An organization wants to create an AI audit trail that satisfies regulatory requirements. Which data should be captured at minimum in the audit log for each AI decision?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — b is correct because a minimum viable AI audit trail must capture: what information was used (inputs), which model produced the output (version), what decision was made (output), when it occurred (timestamp), and accountability (human or AI decision-maker). This enables traceability, reproducibility, and accountability review.
Full explanation below image
Full Explanation
B is correct because a minimum viable AI audit trail must capture: what information was used (inputs), which model produced the output (version), what decision was made (output), when it occurred (timestamp), and accountability (human or AI decision-maker). This enables traceability, reproducibility, and accountability review. Source code and training data (A) are important documentation but not per-decision log requirements. Full probability distributions (C) are useful for some analyses but are not a minimum requirement. Personnel identities (D) belong in governance records, not per-decision logs.