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| Section | Objectives |
|---|---|
| Topic 1: Ethics, Privacy, and Responsible AI | - Ethical AI principles and compliance
|
| Topic 2: AI Risk Management | - Risk identification and assessment for AI systems
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| Topic 3: AI Lifecycle Controls | - Controls across AI development lifecycle
|
| Topic 4: Regulatory and Compliance Requirements | - Global AI regulatory landscape
|
| Topic 5: AI Governance and Strategy | - AI governance frameworks and organizational oversight
|
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NEW QUESTION # 114
A risk practitioner learns that a credit-scoring AI system is exhibiting bias that cannot be eliminated through further training. Which of the following is the risk practitioner's BEST recommendation?
Answer: C
Explanation:
Credit scoring AI systems are subject to anti-discrimination regulations that prohibit using models that produce biased outcomes affecting protected classes. When bias cannot be eliminated through technical means, continuing to operate the system creates ongoing legal violations and harm to affected individuals.
Why B is Correct: According to ISACA AAIR risk treatment guidance and legal compliance obligations, removing a biased credit-scoring system from production is the appropriate response when bias cannot be technically remediated. Continuing to operate a system known to produce discriminatory credit decisions violates anti-discrimination laws (such as the Equal Credit Opportunity Act), exposes the organization to regulatory enforcement, and causes ongoing harm to affected borrowers. Risk avoidance through system withdrawal is the appropriate treatment when the risk cannot be adequately mitigated.
Why A is Wrong: Requesting senior management risk acceptance for confirmed legal violations is inappropriate because organizations cannot accept risks involving known regulatory breaches. Senior management cannot legitimately authorize continued discriminatory lending practices.
Why C is Wrong: Sourcing a replacement system is a necessary future action but takes time to procure, validate, and deploy. In the interim, the biased system should not continue operating. Removing the system from production should precede replacement planning.
Why D is Wrong: Applying compensating controls to generate offsetting biases compounds the discriminatory problem rather than resolving it. Deliberately introducing additional bias-even in the opposite direction-creates an unpredictably biased model that does not produce fair outcomes.
NEW QUESTION # 115
An organization is integrating AI systems into core business operations and has decided to establish a formal process to align AI initiatives with corporate values. Which of the following is the GREATEST benefit of this decision?
Answer: A
Explanation:
Aligning AI initiatives with corporate values establishes ethical foundations that directly influence how models are designed, deployed, and governed. This alignment is most powerfully expressed through enhanced transparency and explainability of AI decisions.
Why D is Correct: The ISACA AAIR Study Guide identifies transparency and explainability as core benefits of value-aligned AI governance. When AI processes are formally anchored to corporate values, organizations build systems that can explain their decisions to regulators, customers, employees, and the public. This fosters trust, enables accountability, and supports compliance across all stakeholder groups-producing the most broadly impactful organizational benefit.
Why A is Wrong: This option suggests a sequential approach where ethics are retrofitted after deployment, which is actually a risk and poor practice. The formal alignment process prevents this problem rather than enabling it.
Why B is Wrong: ROI evaluation is a financial management function. While valuable, it is a narrow benefit compared to the enterprise-wide stakeholder value created by transparency and explainability.
Why C is Wrong: Obtaining executive support for training is an organizational change management benefit.
While useful, it is a means to an end rather than the primary organizational benefit of value alignment.
NEW QUESTION # 116
An organization is integrating AI systems into core business operations and has decided to establish a formal process to align AI initiatives with corporate values. Which of the following is the GREATEST benefit of this decision?
Answer: A
NEW QUESTION # 117
Which of the following is the MOST important vendor assurance measure when an organization plans to engage multiple AI vendors for critical model components?
Answer: A
Explanation:
Within the ISACA Advanced in AI Risk framework, program management connects risk identification, control selection, treatment, monitoring, resilience, third-party oversight, and reporting to enterprise risk objectives. When multiple vendors provide critical model components, assurance depends on evidence of provenance and integrity so the organization can trace the origin and handling of data and artifacts. Tool mandates or centralized IT ownership do not establish trustworthiness. This makes option A, Verifying documentation of data provenance and integrity, the strongest answer. The other choices describe narrower technical, operational, performance, or administrative considerations and do not address the primary risk- management objective in the scenario as directly. A risk practitioner should select the response that most effectively reduces the stated exposure while preserving appropriate oversight, traceability, and alignment with organizational risk tolerance and business requirements.
NEW QUESTION # 118
An organization uses AI to generate procedure documents for operational processes. Which of the following would be of GREATEST concern to a risk practitioner?
Answer: A
Explanation:
AI-generated content-including operational procedures-can contain errors, omissions, hallucinations, and contextually inappropriate guidance. Human review is a critical quality control and accountability mechanism that ensures generated procedures are accurate, complete, and appropriate for actual operational use.
Why A is Correct: The ISACA AAIR guidance on human oversight identifies the absence of human review as the greatest risk in AI-generated documentation. Without review, errors and AI hallucinations are propagated directly into operational use, potentially causing safety incidents, compliance violations, or operational failures. Human review is the last line of defense against AI output quality failures, particularly in operational procedure contexts where incorrect instructions can have serious consequences.
Why B is Wrong: Outdated procedures are a content quality issue that would typically be caught during human review. The greater concern is that no review is occurring, which allows all types of errors-including outdated content-to reach operational use unchallenged.
Why C is Wrong: Policy misalignment is a governance concern but represents a specific type of error that would be identified if adequate human review were performed. The absence of review is the root governance failure.
Why D is Wrong: Using AI to generate procedures for high-risk activities is a deployment scope concern that raises the stakes of errors. However, the fundamental governance failure-and the greatest concern-is that no human verification occurs regardless of the risk level of the activity.
NEW QUESTION # 119
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