"Change description and justification" in audit trails means that AI/ML models document:

1. _Reasons for changes_: Explanations for why changes were made, including bug fixes, new features, or performance improvements.

2. _Description of changes_: Detailed descriptions of what was changed, including specific code updates or model modifications.

3. _Impact analysis_: Assessments of how changes may impact the model's behavior, performance, or accuracy.

4. _Rationale for decisions_: Explanations for why specific decisions were made, including trade-offs and considerations.

5. _Context for changes_: Relevant context, such as related issues, bug reports, or user feedback.

6. _Change requests and approvals_: Documentation of change requests, approvals, and reviews.

7. _Model version updates_: Updates to model versions, including changes to dependencies or libraries.

8. _Knowledge sharing and collaboration_: Sharing of knowledge and collaboration among team members, including comments and discussions.

By including change descriptions and justifications in audit trails, AI/ML models can:

- Provide transparency and accountability

- Support knowledge sharing and collaboration

- Facilitate error analysis and debugging

- Enable continuous improvement and learning

- Support compliance and regulatory adherence