Most UptoDate IAPP AIGP Exam Dumps PDF 2026
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NEW QUESTION # 67
CASE STUDY
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 Al tool to screen resumes and assist with hiring. They have been talking to several vendors about possibly obtaining a third-party Al-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 Al hiring tools and wants to mitigate them. It also questions how best to organize and train its existing personnel to use the Al hiring tool responsibly. Their concerns are heightened by the fact that relevant laws vary across jurisdictions and continue to change.
The organization continues planning the adoption of an AI tool to support hiring, but is concerned about potential bias in content generated by AI systems and how that could affect public perception.
Which of the following measures should the company adopt to best mitigate its risk of reputational harm from using the AI tool?
- A. Ensure the vendor provides indemnification for the AI tool
- B. Test the AI tool pre- and post-deployment
- C. Require the procurement and deployment teams to agree upon the AI tool
- D. Continue to require the company's hiring personnel to manually screen all applicants
Answer: B
Explanation:
Note: This is the same scenario and question as Question 21 and thus has the same correct answer: A. It's possible this was duplicated in your original input.
Repeated for clarity:
"Testing AI tools pre- and post-deployment helps ensure they perform as expected and do not introduce bias, privacy issues, or fairness concerns. This mitigates reputational and legal risk." The AI Governance in Practice Report 2024 further reinforces:
"Ongoing monitoring and testing post-deployment allows organizations to catch and correct unintended impacts... especially important in HR and hiring contexts."
NEW QUESTION # 68
Your organization is searching for a new way to help accurately forecast sales predictions by various types of customers. Which of the following is the best type of model to choose if your organization wants to customize the model and avoid lock-in?
- A. A free large language model.
- B. A subscription-based, multimodal model.
- C. A proprietary generative AI model.
- D. A classic machine learning model.
Answer: D
Explanation:
A classic machine learning model offers full customization, transparency, and portability, allowing the organization to tailor training data, model architecture, and deployment without dependence on a proprietary vendor, thereby avoiding lock-in.
NEW QUESTION # 69
What is the best method to apply to an AI model so that it is statistically unlikely that a specific piece of training data can be identified from a model's output?
- A. Homomorphic encryption.
- B. Data compartmentalization.
- C. Data sharding.
- D. Differential privacy.
Answer: D
Explanation:
Differential privacy adds controlled noise to the training process, making it statistically unlikely to identify specific training data from the model's outputs.
NEW QUESTION # 70
Random forest algorithms are in what type of machine learning model?
- A. Generative.
- B. Natural language processing.
- C. Discriminative.
- D. Symbolic.
Answer: C
Explanation:
Random forest algorithms are classified as discriminative models. Discriminative models are used to classify data by learning the boundaries between classes, which is the core functionality of random forest algorithms.
They are used for classification and regression tasks by aggregating the results of multiple decision trees to make accurate predictions.
Reference: The AIGP Body of Knowledge explains that discriminative models, including random forest algorithms, are designed to distinguish between different classes in the data, making them effective for various predictive modeling tasks.
NEW QUESTION # 71
All of the following are reasons to deploy a challenger Al model in addition a champion Al model EXCEPT to?
- A. Retrain the champion model.
- B. Provide a framework to consider alternatives to the champion model.
- C. Perform testing on the champion model.
- D. Automate real-time monitoring of the champion model.
Answer: A
Explanation:
Deploying a challenger AI model alongside a champion model is a strategy used to compare the performance of different models in a real-world environment. This approach helps in providing a framework to consider alternatives to the champion model, automating real-time monitoring of the champion model, and performing testing on the champion model. However, retraining the champion model is not a reason to deploy a challenger model. Retraining is a separate process that involves updating the champion model with new data or techniques, which is not related to the use of a challenger model.
Reference: AIGP BODY OF KNOWLEDGE, sections on model evaluation and management.
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 marketing company and its tech provider have taken reasonable steps to govern the AI's use, including legal disclosures, impact assessments, and bias mitigation. However, the company wants to takeone more stepto improve governance and reduce risks related to ongoing oversight and accountability.
While the marketing agency took steps to mitigate its risks, the best additional step would be to:
- A. Establish a governance committee to oversee the project
- B. Negotiate an intellectual property indemnity from the technology company
- C. Engage a third party to lead the procurement selection process
- D. Evaluate the use of AI in the marketing industry to identify best practices
Answer: A
Explanation:
The correct answer isD. Forming adedicated governance committeeensures continuous oversight, role clarity, and accountability throughout the AI lifecycle.
