Ace AIGP Certification with 204 Actual Questions [Q110-Q129]

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Ace AIGP Certification with 204 Actual Questions

PASS IAPP AIGP EXAM WITH UPDATED DUMPS

Q110. Which stakeholder is responsible for lawful collection of data for the training of the foundational AI model?

 
 
 
 

Q111. When monitoring the functional performance of a model that has been deployed into production, all of the following are concerns EXCEPT?

 
 
 
 

Q112. You are the chief privacy officer of a medical research company that would like to collect and use sensitive data about cancer patients, such as their names, addresses, race and ethnic origin, medical histories, insurance claims, pharmaceutical prescriptions, eating and drinking habits and physical activity.
The company will use this sensitive data to build an AI algorithm that will spot common attributes that will help predict if seemingly healthy people are more likely to get cancer. However, the company is unable to obtain consent from enough patients to sufficiently collect the minimum data to train its model.
Which of the following solutions would most efficiently balance privacy concerns with the lack of available data during the testing phase?

 
 
 
 

Q113. 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?

 
 
 
 

Q114. In the machine learning context, feature engineering is the process of:

 
 
 
 

Q115. Your company is developing an AI system for global markets. This system involves personal data processing and some decision making that may affect rights of the individuals. Part of your role as an AI governance professional is to ensure the AI system complies with various international regulatory requirements. Which of the following approaches best aligns with a comprehensive understanding of and compliance with AI regulatory requirements in this scenario?

 
 
 
 

Q116. In the context of AI governance, which of the following best describes the roles and responsibilities of a developer of a proprietary model? (Choose three.)

 
 
 
 
 

Q117. All of the following are included within the scope of post-deployment Al maintenance EXCEPT?

 
 
 
 

Q118. An organization is assessing the impact of four separate AI tools currently in use. Which one should it prioritize last?

 
 
 
 

Q119. Which of the following is a subcategory of Al and machine learning that uses labeled datasets to train algorithms?

 
 
 
 

Q120. A Canadian company is developing an AI solution to evaluate candidates in the course of job interviews. Before offering the AI solution in the EU market, the company must take all of the following steps EXCEPT:

 
 
 
 

Q121. Which of the following AI uses is best described as human-centric?

 
 
 
 

Q122. According to the Singapore Model Al Governance Framework, all of the following are recommended measures to promote the responsible use of Al EXCEPT?

 
 
 
 

Q123. A UK company has designed a facial recognition model to support border control. The EU AI Act would apply to the model in all of the following situations EXCEPT if:

 
 
 
 

Q124. CASE STUDY
Please use the following to answer the next question:
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.
Which of the following measures should the company adopt to best mitigate its risk of reputational harm from using the AI tool?

 
 
 
 

Q125. CASE STUDY
Please use the following to answer the next question:
A mid-size US healthcare network has decided to develop an AI solution to detect a type of cancer that is most likely to arise in adults. Specifically, the healthcare network intends to create a recognition algorithm that will perform an initial review of all imaging and then route records to a radiologist for secondary review pursuant to agreed-upon criteria (e.g., a confidence score below a threshold).
To date, the healthcare network has:
– Defined its AI ethical principles.
– Conducted discovery to identify the intended uses and success
criteria for the system.
– Established an AI risk committee.
– Assembled a cross-functional team with clear roles and
responsibilities.
– Created policies and procedures to document standards, workflows,
timelines and risk thresholds during the project.
The healthcare network intends to retain a cloud provider to host the solution. It also intends to retain a large consulting firm to supplement its small data science team and help develop the algorithm using the healthcare network’s existing data and de-identified data that is licensed from a large US clinical research partner.
In the design phase, which of the following steps is most important in gathering the data from the clinical research partner?

 
 
 
 

Q126. Scenario:
An organization wants to leverage its existing compliance structures to identify AI-specific risks as part of an ongoing data governance audit.
Which of the following compliance-related controls within an organization ismost easily adaptedto identify AI risks?

 
 
 
 

Q127. Under the NIST AI Risk Management Framework, all of the following are defined as characteristics of trustworthy AI EXCEPT:

 
 
 
 

Q128. To maintain fairness in a deployed system, it is most important to:

 
 
 
 

Q129. In accordance with the EU AI Act, for how long after a high-risk AI system has been placed on the market must the provider keep the relevant documentations at the disposal of the national competent authorities?

 
 
 
 

IAPP AIGP Exam Syllabus Topics:

Topic Details
Topic 1
  • 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.
Topic 2
  • 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 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 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.

 

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