Exam AIGP Course, Trustworthy AIGP Exam Content
Exam AIGP Course, Trustworthy AIGP Exam Content
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Tags: Exam AIGP Course, Trustworthy AIGP Exam Content, AIGP Reliable Exam Materials, Valid Braindumps AIGP Questions, AIGP New Practice Materials
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Trustworthy AIGP Exam Content - AIGP Reliable Exam Materials
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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q87-Q92):
NEW QUESTION # 87
All of the following may be permissible uses of an Al system under the EU Al Act EXCEPT?
- A. To implement social scoring.
- B. To manage border control.
- C. To promote equitable distribution of welfare benefits.
- D. To detect an individual's intent for law enforcement purposes.
Answer: A
Explanation:
The EU AI Act explicitly prohibits the use of AI systems for social scoring by public authorities, as it can lead to discrimination and unfair treatment of individuals based on their social behavior or perceived trustworthiness. While AI can be used to promote equitable distribution of welfare benefits, manage border control, and even detect an individual's intent for law enforcement purposes (within strict regulatory and ethical boundaries), implementing social scoring systems is not permissible under the Act due to the significant risks to fundamental rights and freedoms.
NEW QUESTION # 88
An EU bank intends to launch a multi-modal Al platform for customer engagement and automated decision-making assist with the opening of bank accounts. The platform has been subject to thorough risk assessments and testing, where it proves to be effective in not discriminating against any individual on the basis of a protected class.
What additional obligations must the bank fulfill prior to deployment?
- A. The bank must subject the Al system an adequacy decision and publish its appropriate safeguards.
- B. The bank must disclose how the Al system works under the Ell Digital Services Act.
- C. The bank must obtain explicit consent from users under the privacy Directive.
- D. The bank must disclose the use of the Al system and implement suitable measures for users to contest automated decision-making.
Answer: D
Explanation:
Under the EU regulations, particularly the GDPR, banks using AI for decision-making must inform users about the use of AI and provide mechanisms for users to contest decisions. This is part of ensuring transparency and accountability in automated processing. Explicit consent under the privacy directive (A) and disclosing under the Digital Services Act (B) are not specifically required in this context. An adequacy decision is related to data transfers outside the EU (C).
NEW QUESTION # 89
You are a privacy program manager at a large e-commerce company that uses an Al tool to deliver personalized product recommendations based on visitors' personal information that has been collected from the company website, the chatbot and public data the company has scraped from social media.
A user submits a data access request under an applicable U.S. state privacy law, specifically seeking a copy of their personal data, including information used to create their profile for product recommendations.
What is the most challenging aspect of managing this request?
- A. Some of the data subject's data is unstructured data and you cannot untangle it from the other data, including information about other individuals.
- B. The data subject's data is structured data that can be searched, compiled and reviewed only by an automated tool.
- C. Some of the visitor's data is synthetic data that the company does not have to provide to the data subject.
- D. The data subject is not entitled to receive a copy of their data because some of it was scraped from public sources.
Answer: A
Explanation:
The most challenging aspect of managing a data access request in this scenario is dealing with unstructured data that cannot be easily disentangled from other data, including information about other individuals.
Unstructured data, such as free-text inputs or social media posts, often lacks a clear structure and may be intermingled with data from multiple individuals, making it difficult to isolate the specific data related to the requester. This complexity poses significant challenges in complying with data access requests under privacy laws. Reference: AIGP Body of Knowledge on Data Subject Rights and Data Management.
NEW QUESTION # 90
What is the main purpose of accountability structures under the Govern function of the NIST Al Risk Management Framework?
- A. To empower and train appropriate cross-functional teams.
- B. To establish diverse, equitable and inclusive processes.
- C. To enable and encourage participation by external stakeholders.
- D. To determine responsibility for allocating budgetary resources.
Answer: A
Explanation:
The NIST AI Risk Management Framework's Govern function emphasizes the importance of establishing accountability structures that empower and train cross-functional teams. This is crucial because cross- functional teams bring diverse perspectives and expertise, which are essential for effective AI governance and risk management. Training these teams ensures that they are well-equipped to handle their responsibilities and can make informed decisions that align with the organization's AI principles and ethical standards. Reference:
NIST AI Risk Management Framework documentation, Govern function section.
NEW QUESTION # 91
Which of the following is a subcategory of Al and machine learning that uses labeled datasets to train algorithms?
- A. Expert systems.
- B. Supervised learning.
- C. Generative Al.
- D. Segmentation.
Answer: B
Explanation:
Supervised learning is a subcategory of AI and machine learning where labeled datasets are used to train algorithms. This process involves feeding the algorithm a dataset where the input-output pairs are known, allowing the algorithm to learn and make predictions or decisions based on new, unseen data. Reference:
AIGP BODY OF KNOWLEDGE, which describes supervised learning as a model trained on labeled data (e.
g., text recognition, detecting spam in emails).
NEW QUESTION # 92
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