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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q186-Q191):

NEW QUESTION # 186
To maintain fairness in a deployed system, it is most important to:

Answer: A

Explanation:
Monitoring for data drift is critical to maintain fairness, as shifts in data over time can degrade model performance and introduce bias.


NEW QUESTION # 187
CASE STUDY
A company is considering the procurement of an AI system designed to enhance the security of IT infrastructure. The AI system analyzes how users type on their laptops, including typing speed, rhythm and pressure, to create a unique user profile. This data is then used to authenticate users and ensure that only authorized personnel can access sensitive resources.
All of the following are obligations of the company as a data controller when implementing its AI system EXCEPT?

Answer: A

Explanation:
The correct answer is A. While location of processors may have implications (such as for data transfers under GDPR), there is no absolute requirement that third-party processors be based in the same country.
From the AI Governance in Practice Report 2024 and ILT Guide:
"Data controllers are responsible for ensuring that third-party processors have adequate protections, but not necessarily that they reside in the same jurisdiction. What is required is legal safeguards (e.g., SCCs) for international transfers, not same-country location." In contrast, DPIAs, DSARs, and implementation of technical/organizational safeguards are explicitly required under GDPR and responsible AI frameworks.


NEW QUESTION # 188
What is the best reason for a company to adopt a policy that prohibits the use of generative AI?

Answer: B

Explanation:
The correct answer is D because one of the most significant risks associated with generative AI is the potential leakage of sensitive, confidential, or proprietary information. AI governance frameworks emphasize data protection, confidentiality, and secure data handling as critical organizational responsibilities. When employees input sensitive data into generative AI tools, especially external or third-party systems, that information may be stored, reused, or exposed unintentionally. This creates legal, regulatory, and reputational risks. As a result, organizations may restrict or prohibit generative AI use to prevent unauthorized data disclosure. The other options relate to operational or business considerations, which are not primary governance drivers. Protecting sensitive information aligns with core AI governance principles such as privacy, security, and risk mitigation, making it the strongest justification for such a policy.


NEW QUESTION # 189
Which of the following is NOT a common type of machine learning?

Answer: A

Explanation:
The common types of machine learning include supervised learning, unsupervised learning, reinforcement learning, and deep learning. Cognitive learning is not a type of machine learning; rather, it is a term often associated with the broader field of cognitive science and psychology. Reference: AIGP BODY OF KNOWLEDGE and standard AI/ML literature.


NEW QUESTION # 190
Which of the following deployments of generative AI best respects intellectual property rights?

Answer: B

Explanation:
Categorizing and filtering content based on licensing respects intellectual property rights by ensuring proper use according to license terms.


NEW QUESTION # 191
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