Latest AIGP Actual Free Exam Questions Updated 166 Questions [Q33-Q49]

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Latest AIGP Actual Free Exam Questions Updated 166 Questions

Free AIGP Exam Braindumps certification guide Q&A

IAPP AIGP Exam Syllabus Topics:

Topic	Details
Topic 1	Understanding How to Govern AI Development: This section of the exam measures the skills of AI project managers and covers the governance responsibilities involved in designing, building, training, testing, and maintaining AI models. It emphasizes defining the business context, performing impact assessments, applying relevant laws and best practices, and managing risks during model development. The domain also includes establishing data governance for training and testing, ensuring data quality and provenance, and documenting processes for compliance. Additionally, it focuses on preparing models for release, continuous monitoring, maintenance, incident management, and transparent disclosures to stakeholders.
Topic 2	Understanding the Foundations of AI Governance: This section of the exam measures skills of AI governance professionals and covers the core concepts of AI governance, including what AI is, why governance is needed, and the risks and unique characteristics associated with AI. It also addresses the establishment and communication of organizational expectations for AI governance, such as defining roles, fostering cross-functional collaboration, and delivering training on AI strategies. Additionally, it focuses on developing policies and procedures that ensure oversight and accountability throughout the AI lifecycle, including managing third-party risks and updating privacy and security practices.
Topic 3	Understanding How Laws, Standards, and Frameworks Apply to AI: This section of the exam measures skills of compliance officers and covers the application of existing and emerging legal requirements to AI systems. It explores how data privacy laws, intellectual property, non-discrimination, consumer protection, and product liability laws impact AI. The domain also examines the main elements of the EU AI Act, such as risk classification and requirements for different AI risk levels, as well as enforcement mechanisms. Furthermore, it addresses the key industry standards and frameworks, including OECD principles, NIST AI Risk Management Framework, and ISO AI standards, guiding organizations in trustworthy and compliant AI implementation.
Topic 4	Understanding How to Govern AI Deployment and Use: This section of the exam measures skills of technology deployment leads and covers the responsibilities associated with selecting, deploying, and using AI models in a responsible manner. It includes evaluating key factors and risks before deployment, understanding different model types and deployment options, and ensuring ongoing monitoring and maintenance. The domain applies to both proprietary and third-party AI models, emphasizing the importance of transparency, ethical considerations, and continuous oversight throughout the model’s operational life.

QUESTION 33
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:

Related TEVV (test, evaluate, verify, validate) and system metrics

The users and their expectations

Equitable access to the AI tool

Potential positive and negative impacts of the system

QUESTION 34
Pursuant to the White House Executive Order of November 2023, who is responsible for creating guidelines to conduct red-teaming tests of Al systems?

National Institute of Standards and Technology (NIST).

National Science and Technology Council (NSTC).

Office of Science and Technology Policy (OSTP).

Department of Homeland Security (DHS).

QUESTION 35
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 take one more step to 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:

Negotiate an intellectual property indemnity from the technology company

Evaluate the use of AI in the marketing industry to identify best practices

Engage a third party to lead the procurement selection process

Establish a governance committee to oversee the project

QUESTION 36
CASE STUDY
Please use the following 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.
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 are responsible for integrating and deploying 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 frameworks that would be most appropriate for XYZ’s governance needs would be the NIST Al Risk Management Framework and?

NIST Information Security Risk (NIST SP 800-39).

NIST Cyber Security Risk Management Framework (CSF 2.0).

IEEE Ethical System Design Risk Management Framework (IEEE 7000-21).

Human Rights, Democracy, and Rule of Law Impact Assessment (HUDERIA).

QUESTION 37
What is the primary purpose of an AI impact assessment?

To determine whether a conformity assessment is needed

To escalate the findings to the appropriate owner(s)

To identify and measure the benefits of an AI system

To anticipate and manage the potential risks and harms of an AI system

QUESTION 38
Which of the following is a subcategory of Al and machine learning that uses labeled datasets to train algorithms?

Segmentation.

Generative Al.

Expert systems.

Supervised learning.

QUESTION 39
Which of the following is a foundational characteristic of effective AI governance?

Engagement of a cross-functional team

Reliance on tested vendor management processes

Thorough reviews of a company’s public filings with experts

Uniform policies and procedures across developer, deployer and user roles

QUESTION 40
A company initially intended to use a large data set containing personal information to train an Al model.
After consideration, the company determined that it can derive enough value from the data set without any personal information and permanently obfuscated all personal data elements before training the model.
This is an example of applying which privacy-enhancing technique (PET)?

Anonymization.

Pseudonymization.

Differential privacy.

Federated learning.

QUESTION 41
To maintain fairness in a deployed system, it is most important to?

Protect against loss of personal data in the model.

Monitor for data drift that may affect performance and accuracy.

Detect anomalies outside established metrics that require new training data.

Optimize computational resources and data to ensure efficiency and scalability.

QUESTION 42
All of the following are reasons to deploy a challenger Al model in addition a champion Al model EXCEPT to?

Provide a framework to consider alternatives to the champion model.

Automate real-time monitoring of the champion model.

Perform testing on the champion model.

Retrain the champion model.

QUESTION 43
Which of the following is an example of a high-risk application under the EU Al Act?

A resume scanning tool that ranks applicants.

An Al-enabled inventory management tool.

A government-run social scoring tool.

A customer service chatbot tool.

QUESTION 44
The best practice to manage third-party risk associated with AI systems is to create and implement policies that?

Focus on the financial stability of third-party vendors as the primary criterion for risk assessment.

Provide for an appropriate level of due diligence and ongoing monitoring based on the defined risk.

Require third-party AI systems to undergo a comprehensive audit by an external cybersecurity firm every six months.

Focus on the technical aspects of AI systems, such as data security, while ethical risks are addressed through suitable contracts.

QUESTION 45
Retraining an LLM can be necessary for all of the following reasons EXCEPT?

To minimize degradation in prediction accuracy due tochanges in data.

Adjust the model’s hyper parameters specific use case.

Account for new interpretations of the same data.

To ensure interpretability of the model’s predictions.

QUESTION 46
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 the most effective methods to 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:

Including clauses in the procurement agreement for buyers of generative AI tools to put certain liabilities on the tool supplier

Allowing publicly available information and personally identifiable information (PII) to be incorporated into the prompt

Requiring an independent third-party bias audit for third-party generative AI tools

Requiring new use cases of the generative AI tools or applications to be reviewed and approved by the generative AI governance body

QUESTION 47
Which type of existing assessment could best be leveraged to create an Al impact assessment?

A safety impact assessment.

A privacy impact assessment.

A security impact assessment.

An environmental impact assessment.

QUESTION 48
What is the best method to proactively train an LLM so that there is mathematical proof that no specific piece of training data has more than a negligible effect on the model or its output?

Clustering.

Transfer learning.

Differential privacy.

Data compartmentalization.

QUESTION 49
The framework set forth in the White House Blueprint for an Al Bill of Rights addresses all of the following EXCEPT?

Human alternatives, consideration and fallback.

High-risk mitigation standards.

Safe and effective systems.

Data privacy.