Your guide to navigating AI, ethics, and regulation—one term at a time.
Essential concepts at the intersection of AI and data protection
Making decisions solely by automated means without human involvement
Automated processing of personal data to evaluate aspects about an individual
Right to obtain explanation of decisions made by AI systems
Limiting data collection to what's necessary for specified purposes
Making AI algorithms understandable and their decisions explainable
Assessment of risks to rights and freedoms posed by data processing
Building data protection into the design of AI systems
Ensuring the highest privacy settings by default
AI systems designed to be understandable by humans
Processing data only for specified, explicit, and legitimate purposes
AI systems posing significant risks to rights and freedoms
Human supervision and intervention in AI systems
Unfair treatment resulting from AI system prejudices
Ensuring AI systems treat individuals equitably
Ensuring data is accurate, complete, and representative
Artificially generated data that mimics real data
Training AI models across devices while keeping data local
Methods to protect privacy while enabling data analysis
Mathematical framework for privacy-preserving data analysis
Attacks that extract training data from AI models
Determining if data was used to train an AI model
Responsibility for and demonstration of GDPR compliance
Framework for responsible AI development and deployment
Records of AI system design, operation, and compliance
Evaluation of AI system impacts beyond data protection
Integrating ethical considerations into AI development
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This tool is for informational purposes only and does not constitute legal advice.