NEW BRAINDUMPS AIGP BOOK, EXAM AIGP REVIEW

New Braindumps AIGP Book, Exam AIGP Review

New Braindumps AIGP Book, Exam AIGP Review

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Tags: New Braindumps AIGP Book, Exam AIGP Review, Training AIGP Pdf, AIGP Exam Introduction, AIGP Test Collection Pdf

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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
  • 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 3
  • Contemplating Ongoing Issues and Concerns: The topic focuses on issues around AI governance.
Topic 4
  • Implementing Responsible AI Governance and Risk Management: It explains the collaboration of major AI stakeholders in a layered approach.
Topic 5
  • 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 6
  • Understanding How Current Laws Apply to AI Systems: It focuses on laws that govern the use of artificial intelligence.

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IAPP Certified Artificial Intelligence Governance Professional (AIGP) PDF dumps are the third and most convenient format of the IAPP AIGP PDF questions prep material. This format is perfect for busy test takers who prefer to study for the IAPP Certified Artificial Intelligence Governance Professional (AIGP) exam on the go. Questions bank in the Actual4Exams IAPP AIGP Pdf Dumps is accessible via all smart devices. We also update IAPP Certified Artificial Intelligence Governance Professional (AIGP) PDF questions regularly to ensure they match with the new content of the AIGP exam.

IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q53-Q58):

NEW QUESTION # 53
Why is it important that conformity requirements are satisfied before an AI system is released into production?

  • A. To ensure the visual design is fit-for-purpose.
  • B. To guarantee interoperability of the AI system across multiple platforms and environments.
  • C. To comply with legal and regulatory standards, ensuring the AI system is safe and trustworthy.
  • D. To ensure the AI system is easy for end-users to operate.

Answer: C

Explanation:
Conformity assessmentsare a core requirement under theEU AI Actfor high-risk systems and serve to confirm that the AI meetsregulatory, safety, and ethical standardsbefore it is put into production.
From theAI Governance in Practice Report 2024:
"Conformity assessments... ensure that systems comply with legal requirements, safety criteria, and intended purpose before being placed on the market." (p. 34)
"They are a critical step to demonstrate safety and trustworthiness in AI deployment." (p. 35)


NEW QUESTION # 54
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 a 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.
What is the best strategy to mitigate the bias uncovered in the loan applications?

  • A. Document all instances of bias in the data set.
  • B. Retrain the model with data that reflects demographic parity.
  • C. Delete all gender-based data in the data set.
  • D. Procure a third-party statistical bias assessment tool.

Answer: B

Explanation:
Retraining the model with data that reflects demographic parity is the best strategy to mitigate the bias uncovered in the loan applications. This approach addresses the root cause of the bias by ensuring that the training data is representative and balanced, leading to more equitable decision-making by the AI model.
Reference: The AIGP Body of Knowledge stresses the importance of using high-quality, unbiased training data to develop fair and reliable AI systems. Retraining the model with balanced data helps correct biases that arise from historical inequalities, ensuring that the AI system makes decisions based on equitable criteria.


NEW QUESTION # 55
You asked a generative Al tool to recommend new restaurants to explore in Boston, Massachusetts that have a specialty Italian dish made in a traditional fashion without spinach and wine. The generative Al tool recommended five restaurants for you to visit.
After looking up the restaurants, you discovered one restaurant did not exist and two others did not have the dish.
This information provided by the generative Al tool is an example of what is commonly called?

  • A. Overfitting.
  • B. Prompt injection.
  • C. Model collapse.
  • D. Hallucination.

Answer: D

Explanation:
In the context of AI, particularly generative models, "hallucination" refers to the generation of outputs that are not based on the training data and are factually incorrect or non-existent. The scenario described involves the generative AI tool providing incorrect and non-existent information about restaurants, which fits the definition of hallucination. Reference: AIGP BODY OF KNOWLEDGE and various AI literature discussing the limitations and challenges of generative AI models.


NEW QUESTION # 56
Under the NIST Al Risk Management Framework, all of the following are defined as characteristics of trustworthy Al EXCEPT?

  • A. Secure and Resilient.
  • B. Accountable and Transparent.
  • C. Explainable and Interpretable.
  • D. Tested and Effective.

Answer: C

Explanation:
The NIST AI Risk Management Framework outlines several characteristics of trustworthy AI, including being secure and resilient, explainable and interpretable, and accountable and transparent. While being tested and effective is important, it is not explicitly listed as a characteristic of trustworthy AI in the NIST framework.
The focus is more on the system's ability to function safely, securely, and transparently in a way that stakeholders can understand and trust. Reference: AIGP Body of Knowledge, NIST AI RMF section.


NEW QUESTION # 57
Pursuant to the White House Executive Order of November 2023, who is responsible for creating guidelines to conduct red-teaming tests of Al systems?

  • A. Department of Homeland Security (DHS).
  • B. National Institute of Standards and Technology (NIST).
  • C. National Science and Technology Council (NSTC).
  • D. Office of Science and Technology Policy (OSTP).

Answer: B

Explanation:
The White House Executive Order of November 2023 designates the National Institute of Standards and Technology (NIST) as the responsible body for creating guidelines to conduct red-teaming tests of AI systems. NIST is tasked with developing and providing standards and frameworks to ensure the security, reliability, and ethical deployment of AI systems, including conducting rigorous red-teaming exercises to identify vulnerabilities and assess risks in AI systems.
Reference: AIGP BODY OF KNOWLEDGE, sections on AI governance and regulatory frameworks, and the White House Executive Order of November 2023.


NEW QUESTION # 58
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