From the AIGP ILT Guide - Governance Structures:
"Organizations using AI in high-impact scenarios should establish a governance body responsible for oversight of risk, compliance, and ethical alignment." Also reflected in AI Governance in Practice Report2025:
"Committees support cross-functional decision-making, provide guidance for updates, and maintain accountability. This is especially critical for high-stakes applications like marketing to diverse audiences." Options A, B, and C are valid supplementary actions, butDoffers a long-term and systematic governance mechanism.
NEW QUESTION # 73
A shipping service based in the US is looking to expand its operations into the EU. It utilizes an in-house developed multimodal AI model that analyzes all personal data collected from shipping senders and recipients, and optimizes shipping routes and schedules based on this data.
As they expand into the EU, all of the following descriptions should be included in the technical documentation for their AI model EXCEPT?
- A. A detailed description of the elements of the AI system and of the process for its development.
- B. A general description of the AI system.
- C. A description of the prioritization of the risks of deployment of the AI system.
- D. A description of the appropriateness of the performance metrics for the specific AI system.
Answer: C
Explanation:
The EU AI Act outlines what must be included intechnical documentationfor high-risk systems. These requirements are designed to supportconformity assessment, transparency, and traceability.
From theAI Governance in Practice Report 2024:
"It mandates drawing up technical documentation... must include a general description of the AI system, the intended purpose, and a detailed description of the elements and development process." (p. 34)
"Documentation... includes training, testing, evaluation procedures, andappropriateness of performance metrics." (p. 34-35) Therisk management systemis addressed separately through arisk management plan, not within the technical documentation itself.
Thus:
* A, C, and Dare explicitly required in thetechnical documentation.
* B, while important, is part of therisk management process, not a required section oftechnical documentation.
NEW QUESTION # 74
Scenario:
A distributor operating in the EU is responsible for selling imported high-risk AI systems to businesses. The distributor wants to ensure they fulfill all applicable obligations under the EU AI Act.
All of the following are obligations of a distributor of high-risk AI systems under the EU AI Act EXCEPT?
- A. Registration in EU Database
- B. Communication with national authorities
- C. Corrective actions
- D. Verification of CE marking
Answer: A
Explanation:
The correct answer isC.Registration in the EU databaseis an obligation ofprovidersof high-risk AI systems- not distributors.
From the AIGP ILT Guide - Roles & Obligations Module:
"Distributors must verify CE marking, ensure instructions for use are provided, inform authorities of risks, and take corrective action when necessary. However, registration duties in the EU database lie with the provider." Also from the AI Governance in Practice Report2025:
"The AI Act differentiates responsibilities for developers, providers, importers, and distributors. Only providers of high-risk systems are obligated to register their systems in the EU AI Database." Distributors focus onverification and communication, not formal registration.
NEW QUESTION # 75
Under the NIST Al Risk Management Framework, all of the following are defined as characteristics of trustworthy Al EXCEPT?
- A. Tested and Effective.
- B. Accountable and Transparent.
- C. Secure and Resilient.
- D. Explainable and Interpretable.
Answer: A
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 # 76
The processes and methods that allow human users to understand and trust the outputs produced by AI are important in addressing which key regulatory concern?
- A. Trustworthy AI.
- B. Interpretable AI.
- C. Responsible AI.
- D. Explainable AI.
Answer: D
Explanation:
Explainable AI focuses specifically on providing users with understandable reasoning behind AI outputs so they can interpret, evaluate, and trust the system's decisions.
NEW QUESTION # 77
Which of the following best defines an "Al model"?
- A. A system that applies defined rules to execute tasks.
- B. A system of controls that is used to govern an Al algorithm.
- C. A program that has been trained on a set of data to find patterns within the data.
- D. A corpus of data which an Al algorithm analyzes to make predictions.
Answer: C
Explanation:
An AI model is best defined as a program that has been trained on a set of data to find patterns within that data. This definition captures the essence of machine learning, where the model learns from the data to make predictions or decisions. Reference: AIGP BODY OF KNOWLEDGE, which provides a detailed explanation of AI models and their training processes.
NEW QUESTION # 78
CASE STUDY
A company is considering the procurement of an AI system designed to enhance the security of IT infrastructure. The AI system analyzes how users type on their laptops, including typing speed, rhythm and pressure, to create a unique user profile. This data is then used to authenticate users and ensure that only authorized personnel can access sensitive resources.
