2025 Reliable AIGP: Valid IAPP Certified Artificial Intelligence Governance Professional Real Test
2025 Reliable AIGP: Valid IAPP Certified Artificial Intelligence Governance Professional Real Test
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Quiz IAPP - AIGP –High Hit-Rate Valid Real Test
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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q70-Q75):
NEW QUESTION # 70
Which of the following is a subcategory of Al and machine learning that uses labeled datasets to train algorithms?
- A. Supervised learning.
- B. Segmentation.
- C. Generative Al.
- D. Expert systems.
Answer: A
Explanation:
Supervised learning is a subcategory of AI and machine learning where labeled datasets are used to train algorithms. This process involves feeding the algorithm a dataset where the input-output pairs are known, allowing the algorithm to learn and make predictions or decisions based on new, unseen data. Reference:
AIGP BODY OF KNOWLEDGE, which describes supervised learning as a model trained on labeled data (e.g., text recognition, detecting spam in emails).
NEW QUESTION # 71
What is the most important reason to document the results of AI testing?
- A. To support post-deployment maintenance.
- B. To create a verifiable audit trail.
- C. To identify areas for red-teaming focus.
- D. To limit the need for future testing cycles.
Answer: B
Explanation:
Testing results need to bedocumented thoroughlyto ensuretraceability, accountability, and compliance.
This is central to enabling audits, investigations, or regulatory inquiries into the system's development and performance.
From theAI Governance in Practice Report 2024:
"Documentation and recordkeeping are essential components... to demonstrate AI system compliance, trace system behavior, and support audits and conformity assessments." (p. 34-35)
"Maintaining audit trails across development and deployment enables transparency and accountability." (p.
12)
* AandBare benefits, but not theprimary governance justification.
* D- Limiting future testing is not a recommended goal.
NEW QUESTION # 72
CASE STUDY
A global marketing agency is adapting a large language model ("LLM") to generate content for an upcoming marketing campaign for a client's new product: a hard hat designed for construction workers of any gender to better protect them from head injuries.
The marketing agency is accessing the LLM through an application programming interface ("API") developed by a third-party technology company. They want to generate text to be used for targeted advertising communications that highlight the benefits of the hard hat to potential purchasers. Both the marketing agency and the technology company have taken reasonable steps to address Al governance.
The marketing company has:
* Entered into a contract with the technology company with suitable representations and warranties.
* Completed an impact assessment on the LLM for this intended use.
* Built technical guidance on how to measure and mitigate bias in the LLM.
* Enabled technical aspects of transparency, explainability, robustness and privacy.
* Followed applicable regulatory requirements.
* Created specific legal statements and disclosures regarding the use of the Al on its client's advertising.
The technology company has:
* Provided guidance and resources to developers to address environmental concerns.
* Build technical guidance on how to measure and mitigate bias in the LLM.
* Provided tools and resources to measure bias specific to the LLM.
* Enabled technical aspects of transparency, explainability, robustness and privacy.
* Mapped and mitigated potential societal harms and large-scale impacts.
* Followed applicable regulatory requirements and industry standards.
* Created specific legal statements and disclosures regarding the LLM. including with respect to IP and rights to data.
The technology company has also addressed environmental concerns and societal harms.
Which of the following results would be considered biased outputs from this AI system EXCEPT?
- A. The generated ads are sent to construction companies, not individual workers
- B. The advertising text generated for female audiences focuses on color and style
- C. The images of female workers are hyper-sexualized
- D. The content generated for minority construction workers is insufficient
Answer: A
Explanation:
The correct answer is A. Sending ads to construction companies (business entities) rather than individual workers is a business targeting decision, not inherently a biased AI output.
From the AIGP ILT Participant Guide - Bias & Fairness Module:
"Biased outputs often include stereotyping, exclusion of underrepresented groups, or reinforcing harmful societal assumptions." Examples like insufficient representation of minority groups or gender-stereotyping in visuals or language are typical manifestations of bias.
AI Governance in Practice Report 2024 also notes:
"Bias in generative models may manifest in representation gaps, stereotyping, or unequal performance across demographic groups." Option A, by contrast, describes a distribution strategy, not a bias generated by the AI model.
NEW QUESTION # 73
A company deploys an AI model for fraud detection in online transactions. During its operation, the model begins to exhibit high rates of false positives, flagging legitimate transactions as fraudulent.
Which is the best step the company should take to address this development?
- A. Maintain records of all false positives.
- B. Conduct training for customer service teams to handle flagged transactions.
- C. Dedicate more resources to monitor the model.
- D. Deactivate the model until an assessment is made.
Answer: D
Explanation:
When an AI system causessignificant false positives, especially in sensitive contexts likefraud detection, the priority is tohalt harmful activityand perform a full assessment. Continued use without understanding the fault may cause furthercustomer harmand legal exposure.
From theAI Governance in Practice Report 2024:
"Incident management plans should enable identification, escalation, and system rollback to prevent continued harm from malfunctioning AI systems." (p. 12, 35)
NEW QUESTION # 74
Which of the following use cases would be best served by a non-AI solution?
- A. A non-profit wants to develop a social media presence.
OB. An e-commerce provider wants to make personalized recommendations. - B. A business analyst wants to forecast future cost overruns and underruns.
- C. A customer service agency wants automate answers to common questions.
Answer: A
Explanation:
Developing a social media presence for a non-profit is best served by non-AI solutions. This task primarily involves content creation, community engagement, and strategic planning, which are effectively managed by human expertise and traditional marketing tools. AI is more suitable for tasks requiring automation, large-scale data analysis, and personalized recommendations, such as e-commerce personalization, forecasting cost overruns, or automating customer service responses. Reference: AIGP Body of Knowledge on AI Use Cases and Applications.
NEW QUESTION # 75
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