Back to the MIT repository
7. AI System Safety, Failures, & Limitations1 - Pre-deployment

Insufficient AI development documentation

Throughout the development of an AI system, it is vital to document every decision and action taken. This is not only essential to optimize the development process itself but also required for the auditability of the AI system.

Source: MIT AI Risk Repositorymit997

ENTITY

1 - Human

INTENT

3 - Other

TIMING

1 - Pre-deployment

Risk ID

mit997

Domain lineage

7. AI System Safety, Failures, & Limitations

375 mapped risks

7.4 > Lack of transparency or interpretability

Mitigation strategy

1. Implement a comprehensive, mandated AI Development Documentation Framework that spans the entire model lifecycle, explicitly requiring the recording of all design decisions, model architecture, and system-specific parameters to ensure complete process traceability. 2. Establish a rigorous process for maintaining an immutable audit trail of key artifacts, including training data sources, data preprocessing steps, and model performance metrics, thereby guaranteeing the evidence chain necessary for independent auditability and regulatory compliance. 3. Integrate mandatory documentation checkpoints and standards into the organizational AI Governance structure, enforcing compliance through regular, independent audits to verify the accuracy, accessibility, and completeness of all required development and operational records.