The data processed by the AI system would be classified as:
- A. Non-personal data, as long as it is not linked to a user ID
- B. Organizational data, since it is part of the authentication process
- C. Special category data, if it can be used to uniquely identify a person
- D. Non-sensitive personal data, since it does not reveal information about health, gender or race
Answer: C
Explanation:
The correct answer isD.Keystroke dynamics, used to identify individuals, fallunder biometricdata, which isa specialcategory of personaldata underthe GDPR and other frameworks.
From the AI Governance in Practice Report2025:
"Keystroke dynamics may constitute biometric data if used to uniquely identify an individual... Biometric data is classified as special category personal data and requires higher protection standards." Also reflected in ILT Participant Guide:
"Biometric data, such as facial images, voiceprints, iris scans or keystroke patterns, are treated as special category data when they are used for the purpose of uniquely identifying individuals."
NEW QUESTION # 79
According to the EU AI Act, providers of what kind of machine learning systems will be required to register with an EU oversight agency before placing their systems in the EU market?
- A. AI systems that are harmful based on a legal risk-utility calculations.
- B. AI systems that are "strong" general intelligence.
- C. AI systems that are high-risk.
- D. AI systems trained on sensitive personal data.
Answer: C
Explanation:
The EU AI Act classifies AI systems into four risk categories:
1. Unacceptable risk: AI applications posing a clear threat to safety, livelihoods, and rights of people, such as social scoring or real-time biometric identification in public spaces.
2. High-risk: AI systems that significantly impact health, safety, or fundamental rights, including those used in critical infrastructure, education, employment, and law enforcement.
3. Limited risk: AI systems with specific transparency obligations, like chatbots.
4. Minimal risk: AI systems with minimal regulatory requirements, such as spam filters.
Providers of high-risk AI systems must ensure compliance with the Act's requirements, including conducting a conformity assessment and registering the system in the EU database.
NEW QUESTION # 80
Under the Canadian Artificial Intelligence and Data Act, when must the Minister of Innovation, Science and Industry be notified about a high-impact AI system?
- A. Upon initial deployment of the system.
- B. When the algorithmic impact assessment has been completed.
- C. Upon release of a new version of the system.
- D. When use of the system causes or is likely to cause material harm.
Answer: D
Explanation:
Under the Canadian Artificial Intelligence and Data Act (AIDA), the responsible party must notify the Minister of Innovation, Science and Industry as soon as feasible if the use of a high-impact AI system results in or is likely to result in material harm.
NEW QUESTION # 81
Scenario:
An organization is planning to deploy a new internal application that uses AI to make automated decisions about individuals. This application will process personal information and may affect individuals' access to certain benefits or opportunities.
Which of the following documents must be updated to ensure transparency?
- A. The organization's website privacy notice
- B. The organization's privacy policy
- C. The organization's acceptable use policy
- D. The user privacy notice
Answer: D
Explanation:
The correct answer is D. Transparency obligations under data protection laws, such as GDPR and most AI governance frameworks, require that users whose data is being processed be directly informed.
From the AIGP ILT Guide (Privacy Module):
"The user privacy notice must be updated to explain the nature of automated processing, the logic involved, and the significance and consequences for the data subject." Also, per AI Governance in Practice Report 2024 (Part III):
"Transparency obligations apply throughout the lifecycle of AI... Individuals must be informed about automated decision-making and profiling that may impact them." Unlike internal policies or general privacy notices, the user privacy notice provides direct transparency to the individual data subjects affected by AI processing.
NEW QUESTION # 82
A company that deploys AI but is not currently a provider or developer intends to develop and market its own AI system.
Which obligation would then be likely to apply?
- A. Developing documentation on the system, the potential risks and the safeguards applied.
- B. Implementing a risk management framework.
- C. Developing a reporting plan for any observed algorithmic discrimination or harms to individuals' rights and freedoms.
- D. Conducting an impact assessment including a post-deployment monitoring plan.
Answer: A
Explanation:
Once a company moves from being adeployerto also acting as aprovider or developer, it assumesnew obligationsunder regulations like the EU AI Act. One of the core requirements for providers is to produce and maintaintechnical documentation, including descriptions of the model, associated risks, and mitigation strategies.
From theAI Governance in Practice Report 2024:
"Providers of high-risk AI systems must draw up technical documentation demonstrating the system's conformity with the requirements... including potential risks and safeguards applied." (p. 34)
"This documentation must be available before placing the system on the market." (p. 35)
NEW QUESTION # 83
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?
- A. Regulatory compliance.
- B. Technical performance.
- C. Ethical testing.
- D. System documentation.
- E. Ethical design.
