REAL AIGP TORRENT & AIGP EXAM EXERCISE

Real AIGP Torrent & AIGP Exam Exercise

Real AIGP Torrent & AIGP Exam Exercise

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IAPP AIGP Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • Understanding AI Impacts and Responsible AI Principles: This topic identifies different risks that that ungoverned AI systems. The topic also describes features and principles that are essential for trustworthy and ethical AI.
Topic 3
  • 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 4
  • 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 (Q14-Q19):

NEW QUESTION # 14
In the machine learning context, feature engineering is the process of?

  • A. Converting raw data into clean data.
  • B. Developing guidelines to train and test a model.
  • C. Extracting attributes and variables from raw data.
  • D. Creating learning schema for a model apply.

Answer: C

Explanation:
In the machine learning context, feature engineering is the process of extracting attributes and variables from raw data to make it suitable for training an AI model. This step is crucial as it transforms raw data into meaningful features that can improve the model's accuracy and performance. Feature engineering involves selecting, modifying, and creating new features that help the model learn more effectively. Reference: AIGP Body of Knowledge on AI Model Development and Feature Engineering.


NEW QUESTION # 15
Which type of existing assessment could best be leveraged to create an Al impact assessment?

  • A. A privacy impact assessment.
  • B. An environmental impact assessment.
  • C. A security impact assessment.
  • D. A safety impact assessment.

Answer: A

Explanation:
A privacy impact assessment (PIA) can be effectively leveraged to create an AI impact assessment. A PIA evaluates the potential privacy risks associated with the use of personal data and helps in implementing measures to mitigate those risks. Since AI systems often involve processing large amounts of personal data, the principles and methodologies of a PIA are highly applicable and can be extended to assess broader impacts, including ethical, social, and legal implications of AI. Reference: AIGP Body of Knowledge on Impact Assessments.


NEW QUESTION # 16
An Al system that maintains its level of performance within defined acceptable limits despite real world or adversarial conditions would be described as?

  • A. Robust.
  • B. Reliable.
  • C. Reinforced.
  • D. Resilient.

Answer: D

Explanation:
An AI system that maintains its level of performance within defined acceptable limits despite real-world or adversarial conditions is described as resilient. Resilience in AI refers to the system's ability to withstand and recover from unexpected challenges, such as cyber-attacks, hardware failures, or unusual input data. This characteristic ensures that the AI system can continue to function effectively and reliably in various conditions, maintaining performance and integrity. Robustness, on the other hand, focuses on the system's strength against errors, while reliability ensures consistent performance over time. Resilience combines these aspects with the capacity to adapt and recover.


NEW QUESTION # 17
You are part of your organization's ML engineering team and notice that the accuracy of a model that was recently deployed into production is deteriorating.
What is the best first step address this?

  • A. Perform an audit of the model.
  • B. Run red-teaming exercises.
  • C. Replace the model with a previous version.
  • D. Conduct champion/challenger testing.

Answer: D

Explanation:
When the accuracy of a model deteriorates, the best first step is to conduct champion/challenger testing. This involves deploying a new model (challenger) alongside the current model (champion) to compare their performance. This method helps identify if the new model can perform better under current conditions without immediately discarding the existing model. It provides a controlled environment to test improvements and understand the reasons behind the deterioration. This approach is preferable to directly replacing the model, performing audits, or running red-teaming exercises, which may be subsequent steps based on the findings from the champion/challenger testing.
Reference: AIGP BODY OF KNOWLEDGE, sections on model performance management and testing strategies.


NEW QUESTION # 18
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.
What is the best reason for GVC to offer students the choice to utilize generative Al in limited, defined circumstances?

  • A. Toenable students to learn how to manage their time.
  • B. Toenable students to learn about performing research.
  • C. Toenable students to learn how to use Al as a supportive educational tool.
  • D. Toenable students to learn about practical applications of Al.

Answer: C

Explanation:
The best reason for GVC to offer students the choice to utilize generative AI in limited, defined circumstances is to enable students to learn how to use AI as a supportive educational tool. By integrating AI in a controlled manner, students can learn the practical applications of AI and develop skills to use AI responsibly and effectively in their educational pursuits.
Reference: The AIGP Body of Knowledge highlights the importance of teaching students about AI's practical applications and the responsible use of AI technologies. This aligns with the goal of fostering a better understanding of AI's role and its potential benefits in various contexts, including education.


NEW QUESTION # 19
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