EXAM IAPP AIGP COLLECTION PDF & RELIABLE AIGP TEST CRAM

Exam IAPP AIGP Collection Pdf & Reliable AIGP Test Cram

Exam IAPP AIGP Collection Pdf & Reliable AIGP Test Cram

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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
  • Implementing Responsible AI Governance and Risk Management: It explains the collaboration of major AI stakeholders in a layered approach.

IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q114-Q119):

NEW QUESTION # 114
Random forest algorithms are in what type of machine learning model?

  • A. Natural language processing.
  • B. Symbolic.
  • C. Discriminative.
  • D. Generative.

Answer: C

Explanation:
Random forest algorithms are classified as discriminative models. Discriminative models are used to classify data by learning the boundaries between classes, which is the core functionality of random forest algorithms.
They are used for classification and regression tasks by aggregating the results of multiple decision trees to make accurate predictions.
Reference: The AIGP Body of Knowledge explains that discriminative models, including random forest algorithms, are designed to distinguish between different classes in the data, making them effective for various predictive modeling tasks.


NEW QUESTION # 115
All of the following are common optimization techniques in deep learning to determine weights that represent the strength of the connection between artificial neurons EXCEPT?

  • A. Backpropagation, which starts from the last layer working backwards.
  • B. Momentum, which improves the convergence speed and stability of neural network training.
  • C. Autoregression, which analyzes and makes predictions about time-series data.
  • D. Gradient descent, which initially sets weights arbitrary values, and then at each step changes them.

Answer: C

Explanation:
Autoregression is not a common optimization technique in deep learning to determine weights for artificial neurons. Common techniques include gradient descent, momentum, and backpropagation. Autoregression is more commonly associated with time-series analysis and forecasting rather than neural network optimization.
Reference: AIGP BODY OF KNOWLEDGE, which discusses common optimization techniques used in deep learning.


NEW QUESTION # 116
A UK company has designed a facial recognition model to support border control.
The EU AI Act would apply to the model in all of the following situations EXCEPT if?

  • A. The model was released under an open source license.
  • B. The model was trained by an EU company.
  • C. The model is deployed at an EU border checkpoint.
  • D. The model is deployed at UK border checkpoints.

Answer: D

Explanation:
TheEU AI Actapplies extraterritorially, meaning it affects entitiesoutside the EUwhen their AI systems impact individuals within the EU. However, it doesnotapply to systems that are developed, sold, or used entirely outside of the EU-such as in theUK, unless they affect the EU market or individuals.
From theAI Governance in Practice Report 2024:
"The act imposes regulatory obligations... depending on their capabilities, reach and computing power, certain GPAI systems are considered to present systemic risk and attract broadly similar obligations to those applicable to high-risk AI systems." (p. 7)
"The EU AI Act is the world's first comprehensive AI regulation... requirements apply to providers, deployers, importers, and distributors of AI systems when such systems are placed on the EU market." (p. 7-8) Thus:
* A. Open source releasedoes not exclude applicability if deployed in the EU.
* B. Deployment at an EU borderclearly invokes jurisdiction.
* D. Training by an EU companycreates jurisdictional links.
* C. Deployment only at UK checkpoints, withno EU use or impact, isoutside scope.


NEW QUESTION # 117
Training data is best defined as a subset of data that is used to?

  • A. Enable a model to detect and learn patterns.
  • B. Detect the initial sources of biases to mitigate prior to deployment.
  • C. Fine-tune a model to improve accuracy and prevent overfitting.
  • D. Resemble the structure and statistical properties of production data.

Answer: A

Explanation:
Training data is used to enable a model to detect and learn patterns. During the training phase, the model learns from the labeled data, identifying patterns and relationships that it will later use to make predictions on new, unseen data. This process is fundamental in building an AI model's capability to perform tasks accurately. Reference: AIGP Body of Knowledge on Model Training and Pattern Recognition.


NEW QUESTION # 118
All of the following are penalties and enforcements outlined in the EU Al Act EXCEPT?

  • A. Fines for violations of banned Al applications will be €35 million or 7% global annual turnover (whichever is higher).
  • B. Rules on General Purpose Al will apply after 6 months as a specific provision.
  • C. Fines for SMEs and startups will be proportionally capped.
  • D. The Al Pact will act as a transitional bridge until the Regulations are fully enacted.

Answer: D

Explanation:
The EU AI Act outlines specific penalties and enforcement mechanisms to ensure compliance with its regulations. Among these, fines for violations of banned AI applications can be as high as €35 million or 7% of the global annual turnover of the offending organization, whichever is higher. Proportional caps on fines are applied to SMEs and startups to ensure fairness. General Purpose AI rules are to apply after a 6-month period as a specific provision to ensure that stakeholders have adequate time to comply. However, there is no provision for an "AI Pact" acting as a transitional bridge until the regulations are fully enacted, making option C the correct answer.


NEW QUESTION # 119
......

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