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Customizable practice tests comprehensively and accurately represent the actual Professional IAPP AIGP Certification Exam pattern. Many students have studied from product and passed the IAPP Certified Artificial Intelligence Governance Professional (AIGP) test with ease. Our customers can receive questions updates for up to 1 year after purchasing the product. These free updates of questions will help them to prepare according to the latest syllabus.
| Certification Vendor: | IAPP (International Association of Privacy Professionals) |
|---|---|
| Exam Name: | IAPP Certified Artificial Intelligence Governance Professional Exam |
| Exam Number: | AIGP |
| Real Exam Qty: | 100 |
| Related Certifications: | CIPP CIPM CIPT |
| Exam Price: | USD 649 (members) / USD 799 (non-members) |
| Available Languages: | English |
| Exam Duration: | 165 (including 15-minute optional break) |
| Passing Score: | 300 (scaled score out of 500) |
| Certificate Validity Period: | 2 years |
| Exam Format: | Scenario-based, Multiple-choice |
| Recommended Training: | Official AIGP Body of Knowledge & Study Guide IAPP Training & Resources |
| Exam Registration: | IAPP Official Registration Pearson VUE Scheduling |
| Sample Questions: | IAPP AIGP Sample Questions |
| Exam Way: | Online remote proctored or in-person at Pearson VUE test centers |
| Pre Condition: | No formal prerequisites; open to all professionals |
| Official Syllabus URL: | https://iapp.org/certify/aigp |
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NEW QUESTION # 57
Scenario:
A public sector agency is reviewing proposed AI use cases for improving services. It wants to prioritize implementations that deliver value but minimize unintended negative consequences.
When evaluating which AI use cases to implement, an organization should consider all of the following EXCEPT:
Answer: B
Explanation:
The correct answer is A. While TEVV is important in later lifecycle phases, it is not the primary consideration when evaluating and prioritizing use cases.
From the AIGP Body of Knowledge - Use Case Assessment Module:
"Use case evaluation focuses on value, impact, fairness, and accessibility-technical testing considerations come later." ILT Guide confirms:
"Organizations should first assess whether the AI system provides equitable outcomes and aligns with stakeholder expectations. TEVV is part of implementation, not initial prioritization." Thus, A is not a top-level consideration during use case selection.
NEW QUESTION # 58
What is the most important reason for requiring collaboration among cross-functional stakeholder teams during the AI development lifecycle?
Answer: B
Explanation:
Collaboration among cross-functional teams ensures clear accountability across different AI development stages, improving governance and risk management.
NEW QUESTION # 59
CASE STUDY
Please use the following to answer the next question:
A premier payroll services company that employs thousands of people globally, is embarking on a new hiring campaign and wants to implement policies and procedures to identify and retain the best talent. The new talent will help the company's product team expand its payroll offerings to companies in the healthcare and transportation sectors, including in Asia.
It has become time consuming and expensive for HR to review all resumes, and they are concerned that human reviewers might be susceptible to bias.
To address these concerns, the company is considering using a third-party AI tool to screen resumes and assist with hiring. They have been talking to several vendors about possibly obtaining a third-party AI-enabled hiring solution, as long as it would achieve its goals and comply with all applicable laws.
The organization has a large procurement team that is responsible for the contracting of technology solutions. One of the procurement team's goals is to reduce costs, and it often prefers lower-cost solutions. Others within the company deploy technology solutions into the organization's operations in a responsible, cost-effective manner.
The organization is aware of the risks presented by AI hiring tools and wants to mitigate them. It also questions how best to organize and train its existing personnel to use the AI hiring tool responsibly. Their concerns are heightened by the fact that relevant laws vary across jurisdictions and continue to change.
If the company does not deploy and use the AI hiring tool responsibly in the United States, its liability would likely increase under all of the following laws EXCEPT:
Answer: C
Explanation:
Product liability laws typically apply to manufacturers and sellers of products, not directly to companies deploying AI tools internally; the other laws relate directly to the company's responsibilities in using AI for hiring.
NEW QUESTION # 60
CASE STUDY
Please use the following to answer the next question:
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 AI 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 AI 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.
While the marketing agency took steps to mitigate its risks, the best additional step would be to:
Answer: D
Explanation:
Establishing a governance committee provides ongoing oversight and accountability, which is crucial for managing risks effectively throughout the AI project lifecycle.
NEW QUESTION # 61
A company has trained an ML model primarily using synthetic data, and now intends to use live personal data to test the model.
Which of the following is NOT a best practice apply during the testing?
Answer: A
Explanation:
Minimizing human involvement to the extent practicable is not a best practice during the testing of an ML model. Human oversight is crucial during testing to ensure that the model performs correctly and ethically, and to interpret any anomalies or issues that arise. Best practices include using representative test data, anonymizing data to the extent practicable, and performing testing specific to the intended uses of the model.
Reference: AIGP Body of Knowledge on AI Model Testing and Human Oversight.
NEW QUESTION # 62
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