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| Section | Objectives |
|---|---|
| AI Governance Implementation | - Data Governance for AI
|
| AI Governance Management | - Emerging Issues
|
| AI Laws, Regulations, and Standards | - Global AI Frameworks
|
| AI Risk Management | - Risk Frameworks and Standards
|
| Foundations of AI Governance | - Impacts of AI
|
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NEW QUESTION # 137
In 2025, which U.S. agency ordered companies to provide information about the safety of their AI companion chatbots?
Answer: B
Explanation:
The correct answer is C, the Federal Trade Commission. The FTC plays a central role in U.S. AI governance by enforcing consumer protection and unfair or deceptive practices laws. In the context of AI systems such as companion chatbots, the FTC has authority to investigate risks related to user harm, transparency, safety, and misleading claims. AI governance frameworks emphasize regulatory oversight where AI systems may impact individuals psychologically, financially, or socially. Agencies like the FTC focus on ensuring that companies deploying AI systems do not cause harm through unsafe or deceptive practices and that they provide adequate disclosures about risks and system behavior. This aligns with broader AI governance principles of accountability, transparency, and risk management highlighted in the AI Governance in Practice Report 2024
, which stresses the importance of regulatory involvement in managing AI-related risks.
NEW QUESTION # 138
All of the following are potential benefits of using private over public LLMs EXCEPT?
Answer: B
Explanation:
Private LLMs offer advantages likecustomizability,reduced hallucination,confidentiality, andalignment with enterprise-specific tasks, but theydo not inherently reduce the time or effortneeded fordata validation or verification- which remains an essential step regardless of model privacy.
From the AI risk and quality sections:
"Ensuring the quality of the data... is highly contextual and must be validated regardless of the model's deployment environment." (p. 17)
* B, C, Dare legitimate benefits of private LLMs.
* Ais incorrect - validation still requires time and resources.
NEW QUESTION # 139
CASE STUDY
Please use the following to answer the next question:
You have recently assumed the role of AI Governance leader for a California-based medical technology company. The organization primarily serves hospitals and has recently expanded to include walk-in clinics located within local pharmacies.
The company ' s core business focuses on diagnostic assistance powered by a large language model LLM and back-office process optimization using Agentic AI, including chatbots, medical record request handling, scheduling and billing.
In preparation for its next round of funding, the board has asked you to prepare an AI Risk report to demonstrate to investors how the company is addressing AI-related risks. In preparing the report you learn that last year the company generated 30 million dollars in gross revenue across the US, EU, India, and South Korea and that vendors are engaged for various activities, including model testing and providing third-party AI solutions for chatbots.
Which of the following would provide you the best information addressing quality principles pertaining to the functioning of the AI agents and LLM?
Answer: B
Explanation:
The correct answer is D because it directly reflects core data and model quality principles such as accuracy, performance consistency, and real-world effectiveness across different user groups. AI governance frameworks emphasize that quality must be evaluated based on whether outputs are accurate, complete, and fit for purpose in real-world conditions. Measuring accuracy by user group also supports fairness and bias detection, which are essential components of trustworthy AI. Option D captures outcome-based performance and aligns with continuous monitoring expectations across the AI lifecycle. In contrast, options A and C focus more on operational or technical metrics, while B reflects user sentiment rather than objective quality.
According to AI governance principles, high-quality AI systems require ongoing evaluation of outputs against real-world results to ensure reliability, validity, and safe deployment.
NEW QUESTION # 140
Which of the following best defines an "Al model"?
Answer: A
Explanation:
An AI model is best defined as a program that has been trained on a set of data to find patterns within that data. This definition captures the essence of machine learning, where the model learns from the data to make predictions or decisions. Reference: AIGP BODY OF KNOWLEDGE, which provides a detailed explanation of AI models and their training processes.
NEW QUESTION # 141
The benefit of having a clear process for handling AI-related incidents is that it reduces?
Answer: D
Explanation:
The correct answer is A because having a well-defined incident management process enables organizations to respond quickly and effectively when AI-related issues arise. AI governance frameworks emphasize incident management plans as a key component of operational governance, ensuring that risks such as system failures, harmful outputs, or security breaches are promptly identified, escalated, and resolved. A structured process reduces delays by clearly defining roles, responsibilities, and response procedures, thereby minimizing potential harm and operational disruption. While incident processes may also indirectly support compliance and reduce the impact of failures, their primary benefit is improving responsiveness and coordination.
Efficient response times are critical in maintaining trust, ensuring safety, and limiting negative consequences in real-world AI deployments.
NEW QUESTION # 142
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