Data & Privacy
8 resources in this section
Agentic AI — Autonomous AI Systems and Governance Implications
Definición técnica What is Agentic AI? Agentic AI refers to AI systems that can plan, make decisions, and execute sequences of actions autonomously to achieve specified goals, without…
Data Governance — Foundation of Trustworthy AI Systems
Definición técnica Data governance is the organizational framework of policies, processes, standards, roles, and controls that determines how data is collected, stored, managed, used, shared, and retired across…
Data Lineage — Provenance and Traceability for AI Training Data
Definición técnica Data lineage in AI systems refers to the documented record of where data originates, how it has been transformed, what processes have been applied to it,…
Data Minimization — Necessary Data Principle for AI Systems
Definición técnica Data minimization is the data protection principle, enshrined in GDPR Article 5(1)(c), that personal data must be adequate, relevant, and limited to what is necessary in…
Data Poisoning — Adversarial Attack on AI Training Data
Definición técnica Data poisoning is an adversarial attack on AI systems in which an attacker manipulates the training data to cause the model to learn incorrect patterns, produce…
Large Language Model (LLM) — Governance and Regulatory Obligations
Definición técnica A Large Language Model (LLM) is a type of deep learning AI model trained on large-scale text corpora to understand, generate, and transform natural language. LLMs…
Privacy by Design — Integrating Data Protection into AI Systems
Definición técnica Privacy by Design (PbD) is the principle and practice of integrating data protection and privacy considerations into the design of systems, processes, and products from the…
Pseudonymization — Privacy Protection Technique for AI Training Data
Definición técnica Pseudonymization is a data processing technique defined in GDPR Article 4(5) as the processing of personal data in such a way that it can no longer…
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