If a system influenced the decision, you need a record.

Agencies have decades of experience maintaining chains of custody for evidence. But AI introduces a new type of record: digital outputs that shape decisions in real time. Whether it’s a flag, score, alert, or suggestion, that output becomes part of the operational and legal trail.

If your agency doesn’t log those interactions, you’re exposed.

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Why AI Logs Matter

1. They’re legally discoverable

If a case goes to trial, and AI influenced the process—even indirectly—you may be required to produce logs. No logs = no defense.

2. They show operational integrity

Command staff need visibility into how often systems are used, who’s reviewing them, and whether staff are following policy. Logs are the only way to confirm that.

3. They help identify bias, misuse, or drift

If an AI tool starts generating inconsistent or problematic results, you need a trail to audit. Logs let you see what changed and when.

What Should Be Logged

• System access: Who used the system, when, and in what context
• Output data: What the system produced—e.g., a classification, recommendation, or alert
• Human action: What the staff member did with that output (accepted, rejected, escalated)
• Overrides and exceptions: Any case where a system output was bypassed, challenged, or failed

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