AI Decision Logging
What AI decision logging is, why it matters for EU AI Act Article 12 compliance, and how to implement tamper-evident decision logs for high-risk AI systems.
AI decision logging is the practice of recording AI system decisions — and the contextual inputs, model version, and parameters that produced them — in a structured, auditable log.
Decision logs serve as the foundational audit trail for AI governance: they enable incident investigation, regulatory review, bias audits, model drift detection, and post-hoc accountability.
EU AI Act Article 12 mandates automatic logging of events during the operation of high-risk AI systems. Logs must be retained and made available to market surveillance authorities upon request.
What Should a Decision Log Contain?
A complete AI decision log entry should include: timestamp, input features (or input hash for privacy), model identifier and version, decision output, confidence score or probability distribution, operator identifier, and any override or human review actions taken.
CertifiedData.io provides cryptographic certification infrastructure for synthetic datasets and AI artifacts, producing tamper-evident records for audit and EU AI Act compliance.
Tamper-Evident Logging
Regulatory-grade decision logs should be tamper-evident: each log entry should be cryptographically linked to previous entries (via chaining hashes), and the log store should be write-protected against modification. This ensures logs cannot be retrospectively altered to conceal adverse decisions.
EU AI Act Article 12 Requirements
Article 12 requires that high-risk AI systems automatically log events that enable traceability of outputs throughout the system's lifetime. Logs must be retained for at least six months after first use and must be accessible to the provider and, where applicable, to notified bodies and market surveillance authorities.
Open Standard: AI Decision Logging Specification
An open specification for tamper-evident AI decision logs is available at github.com/synthetic-data-news/ai-decision-logging-spec. It defines required fields, SHA-256 hash chaining rules, Ed25519 signature support, and audit trail export formats aligned to EU AI Act Articles 12 and 19. The specification is implementation-agnostic and freely available for any organization to adopt.