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AIGP PDF Practice Q&A's Total Questions: 219
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IAPP AIGP Exam Syllabus Topics:

TopicDetails
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 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 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.

Reference: https://iapp.org/certify/aigp/

IAPP Certified Artificial Intelligence Governance Professional Sample Questions:

Which of the following arenotconsidered biometric data under U.S. privacy laws?

  • A. Walking gait
  • B. Iris scans
  • C. GPS location of a user's fitness watch
  • D. Keystroke dynamics
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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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 Al 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?

  • A. Deploy the current model and recalibrate it over time with more data.
  • B. Extend the model to multi-modal ingestion with text and images.
  • C. Refocus the algorithm to patients without cancer.
  • D. Utilize synthetic data to offset the lack of patient data.
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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Please select 3 of the 5 options below. No partial credit will be given.
All of the following are unique characteristics of AI that require a comprehensive approach to governance EXCEPT?

  • A. Automation.
  • B. Autonomy.
  • C. Adaptability.
  • D. Speed and scale.
  • E. Superintelligence.
Reveal Solution  Discussion  0

Correct Answer: A,D,E  🗳️

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Retrieval-Augmented Generation (RAG) is defined as?

  • A. Combining LLMs with private knowledge bases to improve their outputs.
  • B. Reducing computational processing requirements of the LLMs.
  • C. Applying advanced filtering techniques to the LLMs.
  • D. Fine tuning LLMs to minimize biased outputs.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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Machine learning is best described as a type of algorithm by which?

  • A. Statistical inferences are drawn from a sample with the goal of predicting human intelligence.
  • B. Systems can automatically improve from experience through predictive patterns.
  • C. Previously unknown properties are discovered in data and used to predict and make improvements in the data.
  • D. Systems can mimic human intelligence with the goal of replacing humans.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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