Term
Audit Trail (ˈɔːdɪt treɪl)
Definition
An Audit Trail is a detailed record that tracks all interactions, decisions, and changes made within an AI system. It is used primarily for monitoring purposes and to ensure compliance with rules and security practices.
Where you’ll find it
You can typically find the Audit Trail within the settings or administration section of your AI platform’s interface. Access and specific location might vary depending on the AI system you are using.
Common use cases
- Monitoring User Activities: This helps track who did what within the AI system, providing a clear timeline of user actions.
- Compliance and Reporting: It is essential for proving that the system meets regulatory requirements by preserving a history of all decisions and actions.
- Security Analysis: This is useful for investigating suspicious activities or discrepancies within the system.
Things to watch out for
- Data Overload: Audit Trails can generate a lot of data, which can be overwhelming and difficult to manage without proper tools.
- Privacy Issues: Since Audit Trails track all user activities, sensitive information might be recorded, necessitating strict access controls.
- System Performance: Keeping an extensive Audit Trail may impact the performance of your AI system; regular maintenance and optimization are advised.
Related terms
- AI System
- Compliance
- User Permissions
- Data Integrity
- Security Protocols
Pixelhaze Tip: To keep the Audit Trail manageable, regularly review and clean up older or irrelevant entries. This helps maintain system performance and ensures that the data remains relevant and easier to analyze when needed.