Glossary
Definitions of key concepts in synthetic data generation, AI governance, EU AI Act compliance, decision logging, and AI certification.
AI Governance
AI Governance Hub →AI Audit Trail
EN · FR · DE · ESAn AI audit trail is a structured record of events, decisions, model behavior, approvals, changes, and evidence related to an AI system over time.
AI Decision Logging
EN · FR · DE · ESAI decision logging is the structured recording of AI system decisions, inputs, outputs, actors, and system state so decisions can be traced, reviewed, and audited later.
AI Decision Traceability
EN · FR · DE · ESAI decision traceability is the ability to reconstruct how a specific AI-assisted decision was produced, including the inputs, system state, rules, model version, and human actions involved.
AI Governance Infrastructure
AI governance infrastructure is the combined technical, procedural, and evidentiary system used to document, monitor, certify, and audit AI systems and their outputs.
Training Data Provenance
Training data provenance is the documented origin, lineage, transformation history, and rights context of data used to train or fine-tune AI systems.
All Terms
Synthetic Data
Synthetic data is artificially generated data designed to replicate the statistical properties of real-world datasets while containing no actual personal records.
CTGAN
CTGAN (Conditional Tabular GAN) is a GAN-based machine learning model specifically designed to generate synthetic tabular data by modeling complex column distributions and dependencies.
Differential Privacy
Differential privacy is a mathematical privacy framework that limits the information any single individual's data contributes to a published dataset or model output, providing a formal, quantifiable privacy guarantee.
AI Governance
AI governance is the set of policies, processes, technical standards, and oversight mechanisms that organizations implement to ensure AI systems are developed, deployed, and monitored responsibly and in compliance with applicable laws and ethical standards.
Decision Logging
Decision logging is the practice of recording AI-assisted or automated decisions — including the inputs, model version, outputs, and contextual metadata — in a structured, tamper-evident log to enable audit, review, and regulatory compliance.
AI Audit Trail
An AI audit trail is a tamper-evident, chronological record of events in an AI system's operation — including model changes, data inputs, decision outputs, and configuration updates — sufficient to reconstruct what happened and why.
Model Risk Management
Model risk management (MRM) is the organizational framework for identifying, measuring, monitoring, and mitigating risks arising from the use of quantitative models — increasingly applied to machine learning and AI systems.
EU AI Act
The EU AI Act (Regulation (EU) 2024/1689) is the European Union's comprehensive legal framework for artificial intelligence, establishing risk-based obligations for AI developers, deployers, and importers operating in the EU market.
Synthetic Data Certification
Synthetic data certification is the process of cryptographically signing and formally documenting a synthetic dataset's generation parameters, statistical properties, and provenance to create a tamper-evident record suitable for audit and regulatory compliance.
Synthetic Data Governance
Synthetic data governance is the set of policies, controls, and documentation practices that organizations apply to synthetic datasets across their lifecycle — from generation through evaluation, certification, and retirement.
AI Artifact Verification
AI artifact verification is the process of confirming that a dataset, model, report, or output matches a recorded fingerprint or certification artifact using cryptographic techniques.
AI Data Lineage
AI data lineage is the documented record of how data assets flow through an AI system — from source through processing, training, evaluation, and model deployment.
Training Data Provenance
Training data provenance is the documented record of where a training dataset came from, how it was collected or generated, how it was validated, and whether it has changed since initial certification.
All Topics
Browse the full knowledge graph — pillar topics, cluster pages, and research coverage.
View Topic Index →