1. Transparency and Explainability
• Ensuring traceability by building an audit trail to document the AI system development and decisionmaking process, implementing a black box recorder that captures all input data streams, or storing data appropriately to avoid degradation and alteration.
1. Transparency and Explainability
• Facilitating auditability by keeping a comprehensive record of data provenance, procurement, preprocessing, lineage, storage, and security.
1. Transparency and Explainability
Deployers should, however, note that auditability does not necessarily entail making certain confidential information about business models or intellectual property related to the AI system publicly available.
1. Transparency and Explainability
A risk based approach can be taken towards identifying the subset of AI enabled features in the AI system for which implemented auditability is necessary to align with regulatory requirements or industry practices.