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IAPP AIGP Exam Syllabus Topics:
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NEW QUESTION # 27
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?
- A. Testing should minimize human involvement to the extent practicable.
- B. The test data should be anonymized to the extent practicable.
- C. The test data should be representative of the expected operationaldata.
- D. Testing should be performed specific to the intended uses.
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 # 28
CASE STUDY
Please use the following answer the next question:
ABC Corp, is a leading insurance provider offering a range of coverage options to individuals. ABC has decided to utilize artificial intelligence to streamline and improve its customer acquisition and underwriting process, including the accuracy and efficiency of pricing policies.
ABC has engaged a cloud provider to utilize and fine-tune its pre-trained, general purpose large language model ("LLM"). In particular, ABC intends to use its historical customer data-including applications, policies, and claims-and proprietary pricing and risk strategies to provide an initial qualification assessment of potential customers, which would then be routed .. human underwriter for final review.
ABC and the cloud provider have completed training and testing the LLM, performed a readiness assessment, and made the decision to deploy the LLM into production. ABC has designated an internal compliance team to monitor the model during the first month, specifically to evaluate the accuracy, fairness, and reliability of its output. After the first month in production, ABC realizes that the LLM declines a higher percentage of women's loan applications due primarily to women historically receiving lower salaries than men.
During the first month when ABC monitors the model for bias, it is most important to?
- A. Seek approval from management for any changes to the model.
- B. Analyze the quality of the training and testing data.
- C. Continue disparity testing.
- D. Compare the results to human decisions prior to deployment.
Answer: C
Explanation:
During the first month of monitoring the model for bias, it is most important to continue disparity testing.
Disparity testing involves regularly evaluating the model's decisions to identify and address any biases, ensuring that the model operates fairly across different demographic groups.
Reference: Regular disparity testing is highlighted in the AIGP Body of Knowledge as a critical practice for maintaining the fairness and reliability of AI models. By continuously monitoring for and addressing disparities, organizations can ensure their AI systems remain compliant with ethical and legal standards, and mitigate any unintended biases that may arise in production.
NEW QUESTION # 29
Scenario:
An organization is developing a powerful general-purpose AI (GPAI) model that has systemic impact. The compliance team is assessing what legal obligations apply under the EU AI Act.
Under the EU AI Act, which of the following compliance actions applies only to General Purpose AI models with systemic risk?
- A. Maintaining up-to-date technical documentation, including testing details
- B. Implementing an intellectual property policy to comply with EU copyright laws
- C. Making information available to downstream providers who integrate the model into their AI systems
- D. Publishing a detailed summary of the data used to train the model
Answer: D
Explanation:
The correct answer is A. Only GPAI models with systemic risk must publish a detailed summary of training data to meet transparency and accountability standards under the EU AI Act.
From the AI Governance in Practice Report 2024 (EU AI Act Section):
"For GPAI systems with systemic risk, providers must publish sufficiently detailed summaries of the content used to train the model." Also, the AIGP ILT Guide confirms:
"The obligation to disclose summaries of training data applies only to systemic-risk GPAI models, not all general-purpose models or high-risk systems." This unique requirement is part of the Act's effort to increase transparency and auditability for powerful foundational models.
NEW QUESTION # 30
Under the NIST Al Risk Management Framework, all of the following are defined as characteristics of trustworthy Al EXCEPT?
- A. Secure and Resilient.
- B. Accountable and Transparent.
- C. Tested and Effective.
- D. Explainable and Interpretable.
Answer: D
Explanation:
The NIST AI Risk Management Framework outlines several characteristics of trustworthy AI, including being secure and resilient, explainable and interpretable, and accountable and transparent. While being tested and effective is important, it is not explicitly listed as a characteristic of trustworthy AI in the NIST framework.
The focus is more on the system's ability to function safely, securely, and transparently in a way that stakeholders can understand and trust. Reference: AIGP Body of Knowledge, NIST AI RMF section.
NEW QUESTION # 31
The OECD's Ethical Al Governance Framework is a self-regulation model that proposes to prevent societal harms by?