Answer: A,B,C
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 2024:
"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 # 84
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. Ensure the vendor provides indemnification for the AI tool
- B. Test the AI tool pre- and post-deployment
- C. Require the procurement and deployment teams to agree upon the AI tool
- D. Continue to require the company's hiring personnel to manually screen all applicants
Answer: B
Explanation:
The correct answer isA. Pre- and post-deployment testing ensuresbias, accuracy, and fairnessare evaluated and corrected as needed, which isessential 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 Report2025(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 # 85
After initially deploying a third-party AI model, you learn the developer has released a new version. As deployer of this third-party model, what should you do?
- A. Seek input from data scientists.
- B. Communicate necessary updates to your users.
- C. Retrain the model.
- D. Audit the model.
Answer: D
Explanation:
When a third-party developer releases a new model version, the deployer must first audit the updated model to determine whether the changes introduce new risks, alter performance, or affect compliance obligations before considering deployment or communicating updates.
NEW QUESTION # 86
Which of the following are subjects covered by a typical impact assessment?
- A. Third-party risk, model risk and legal risk.
- B. Fundamental rights, data protection and safety.
- C. Toxicity, accuracy and development.
- D. Datasets, behavior and tooling.
Answer: B
Explanation:
The correct answer is D because typical AI impact assessments focus on evaluating risks to individuals and society, particularly in areas such as fundamental rights, data protection, and safety. Frameworks like Data Protection Impact Assessments and Fundamental Rights Impact Assessments are designed to assess how AI systems may affect privacy, fairness, human rights, and potential harm to users. These assessments are core components of AI governance and are often required or recommended by regulations such as the GDPR and the EU AI Act. While options A, B, and C reference technical or operational considerations, they do not capture the broader societal and legal impacts that impact assess ments are intended to address. AI governance emphasizes a human-centric approach, ensuring systems are safe, lawful, and respectful of individual rights before deployment.
NEW QUESTION # 87
Scenario:
A distributor operating in the EU is responsible for selling imported high-risk AI systems to businesses. The distributor wants to ensure they fulfill all applicable obligations under the EU AI Act.
All of the following are obligations of a distributor of high-risk AI systems under the EU AI Act EXCEPT?
- A. Registration in EU Database
- B. Communication with national authorities
- C. Corrective actions
- D. Verification of CE marking
Answer: A
Explanation:
The correct answer is C. Registration in the EU database is an obligation of providers of high-risk AI systems-not distributors.
From the AIGP ILT Guide - Roles & Obligations Module:
"Distributors must verify CE marking, ensure instructions for use are provided, inform authorities of risks, and take corrective action when necessary. However, registration duties in the EU database lie with the provider." Also from the AI Governance in Practice Report 2024:
"The AI Act differentiates responsibilities for developers, providers, importers, and distributors. Only providers of high-risk systems are obligated to register their systems in the EU AI Database." Distributors focus on verification and communication, not formal registration.
NEW QUESTION # 88
A company is creating a mobile app to enable individuals to upload images and videos, and analyze this data using ML to provide lifestyle improvement recommendations. The sign-up form has the following data fields:
1. First name
2. Last name
3. Mobile number
4. Email ID
5. New password
6. Date of birth
7. Gender
In addition, the app obtains a device's IP address and location information while in use.
What GDPR privacy principles does this violate?
- A. Transparency and Accuracy.
- B. Integrity and Confidentiality.
- C. Accountability and Lawfulness.
- D. Purpose Limitation and Data Minimization.
Answer: D
Explanation:
Collecting more personal data than necessary violates GDPR principles of Purpose Limitation (using data only for specific purposes) and Data Minimization (collecting only what is needed).
NEW QUESTION # 89
You are part of your organization's ML engineering team and notice that the accuracy of a model that was recently deployed into production is deteriorating.
What is the best first step address this?
- A. Replace the model with a previous version.
- B. Conduct champion/challenger testing.
- C. Perform an audit of the model.
- D. Run red-teaming exercises.
Answer: B
Explanation:
When the accuracy of a model deteriorates, the best first step is to conduct champion/challenger testing. This involves deploying a new model (challenger) alongside the current model (champion) to compare their performance. This method helps identify if the new model can perform better under current conditions without immediately discarding the existing model. It provides a controlled environment to test improvements and understand the reasons behind the deterioration. This approach is preferable to directly replacing the model, performing audits, or running red-teaming exercises, which may be subsequent steps based on the findings from the champion/challenger testing.
Reference: AIGP BODY OF KNOWLEDGE, sections on model performance management and testing strategies.
NEW QUESTION # 90
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