Technical

Audit Trail

Immutable logs of inputs, prompts, outputs and system versions.

How the laws define this

Both instruments agree that an audit trail is a tamper-evident record essential for enabling audits and accountability. Where they diverge is in the scope of the system activities that must be logged. Under the Resolución de Presidencia 206/2025 – Guía de Recomendaciones y Directrices para el Uso de Sistemas de Inteligencia Artificial en el Poder Judicial de la Ciudad Autónoma de Buenos Aires, audit trails focus on operational interactions, capturing inputs, prompts, system responses, model versions, and relevant metadata to enable the reconstruction, review, challenge, and independent auditing of AI-assisted processes. In contrast, the AI and Data Protection Regulation Bill mandates comprehensive coverage across the entire AI system lifecycle, requiring records of development and governance events—such as dataset versions, training runs, model updates, testing results, and deployment decisions—alongside decision outputs to support regulatory compliance investigations.

Synthesised from the 2 statutory definitions below. Each one is quoted in full, with its source.

Definitions (2)

A secure, tamper-evident record containing inputs, prompts, system responses, model versions and relevant metadata to enable reconstruction, auditing and accountability of AI-assisted processes. The Guide requires maintenance of audit trails to support review, challenge, and independent audits of systems used operationally.

Comprehensive, tamper-evident records capturing key events across an AI system's lifecycle — including dataset versions, training runs, model updates, testing results, deployment decisions, and decision outputs — to enable audits, accountability, and regulatory compliance investigations.