proposals to ensure maximum protection for individuals in the era and context of AI.


