100% PASS-RATE AIGP TEST CRAM & LEADING OFFER IN QUALIFICATION EXAMS & FANTASTIC AIGP: IAPP CERTIFIED ARTIFICIAL INTELLIGENCE GOVERNANCE PROFESSIONAL

100% Pass-Rate AIGP Test Cram & Leading Offer in Qualification Exams & Fantastic AIGP: IAPP Certified Artificial Intelligence Governance Professional

100% Pass-Rate AIGP Test Cram & Leading Offer in Qualification Exams & Fantastic AIGP: IAPP Certified Artificial Intelligence Governance Professional

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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 How Current Laws Apply to AI Systems: It focuses on laws that govern the use of artificial intelligence.
Topic 3
  • Contemplating Ongoing Issues and Concerns: The topic focuses on issues around AI governance.
Topic 4
  • 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.

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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q26-Q31):

NEW QUESTION # 26
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 is deployed at an EU border checkpoint.
  • C. The model is deployed at UK border checkpoints.
  • D. The model was trained by an EU company.

Answer: C

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 # 27
Scenario:
An organization is developing a powerful general-purpose AI (GPAI) model that has systemic impact. The compliance team is assessing what legal obligations apply under the EU AI Act.
Under the EU AI Act, which of the following compliance actions applies only to General Purpose AI models with systemic risk?

  • A. Maintaining up-to-date technical documentation, including testing details
  • B. Publishing a detailed summary of the data used to train the model
  • C. Making information available to downstream providers who integrate the model into their AI systems
  • D. Implementing an intellectual property policy to comply with EU copyright laws

Answer: B

Explanation:
The correct answer is A. Only GPAI models with systemic risk must publish a detailed summary of training data to meet transparency and accountability standards under the EU AI Act.
From the AI Governance in Practice Report 2024 (EU AI Act Section):
"For GPAI systems with systemic risk, providers must publish sufficiently detailed summaries of the content used to train the model." Also, the AIGP ILT Guide confirms:
"The obligation to disclose summaries of training data applies only to systemic-risk GPAI models, not all general-purpose models or high-risk systems." This unique requirement is part of the Act's effort to increase transparency and auditability for powerful foundational models.


NEW QUESTION # 28
Under the NIST Al Risk Management Framework, all of the following are defined as characteristics of trustworthy Al EXCEPT?

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

Answer: B

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 # 29
Which risk management framework/guide/standard focuses on value-based engineering methodology?

  • A. ISO/IEC Guide 51 (Safety).
  • B. IEEE 7000-2021 Standard Model Process for Addressing Ethical Concerns during System Design.
  • C. ISO 31000 Guidelines (Risk Management).
  • D. Council of Europe Human Rights, Democracy, and the Rule of Law Assurance Framework (HUDERIA) for Al Systems.

Answer: B

Explanation:
The IEEE 7000-2021 Standard focuses on a value-based engineering methodology for addressing ethical concerns during system design. This standard guides engineers and organizations in integrating ethical considerations into the design and development processes of AI systems, ensuring that these technologies are developed responsibly and align with human values. Reference: AIGP Study Material, section on risk management frameworks and standards.


NEW QUESTION # 30
CASE STUDY
A global marketing agency is adapting a large language model ("LLM") to generate content for an upcoming marketing campaign for a client's new product: a hard hat designed for construction workers of any gender to better protect them from head injuries.
The marketing agency is accessing the LLM through an application programming interface ("API") developed by a third-party technology company. They want to generate text to be used for targeted advertising communications that highlight the benefits of the hard hat to potential purchasers. Both the marketing agency and the technology company have taken reasonable steps to address Al governance.
The marketing company has:
* Entered into a contract with the technology company with suitable representations and warranties.
* Completed an impact assessment on the LLM for this intended use.
* Built technical guidance on how to measure and mitigate bias in the LLM.
* Enabled technical aspects of transparency, explainability, robustness and privacy.
* Followed applicable regulatory requirements.
* Created specific legal statements and disclosures regarding the use of the Al on its client's advertising.
The technology company has:
* Provided guidance and resources to developers to address environmental concerns.
* Build technical guidance on how to measure and mitigate bias in the LLM.
* Provided tools and resources to measure bias specific to the LLM.
* Enabled technical aspects of transparency, explainability, robustness and privacy.
* Mapped and mitigated potential societal harms and large-scale impacts.
* Followed applicable regulatory requirements and industry standards.
* Created specific legal statements and disclosures regarding the LLM. including with respect to IP and rights to data.
The agency has taken governance actions such as:
* Conducting an impact assessment
* Providing legal disclosures
* Enabling bias mitigation and explainability
* Complying with regulatory requirements
Which of the following should be included in the marketing company's disclosures about the use of the LLM EXCEPT?

  • A. Compliance with law
  • B. Intended purpose
  • C. Acknowledgement of limitations
  • D. Proprietary methods

Answer: D

Explanation:
The correct answer is B - Proprietary methods. While transparency is important, organizations are not obligated to disclose proprietary algorithms, methods, or trade secrets in public disclosures.
From the AIGP Body of Knowledge - Transparency & Disclosures:
"AI system users should disclose the purpose, capabilities, limitations, and applicable legal context-but not sensitive IP." AI Governance in Practice Report 2024 (Transparency Section) states:
"Disclosure requirements balance public understanding with the need to protect proprietary business interests.
Proprietary training methods are not expected to be disclosed."
Thus, while it's best practice to disclose the intended purpose, legal compliance, and system limitations, internal proprietary techniques are usually excluded.


NEW QUESTION # 31
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