Isaca Updated AAISM Exam Questions and Answers by alessio

AAISM directs personnel to use established AI governance channels for suspected privacy, ethics, or compliance risks. The governance panel (risk, privacy, legal/compliance, security, product/data science) is chartered to triage, record, investigate, and direct remediation for potential inference of sensitive attributes and resulting decision impacts. Direct technical action (A or C) bypasses due process and accountability; escalating directly to a single executive (B) lacks the structured, cross-functional oversight required for regulated and ethical AI risk handling.

Hidden triggers are adversarial backdoors planted in AI models, activated only by specific inputs. The AAISM materials specify that the best mitigation is to use adversarial training, which deliberately exposes the model to potential trigger inputs during training so it can learn to neutralize or resist them. Retraining with diverse data reduces bias but does not address hidden triggers. Differential privacy is focused on privacy preservation, not adversarial resilience. Monitoring outputs can help with detection but is reactive rather than preventative. The proactive solution highlighted in the study guide is adversarial training.

AAISM categorizes unbounded consumption (also known as “resource exhaustion” or “infinite queries”) as an AI-specific vulnerability where attackers (or faulty prompts) trigger excessive computation, leading to high costs and degraded service.

This aligns precisely with unexpected large compute bills.

Excessive agency (A) refers to unsafe autonomy, while disclosure (B) and prompt leakage (D) do not relate to compute overuse.

AAISM identifies robust data validation and anomaly detection on incoming training data as the primary defense against data poisoning. These controls detect corrupted, manipulated, or adversarial samples before they enter the training pipeline.

Diverse data (A) is helpful but not protective against poisoning. More complexity (B) does not mitigate poisoning and can worsen vulnerability. More features (D) increases attack surface.