- A. Focusing on Al technical design and post-deployment monitoring.
- B. Balancing Al innovation with ethical considerations.
- C. Establishing explain ability criteria to responsibly source and use data to train Al systems.
- D. Defining requirements specific to each industry sector and high-risk Al domain.
Answer: B
Explanation:
The OECD's Ethical AI Governance Framework aims to ensure that AI development and deployment are carried out ethically while fostering innovation. The framework includes principles like transparency, accountability, and human rights protections to prevent societal harm. It does not focus solely on technical design or post-deployment monitoring (C), nor does it establish industry-specific requirements (B). While explainability is important, the primary goal is to balance innovation with ethical considerations (D).
NEW QUESTION # 32
A Canadian company is developing an Al solution to evaluate candidates in the course of job interviews.
Before offering the Al solution in the EU market, the company must take all of the following steps EXCEPT?
- A. Establish a risk and quality management system.
- B. Draw up technical documentation and instructions for use.
- C. Register the Al solution in a public EU database.
- D. Engage a third-party auditor to perform a bias audit.
Answer: C
Explanation:
Before offering an AI solution in the EU market, a Canadian company must take several steps to comply with the EU AI Act. These steps include establishing a risk and quality management system (B), engaging a third-party auditor to perform a bias audit (C), and drawing up technical documentation and instructions for use (D). However, there is no requirement to register the AI solution in a public EU database (A). This registration step is not specified as part of the compliance requirements under the EU AI Act for such solutions.
NEW QUESTION # 33
Pursuant to the White House Executive Order of November 2023, who is responsible for creating guidelines to conduct red-teaming tests of Al systems?
- A. National Institute of Standards and Technology (NIST).
- B. Office of Science and Technology Policy (OSTP).
- C. National Science and Technology Council (NSTC).
- D. Department of Homeland Security (DHS).
Answer: A
Explanation:
The White House Executive Order of November 2023 designates the National Institute of Standards and Technology (NIST) as the responsible body for creating guidelines to conduct red-teaming tests of AI systems.
NIST is tasked with developing and providing standards and frameworks to ensure the security, reliability, and ethical deployment of AI systems, including conducting rigorous red-teaming exercises to identify vulnerabilities and assess risks in AI systems.
Reference: AIGP BODY OF KNOWLEDGE, sections on AI governance and regulatory frameworks, and the White House Executive Order of November 2023.
NEW QUESTION # 34
All of the following are potential benefits of using private over public LLMs EXCEPT?
- A. Confirmation of security and confidentiality.
- B. Application for specific use cases within the enterprise.
- C. Reduction in possibility of hallucinated information.
- D. Reduction in time taken for data validation and verification.
Answer: D
Explanation:
Private LLMs offer advantages likecustomizability,reduced hallucination,confidentiality, andalignment with enterprise-specific tasks, but theydo not inherently reduce the time or effortneeded fordata validation or verification- which remains an essential step regardless of model privacy.
From the AI risk and quality sections:
"Ensuring the quality of the data... is highly contextual and must be validated regardless of the model's deployment environment." (p. 17)
* B, C, Dare legitimate benefits of private LLMs.
* Ais incorrect - validation still requires time and resources.
NEW QUESTION # 35
According to the GDPR, what is an effective control to prevent a determination based solely on automated decision-making?
- A. Provide a right to review automated decision.
- B. Establish a human-in-the-loop procedure.
- C. Provide a just-in-time notice about the automated decision-making logic.
- D. Define suitable measures to safeguard personal data.
Answer: B
Explanation:
The GDPR requires that individuals have the right to not be subject to decisions based solely on automated processing, including profiling, unless specific exceptions apply. One effective control is to establish a human-in-the-loop procedure (D), ensuring human oversight and the ability to contest decisions. This goes beyond just-in-time notices (A), data safeguarding (B), or review rights (C), providing a more robust mechanism to protect individuals' rights.
