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| Certification Vendor: | IAPP |
|---|---|
| Exam Name: | IAPP Certified Artificial Intelligence Governance Professional |
| Exam Number: | AIGP |
| Exam Duration: | 150 minutes |
| Exam Price: | USD 550 |
| Exam Format: | Multiple-choice |
| Related Certifications: | CIPM CIPP/A CIPP/E CIPP/US CIPT |
| Certificate Validity Period: | 2 Years |
| Passing Score: | 300 |
| Real Exam Qty: | 100 |
| Available Languages: | English |
| Sample Questions: | IAPP AIGP Sample Questions |
| Exam Way: | Online (OnVUE) or Test Center (Pearson VUE) |
| Pre Condition: | No specific prerequisites. Recommended background in privacy, compliance, legal, or technology. |
| Official Syllabus URL: | https://iapp.org/certify/aigp/ |
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NEW QUESTION # 137
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.
All of the following should be included in the marketing company's disclosures about the use of the LLM EXCEPT:
Answer: C
Explanation:
Disclosures by the marketing company should include the intended purpose, legal compliance, and limitations of the LLM but do not typically require revealing proprietary methods, which are confidential.
NEW QUESTION # 138
To assist its internal recruiters with filtering job applications, a company decides to develop in-house an AI model for screening and ranking job applicants ' resumes.
Which of the following is a unique issue this company might face compared with using a third-party AI service?
Answer: A
Explanation:
Developing an AI model internally creates a direct need for technical expertise covering model development, infrastructure, deployment, monitoring, retraining, security, testing, and maintenance. This makes A the strongest distinguishing issue. Third-party AI services can reduce this operational burden because the external provider supplies much of the model and underlying infrastructure; IAPP guidance specifically notes that third-party APIs can accelerate deployment and reduce the burden of managing complex infrastructure. B is incorrect because an internally developed model generally provides more , not less, technical control. C is not necessarily true because total costs depend on scale, licensing, infrastructure, and usage. D is also too absolute: although developing a system can create substantial provider obligations, responsibility under AI laws and governance frameworks may still be distributed among providers, deployers, vendors, processors, and other actors depending on the circumstances.
NEW QUESTION # 139
Scenario:
A European AI technology company was found to be non-compliant with certain provisions of the EU AI Act.
The regulator is considering penalties under the enforcement provisions of the regulation.
According to the EU AI Act, which of the following non-compliance examples could lead to fines of up to €
15 million or 3% of annual worldwide turnover(whichever is higher)?
Answer: B
Explanation:
The correct answer isB. The EU AI Act assigns atiered penalty systembased on the severity of the violation.
A breach ofobligations related to high-risk AI systemsfalls into the mid-tier category, triggering fines of €
15 million or 3% of annual global turnover.
From the AIGP ILT Guide - EU AI Act Module:
"Providers of high-risk AI systems must comply with strict documentation, testing, monitoring, and registration obligations. Breaches of these result in significant fines of up to €15 million or 3% of turnover." AI Governance in Practice Report 2024 supports this:
"Non-compliance with obligations under Title III (high-risk systems) leads to financial penalties under Article
71(3) of the EU AI Act."
Note: Thehighest penalty (€35 million or 7%)applies toprohibited AI uses, not to obligations for high-risk systems.
NEW QUESTION # 140
Business A sells software that provides users with writing and grammar assistance. Business B is a cloud services provider that trains its own AI models.
* Business A has decided to add generative AI features to their software.
* Rather than create their own generative AI model, Business A has chosen to license a model from Business B:
* Business A will then integrate the model into their writing assistance software to provide generative AI capabilities.
* Business A is most concerned that its writing assistance software could recommend toxic or obscene text to its users.
Which of the following governance processes should Business A take to best protect its users against potentially inappropriate text?
Answer: B
Explanation:
Business A is integrating a generative AI model licensed from a third party (Business B) and is primarily concerned with the risk of toxic or obscene outputs being delivered to users. In this scenario,testing and validationof the AI model for such content risks is the most direct and effective governance strategy.
According to theAI Governance in Practice Report 2024, organizations thatdeployAI must engage in performance monitoring protocolsand ensure systems perform adequately for theirintended purposes, including filtering harmful content:
"Operational governance... development of: #Performance monitoring protocols to ensure systems perform adequately for their intended purposes." (p. 12)
"Product governance... includes: #System impact assessments to identify and address risk prior to product development or deployment." (p. 11) Furthermore, under theEU AI Act, which sets the global standard many organizations aim to align with, there is a clear obligation to test and monitor systems for potential harmful behavior:
"The act imposes regulatory obligations... such as establishing appropriate accountability structures,assessing system impact, providing technical documentation,establishing risk management protocols and monitoring performance..." (p. 7) Option B directly reflects this best practice ofpre-deployment testing and validationto ensure that the model aligns with Business A's minimum content safety requirements.
Let's now evaluate the incorrect options:
* A. Fine-tuning on verified user-generated textmay improve model alignment but does not guarantee that the model will generalize correctly, especially if Business A lacks access to model internals (common in third-party licensing scenarios). Fine-tuning also introduces its own risks and may be contractually restricted.
* C. A user reporting featureisreactive, not preventive. While helpful for long-term monitoring and mitigation, it does not prevent the initial harm of toxic outputs, which isBusiness A's primary concern.
* D. Requesting documentation from Business Bis useful for transparency and risk management, but it does not replaceindependent verificationthat the model meets Business A's content safety standards.
Thus,testing the model's behavior for unacceptable outputs before deploymentis the most aligned approach with AI governance best practices and obligations.
NEW QUESTION # 141
Scenario:
A public sector agency is reviewing proposed AI use cases for improving services. It wants to prioritize implementations that deliver value butminimize unintended negative consequences.
When evaluating which AI use cases to implement, an organization should consider all of the following EXCEPT:
Answer: D
Explanation:
The correct answer isA. While TEVV is important inlater lifecycle phases, it isnot the primary considerationwhen evaluating and prioritizinguse 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,Ais not a top-level consideration during use caseselection.
NEW QUESTION # 142
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