FIRST-HAND IAPP AIGP CERTIFICATION DUMP - AIGP IAPP CERTIFIED ARTIFICIAL INTELLIGENCE GOVERNANCE PROFESSIONAL

First-hand IAPP AIGP Certification Dump - AIGP IAPP Certified Artificial Intelligence Governance Professional

First-hand IAPP AIGP Certification Dump - AIGP IAPP Certified Artificial Intelligence Governance Professional

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Tags: AIGP Certification Dump, Exam AIGP Preview, Exam AIGP Syllabus, PDF AIGP Cram Exam, Valid AIGP Test Topics

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IAPP AIGP Exam Syllabus Topics:

TopicDetails
Topic 1
  • Understanding the Existing and Emerging AI Laws and Standards: This topic discusses global AI-specific laws such as the EU AI Act and Canada’s Bill C-27.
Topic 2
  • Understanding the AI Development Life Cycle: The topic outlines the context in which AI risks are managed.
Topic 3
  • Understanding the Foundations of Artificial Intelligence: This topic defines AI and machine learning. It also provides an overview of the different types of AI systems and their use cases.
Topic 4
  • Contemplating Ongoing Issues and Concerns: The topic focuses on issues around AI governance.
Topic 5
  • Implementing Responsible AI Governance and Risk Management: It explains the collaboration of major AI stakeholders in a layered approach.

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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q26-Q31):

NEW QUESTION # 26
Which stakeholder is responsible for lawful collection of data for the training of the foundational AI model?

  • A. The tech company.
  • B. The data aggregator.
  • C. The marketing agency's client.
  • D. The marketing agency.

Answer: B

Explanation:
Data aggregators are third parties that collect and license data from various sources. They are responsible for ensuring thelawful collectionandproper usage rightsof the data they distribute - especially when such data is used to train foundational AI models.
From theAI Governance in Practice Report 2024:
"As organizations have neither proximity to how third-party data was first collected nor direct control over the data governance practices of third parties, an organization can benefit from carrying out its own legal due diligence and third-party risk management." (p. 19)
"Legal due diligence may include verification of the personal data's lawful collection by the databroker..." (p.
19)
This confirms thatdata aggregatorsbear the legal and ethical burden to verify that data has been lawfully collected and is appropriately licensed for use, including in AI training.
* A. The marketing agencyandD. its clientmay use data, but they rely on upstream providers for its lawful origin.
* B. The tech companymay train the model but depends on lawful sourcing by data aggregators.


NEW QUESTION # 27
CASE STUDY
Please use the following answer the next question:
Good Values Corporation (GVC) is a U.S. educational services provider that employs teachers to create and deliver enrichment courses for high school students. GVC has learned that many of its teacher employees are using generative Al to create the enrichment courses, and that many of the students are using generative Al to complete their assignments.
In particular, GVC has learned that the teachers they employ used open source large language models ("LLM") to develop an online tool that customizes study questions for individual students. GVC has also discovered that an art teacher has expressly incorporated the use of generative Al into the curriculum to enable students to use prompts to create digital art.
GVC has started to investigate these practices and develop a process to monitor any use of generative Al, including by teachers and students, going forward.
All of the following may be copyright risks from teachers using generative Al to create course content EXCEPT?

  • A. Generative Al is generally trained using intellectual property owned by third parties.
  • B. Students must expressly consent to this use of generative Al.
  • C. Generative Al often creates content without attribution.
  • D. Content created by an LLM may be protectable under U.S. intellectual property law.

Answer: B

Explanation:
All of the options listed may pose copyright risks when teachers use generative AI to create course content, except for students must expressly consent to this use of generative AI. While obtaining student consent is essential for ethical and privacy reasons, it does not directly relate to copyright risks associated with the creation and use of AI-generated content.
Reference: The AIGP Body of Knowledge discusses the importance of addressing intellectual property (IP) risks when using AI-generated content. Copyright risks are typically associated with the use of third-party data and the lack of attribution, rather than the consent of users.


NEW QUESTION # 28
When monitoring the functional performance of a model that has been deployed into production, all of the following are concerns EXCEPT?

  • A. Feature drift.
  • B. Data loss.
  • C. Model drift.
  • D. System cost.

Answer: D

Explanation:
When monitoring the functional performance of a model deployed into production, concerns typically include feature drift, model drift, and data loss. Feature drift refers to changes in the input features that can affect the model's predictions. Model drift is when the model's performance degrades over time due to changes in the data or environment. Data loss can impact the accuracy and reliability of the model. However, system cost, while important for budgeting and financial planning, is not a direct concern when monitoring the functional performance of a deployed model. Reference: AIGP Body of Knowledge on Model Monitoring and Maintenance.


NEW QUESTION # 29
What is the key feature of Graphical Processing Units (GPUs) that makes them well-suited to running Al applications?

  • A. GPUs can run every task on a computer, making them more robust than CPUs.
  • B. The number of transistors on GPUs doubles every two years, making thechips smaller and lighter.
  • C. GPUs can access memory quickly, resulting in lower latency than CPUs.
  • D. GPUs run many tasks concurrently, resulting in faster processing.

Answer: D

Explanation:
GPUs (Graphical Processing Units) are well-suited to running AI applications due to their ability to run many tasks concurrently, which significantly enhances processing speed. This parallel processing capability makes GPUs ideal for handling the large-scale computations required in AI and deep learning tasks. Reference: AIGP BODY OF KNOWLEDGE, which explains the importance of compute infrastructure in AI applications.


NEW QUESTION # 30
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. Be banned under the EU Al Act.
  • C. Require a detailed conformity assessment.
  • 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 # 31
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