NEW QUESTION # 36
An artist has been using an Al tool to create digital art and would like to ensure that it has copyright protection in the United States.
Which of the following is most likely to enable the artist to receive copyright protection?
- A. Provide a log of the prompts the artist used to generate the images.
- B. Obtain a representation from the Al provider on how the tool works.
- C. Ensure the tool was trained using publicly available content.
- D. Update the images in a creative way to demonstrate that it is the artist's.
Answer: D
Explanation:
For the artist to receive copyright protection, the most effective approach is to demonstrate that the final artwork includes sufficient creative input by the artist. By updating or altering the images in a way that reflects the artist's personal creativity, the artist can claim originality, which is a core requirement for copyright protection under U.S. law. The other options do not directly address the originality and creative input required for copyright. This is highlighted in the sections on copyright protection in the IAPP AIGP Body of Knowledge.
NEW QUESTION # 37
A US company has developed an Al system, CrimeBuster 9619, that collects information about incarcerated individuals to help parole boards predict whether someone is likely to commit another crime if released from prison.
When considering expanding to the EU market, this type of technology would?
- A. Be subject approval by the relevant EU authority.
- B. Require a detailed conformity assessment.
- C. Be banned under the EU Al Act.
- D. Require the company to register the tool with the EU database.
Answer: B
Explanation:
Under the EU AI Act, high-risk AI systems like CrimeBuster 9619 would require a detailed conformity assessment before being deployed in the EU market. This assessment ensures that the AI system complies with all relevant regulations and standards, addressing potential risks related to privacy, security, and discrimination. The company would not need to register the tool with the EU database (A), seek approval from an EU authority (B), or face a ban (D) as long as it meets the necessary conformity requirements.
NEW QUESTION # 38
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)?
- A. In case of a breach of AI Act prohibition by the Union institutions, bodies, offices and agencies
- B. In case of AI Act prohibitions
- C. In case of the supply of misleading information to notified bodies in reply to a request
- D. In case of breach of a provider's obligations for high-risk AI systems
Answer: D
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 # 39
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 content generated for minority construction workers is insufficient
- B. The generated ads are sent to construction companies, not individual workers
- C. The images of female workers are hyper-sexualized
- D. The advertising text generated for female audiences focuses on color and style
Answer: B
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 # 40
All of the following are elements of establishing a global Al governance infrastructure EXCEPT?
- A. Providing training to foster a culture that promotes ethical behavior.
- B. Creating policies and procedures to manage third-partyrisk.
- C. Understanding differences in norms across countries.
- D. Publicly disclosing ethical principles.
Answer: D
Explanation:
Establishing a global AI governance infrastructure involves several key elements, including providing training to foster a culture that promotes ethical behavior, creating policies and procedures to manage third-party risk, and understanding differences in norms across countries. While publicly disclosing ethical principles can enhance transparency and trust, it is not a core element necessary for the establishment of a governance infrastructure. The focus is more on internal processes and structures rather than public disclosure. Reference:
AIGP Body of Knowledge on AI Governance and Infrastructure.
NEW QUESTION # 41
Scenario:
A company using AI for resume screening understands the risks of algorithmic bias and the evolving legal requirements across jurisdictions. It wants to implement the right governance controls to prevent reputational damage from misuse of the AI hiring tool.
Which of the following measures should the company adopt to best mitigate its risk of reputational harm from using the AI tool?
- A. Require the procurement and deployment teams to agree upon the AI tool
- B. Test the AI tool pre- and post-deployment
- C. Ensure the vendor provides indemnification for the AI tool
- D. Continue to require the company's hiring personnel to manually screen all applicants
Answer: B
Explanation:
The correct answer is A. Pre- and post-deployment testing ensures bias, accuracy, and fairness are evaluated and corrected as needed, which is essential for reputational risk mitigation.
From the AIGP Body of Knowledge:
"Testing AI systems before and after deployment is critical to ensure performance, fairness, and compliance.
