What is the purpose of maintaining traceability in AI governance?

• A. To ensure auditability and accountability
• B. To reduce logs
• C. To complicate compliance
• D. To hide decisions

Answer: (A)

Maintaining traceability in AI governance is about creating an auditable record of how the system operates, including what data was used, which models and versions were involved, and why a particular decision was made. This transparency allows reviews to verify compliance, hold the right people or processes accountable, and reproduce results if needed. With a clear traceability trail, regulators and stakeholders can see the data lineage, model changes, inputs, outputs, and the reasoning that led to outcomes, which supports risk management and incident investigation.

So the purpose is to ensure auditability and accountability. Reducing logs, complicating compliance, or hiding decisions would undermine governance, not support it.