2025 PASS-SURE IAPP TRAINING AIGP KIT

2025 Pass-Sure IAPP Training AIGP Kit

2025 Pass-Sure IAPP Training AIGP Kit

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The IAPP AIGP certification exam offers a great opportunity to advance your career. With the IAPP Certified Artificial Intelligence Governance Professional certification exam beginners and experienced professionals can demonstrate their expertise and knowledge. After passing the IAPP Certified Artificial Intelligence Governance Professional (AIGP) exam you can stand out in a crowded job market. The AIGP certification exam shows that you have taken the time and effort to learn the necessary skills and have met the standards in the market.

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IAPP AIGP Exam Syllabus Topics:

TopicDetails
Topic 1
  • Understanding the AI Development Life Cycle: The topic outlines the context in which AI risks are managed.
Topic 2
  • Contemplating Ongoing Issues and Concerns: The topic focuses on issues around AI governance.
Topic 3
  • Implementing Responsible AI Governance and Risk Management: It explains the collaboration of major AI stakeholders in a layered approach.
Topic 4
  • Understanding the Existing and Emerging AI Laws and Standards: This topic discusses global AI-specific laws such as the EU AI Act and copyright’s Bill C-27.
Topic 5
  • Understanding How Current Laws Apply to AI Systems: It focuses on laws that govern the use of artificial intelligence.
Topic 6
  • 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.

IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q12-Q17):

NEW QUESTION # 12
A Canadian company is developing an Al solution to evaluate candidates in the course of job interviews.
Before offering the Al solution in the EU market, the company must take all of the following steps EXCEPT?

  • A. Establish a risk and quality management system.
  • B. Register the Al solution in a public EU database.
  • C. Draw up technical documentation and instructions for use.
  • D. Engage a third-party auditor to perform a bias audit.

Answer: B

Explanation:
Before offering an AI solution in the EU market, a Canadian company must take several steps to comply with the EU AI Act. These steps include establishing a risk and quality management system (B), engaging a third-party auditor to perform a bias audit (C), and drawing up technical documentation and instructions for use (D). However, there is no requirement to register the AI solution in a public EU database (A). This registration step is not specified as part of the compliance requirements under the EU AI Act for such solutions.


NEW QUESTION # 13
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.
Which of the following risks should be of the highest concern to individual teachers using generative Al to ensure students learn the course material?

  • A. Technical complexity.
  • B. Financial cost.
  • C. Copyright infringement.
  • D. Model accuracy.

Answer: D

Explanation:
The highest concern for individual teachers using generative AI to ensure students learn the course material is model accuracy. Ensuring that the AI-generated content is accurate and relevant to the curriculum is crucial for effective learning. If the AI model produces inaccurate or irrelevant content, it can mislead students and hinder their understanding of the subject matter.
Reference: According to the AIGP Body of Knowledge, one of the core risks posed by AI systems is the accuracy of the data and models used. Ensuring the accuracy of AI-generated content is essential for maintaining the integrity of the educational material and achieving the desired learning outcomes.


NEW QUESTION # 14
CASE STUDY
Please use the following answer the next question:
ABC Corp, is a leading insurance provider offering a range of coverage options to individuals. ABC has decided to utilize artificial intelligence to streamline and improve its customer acquisition and underwriting process, including the accuracy and efficiency of pricing policies.
ABC has engaged a cloud provider to utilize and fine-tune its pre-trained, general purpose large language model ("LLM"). In particular, ABC intends to use its historical customer data-including applications, policies, and claims-and proprietary pricing and risk strategies to provide an initial qualification assessment of potential customers, which would then be routed tA. human underwriter for final review.
ABC and the cloud provider have completed training and testing the LLM, performed a readiness assessment, and made the decision to deploy the LLM into production. ABC has designated an internal compliance team to monitor the model during the first month, specifically to evaluate the accuracy, fairness, and reliability of its output. After the first month in production, ABC realizes that the LLM declines a higher percentage of women's loan applications due primarily to women historically receiving lower salaries than men.
Each of the following steps would support fairness testing by the compliance team during the first month in production EXCEPT?

  • A. Providing the loan applicants with information about the model capabilities and limitations.
  • B. Using tools to help understand factors that may account for differences in decision-making.
  • C. Identifying if additional training data should be collected for specific demographic groups.
  • D. Validating a similar level of decision-making across different demographic groups.

Answer: A

Explanation:
Providing the loan applicants with information about the model capabilities and limitations would not directly support fairness testing by the compliance team. Fairness testing focuses on evaluating the model's decisions for biases and ensuring equitable treatment across different demographic groups, rather than informing applicants about the model.
Reference: The AIGP Body of Knowledge outlines that fairness testing involves technical assessments such as validating decision-making consistency across demographics and using tools to understand decision factors.
While transparency to applicants is important for ethical AI use, it does not contribute directly to the technical process of fairness testing.


NEW QUESTION # 15
What is the key feature of Graphical Processing Units (GPUs) that makes them well-suited to running Al applications?

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

Answer: B

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 # 16
Which of the following elements of feature engineering is most important to mitigate the potential bias in an Al system?

  • A. Feature validation.
  • B. Feature importance analysis.
  • C. Feature selection.
  • D. Feature transformation.

Answer: C

Explanation:
Feature selection is the most important element of feature engineering to mitigate potential bias in an AI system. This process involves choosing the most relevant and representative features from the data set, which directly affects the model's performance and fairness. By carefully selecting features, data scientists can reduce the influence of biased or irrelevant attributes, ensuring that the AI system is more accurate and equitable. Proper feature selection helps in eliminating biases that might stem from socio-demographic factors or other sensitive variables, leading to a more balanced and fair AI model. Reference: AIGP Body of Knowledge on Fairness in AI and Feature Engineering.


NEW QUESTION # 17
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