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| Certification Vendor: | IAPP (International Association of Privacy Professionals) |
|---|---|
| Exam Name: | IAPP Certified Artificial Intelligence Governance Professional (AIGP) Exam |
| Exam Number: | AIGP |
| Exam Format: | Multi-select, Scenario-based questions, Single-select, Multiple-choice |
| Available Languages: | English |
| Certificate Validity Period: | 2 years |
| Exam Price: | USD 799 (non-member) / USD 649 (IAPP member) |
| Real Exam Qty: | 100 (85 scored + ~15 unscored pilot questions) |
| Passing Score: | 300 (scaled score out of 100–500) |
| Related Certifications: | CIPP/E CIPT CIPP/US CIPM |
| Exam Duration: | 165 minutes |
| Recommended Training: | IAPP Official AIGP Training and Resources AIGP Practice Exam (Official IAPP Store) |
| Exam Registration: | Pearson VUE Scheduling Portal (via IAPP account) Official IAPP AIGP Exam Registration |
| Sample Questions: | IAPP AIGP Sample Questions |
| Exam Way: | Computer-based exam delivered via Pearson VUE (test center or online proctored OnVUE) |
| Pre Condition: | None |
| Official Syllabus URL: | https://iapp.org/certify/aigp |
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NEW QUESTION # 40
Scenario:
An enterprise is evaluating multiple third-party generative AI tools to integrate into its platform. As part of its AI governance policy, it is assessing themost effective methodsto reduce risks related to bias, data misuse, and liability when using third-party solutions.
All of the following are commonly adopted processes and policies in reducing potential risks introduced by third-party AI tools or applications EXCEPT:
Answer: B
Explanation:
The correct answer isB. AllowingPIIto be freely entered into prompts without safeguards is considered amajor privacy and security riskand is not a responsible governance practice.
From the AIGP ILT Guide - Generative AI & Third-Party Risk Management:
"Use of personal or sensitive information in AI prompts can result in unintended exposure, regulatory breaches, and downstream liability." The AI Governance in Practice Report2025highlights:
"PII should be minimized or protected by design. Prompt engineering should prevent entry of personally identifiable data unless legally and technically safeguarded." A, C, and D are established best practices under responsible AI procurement and use.
NEW QUESTION # 41
Which of the following considerations is the most important in mitigating the potential of bias in training and testing data?
Answer: D
Explanation:
The correct answer is B because ensuring that training and testing data is representative is the most critical factor in mitigating bias in AI systems. AI governance frameworks emphasize that biased or unrepresentative datasets can lead to discriminatory outcomes, particularly when certain demographic groups are underrepresented or overrepresented. Representative data helps ensure that the model performs fairly and accurately across different populations. While privacy-enhancing tools and consent address legal and ethical data use, they do not directly prevent bias in model outcomes. Similarly, assessing the sufficiency of third- party data focuses on quantity rather than fairness or distribution. Effective bias mitigation begins with evaluating whether the dataset reflects the diversity and characteristics of the real-world population the AI system will impact.
NEW QUESTION # 42
MULTI-SELECT
Please select 3 of the 5 options below. No partial credit will be given.
What are the roles and responsibilities of deployers of a proprietary model?
Answer: B,D,E
Explanation:
Deployers of proprietary models arenot responsible for design, but they are accountable for how the system performsin their context of use, including ensuring ethical behavior, performance, and legal compliance.
From theAI Governance in Practice Report 2025:
"Deployers of AI systems must take reasonable steps to ensure that systems are used ethically, perform safely, and align with applicable laws and standards." (p. 11-12)
"Operational governance... includes performance monitoring protocols, incident management plans, and regulatory oversight." (p. 12) Thus:
✅A. Ethical testing- Required to mitigate misuse and unintended harms.
❌B. Ethical design- Belongs todevelopers/providers, not deployers.
✅C. Technical performance- Deployers must ensure that AI performs as expected.
❌D. System documentation- This is theprovider'sobligation.
✅E. Regulatory compliance- Deployers must ensure system use complies with applicable laws.
NEW QUESTION # 43
In the machine learning context, feature engineering is the process of:
Answer: D
Explanation:
Feature engineering involves extracting and transforming relevant attributes or variables from raw data to improve model performance.
NEW QUESTION # 44
CASE STUDY
Please use the following to answer the next question:
XYZ Corp., 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.
The frameworks that would be most appropriate for XYZ's governance needs would be the NIST AI Risk Management Framework and:
Answer: B
Explanation:
The IEEE Ethical System Design Risk Management Framework (IEEE 7000-21) complements the NIST AI Risk Management Framework by addressing ethical considerations in AI system design, fitting XYZ Corp's governance needs for responsible AI hiring tool use.
NEW QUESTION # 45
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