AIGP Dumps with Practice Exam Questions Answers

The most comprehensive way to identify a full range of risks — legal, ethical, operational, and societal — for a new AI model is through aformal impact assessment, such as aData Protection Impact Assessment (DPIA)orAlgorithmic Impact Assessment.

From theAI Governance in Practice Report 2025:

“Risk-based approaches are often distilled into organizational risk management efforts, which put impact assessments at the heart of deciding whether harm can be reduced.” (p. 29)

“DPIAs… help organizations identify, analyze and minimize data-related risks and demonstrate accountability.” (p. 30)

A. Environmental scanis too general.

B. Red teamingis useful for adversarial risk but not broad.

C. Integration testingfocuses on technical/system compatibility, not overall risk.

According to the GDPR, individuals have the right to not be subject to a decision based solely on automated processing, including profiling, which produces legal effects or similarly significantly affects them. However, there are exceptions to this right, one of which is when the decision is based on the data subject ' s explicit consent. This means that if an individual explicitly consents to the automated decision-making process, there is no requirement for human intervention to confirm or replace the decision. This exception ensures that individuals can have control over automated decisions that affect them, provided they have given clear and informed consent.

After completing model testing and validation, the most important step prior to deploying the model into production is to perform a readiness assessment. This assessment ensures that the model is fully prepared for deployment, addressing any potential issues related to infrastructure, performance, security, and compliance. It verifies that the model meets all necessary criteria for a successful launch. Other steps, such as defining a model-validation methodology, documenting maintenance teams and processes, and identifying known edge cases, are also important but come secondary to confirming overall readiness. Reference: AIGP Body of Knowledge on Deployment Readiness.

According to the EU AI Act, providers of high-risk AI systems are required to register with an EU oversight agency before these systems can be placed on the market. This requirement is part of the Act ' s framework to ensure that high-risk AI systems comply with stringent safety, transparency, and accountability standards. High-risk systems are those that pose significant risks to health, safety, or fundamental rights. Registration with oversight agencies helps facilitate ongoing monitoring and enforcement of compliance with the Act ' s provisions. Systems categorized under other criteria, such as those trained on sensitive personal data or exhibiting " strong " general intelligence, also fall under scrutiny but are primarily covered under different regulatory requirements or classifications.

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 de ceptive 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.