Failing to do so may result in reputational damage and legal exposure." AI Governance in Practice Report 2024 (Bias/Fairness and Risk Sections):
"System impact assessments, testing, and post-deployment monitoring are necessary to identify and mitigate risks... This supports both compliance and public trust." Testing is proactive, unlike indemnification (which transfers risk after damage), or requiring manual review (which defeats automation).
NEW QUESTION # 42
Which of the following disclosures is NOT required for an EU organization that developed and deployed a high-risk Al system?
- A. The human oversight measures employed.
- B. The fact that an Al system is being used.
- C. How an individual may contest a decision.
- D. The location(s) where data is stored.
Answer: D
Explanation:
Under the EU AI Act, organizations that develop and deploy high-risk AI systems are required to provide several key disclosures to ensure transparency and accountability. These include the human oversight measures employed, how individuals can contest decisions made by the AI system, and informing individuals that an AI system is being used. However, there is no specific requirement to disclose the exact locations where data is stored. The focus of the Act is on the transparency of the AI system's operation and its impact on individuals, rather than on the technical details of data storage locations.
NEW QUESTION # 43
What is the primary purpose of an AI impact assessment?
- A. To anticipate and manage the potential risks and harms of an AI system
- B. To escalate the findings to the appropriate owner(s)
- C. To identify and measure the benefits of an AI system
- D. To determine whether a conformity assessment is needed
Answer: A
Explanation:
The correct answer is D. AI Impact Assessments are primarily used to identify and manage risks and harms associated with AI systems.
From the AIGP Body of Knowledge:
"The goal of an AI impact assessment is to ensure that risks are identified, evaluated, and mitigated prior to or during development and deployment." As further confirmed in the AI Governance in Practice Report 2024 (Part III):
"Risk-based tools like DPIAs and Algorithmic Impact Assessments help identify potential risks to individuals and society, enabling organizations to implement mitigation plans and safeguards." While benefits may be noted in such assessments, the core objective is to manage risks and promote responsible AI.
NEW QUESTION # 44
After completing model testing and validation, which of the following is the most important step that an organization takes prior to deploying the model into production?
- A. Identify known edge cases to monitor post-deployment.
- B. Perform a readiness assessment.
- C. Document maintenance teams and processes.
- D. Define a model-validation methodology.
Answer: B
Explanation:
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.
NEW QUESTION # 45
What is the most important reason to document the results of AI testing?
- A. To limit the need for future testing cycles.
- B. To create a verifiable audit trail.
- C. To identify areas for red-teaming focus.
- D. To support post-deployment maintenance.
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 # 46
All of the following types of testing can help evaluate the performance of a responsible Al system EXCEPT?
- A. Adversarial robustness.
- B. Risk probability/severity.
- C. Statistical sampling.
- D. Decision analysis.
Answer: B
Explanation:
Risk probability/severity testing is not typically used to evaluate the performance of an AI system. While important for risk management, it does not directly assess an AI system's operational performance.
Adversarial robustness, statistical sampling, and decision analysis are all methods that can help evaluate the performance of a responsible AI system by testing its resilience, accuracy, and decision-making processes under various conditions. Reference: AIGP Body of Knowledge on AI Performance Evaluation and Testing.
NEW QUESTION # 47
What is the primary purpose of an Al impact assessment?
- A. To define and evaluate the legal risks associated with developing an Al system.
- B. To identify and measure the benefits of an Al system.
- C. To define and document the roles and responsibilities of Al stakeholders.
- D. Anticipate and manage the potential risks and harms of an Al system.
Answer: D
Explanation:
The primary purpose of an AI impact assessment is to anticipate and manage the potential risks and harms of an AI system. This includes identifying the possible negative outcomes and implementing measures to mitigate these risks. This process helps ensure that AI systems are developed and deployed in a manner that is ethically and socially responsible, addressing concerns such as bias, fairness, transparency, and accountability.
The assessment often involves a thorough evaluation of the AI system's design, data inputs, outputs, and the potential impact on various stakeholders. This approach is crucial for maintaining public trust and adherence to regulatory requirements.
NEW QUESTION # 48
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