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New AIGP Exam Discount - AIGP Valid Exam Labs

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New AIGP Exam Discount - AIGP Valid Exam Labs

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IAPP AIGP Exam Syllabus Topics:
TopicDetails
Topic 1
  • Understanding How to Govern AI Deployment and Use: This section of the exam measures skills of technology deployment leads and covers the responsibilities associated with selecting, deploying, and using AI models in a responsible manner. It includes evaluating key factors and risks before deployment, understanding different model types and deployment options, and ensuring ongoing monitoring and maintenance. The domain applies to both proprietary and third-party AI models, emphasizing the importance of transparency, ethical considerations, and continuous oversight throughout the model’s operational life.
Topic 2
  • Understanding How to Govern AI Development: This section of the exam measures the skills of AI project managers and covers the governance responsibilities involved in designing, building, training, testing, and maintaining AI models. It emphasizes defining the business context, performing impact assessments, applying relevant laws and best practices, and managing risks during model development. The domain also includes establishing data governance for training and testing, ensuring data quality and provenance, and documenting processes for compliance. Additionally, it focuses on preparing models for release, continuous monitoring, maintenance, incident management, and transparent disclosures to stakeholders.
Topic 3
  • Understanding the Foundations of AI Governance: This section of the exam measures skills of AI governance professionals and covers the core concepts of AI governance, including what AI is, why governance is needed, and the risks and unique characteristics associated with AI. It also addresses the establishment and communication of organizational expectations for AI governance, such as defining roles, fostering cross-functional collaboration, and delivering training on AI strategies. Additionally, it focuses on developing policies and procedures that ensure oversight and accountability throughout the AI lifecycle, including managing third-party risks and updating privacy and security practices.
Topic 4
  • Understanding How Laws, Standards, and Frameworks Apply to AI: This section of the exam measures skills of compliance officers and covers the application of existing and emerging legal requirements to AI systems. It explores how data privacy laws, intellectual property, non-discrimination, consumer protection, and product liability laws impact AI. The domain also examines the main elements of the EU AI Act, such as risk classification and requirements for different AI risk levels, as well as enforcement mechanisms. Furthermore, it addresses the key industry standards and frameworks, including OECD principles, NIST AI Risk Management Framework, and ISO AI standards, guiding organizations in trustworthy and compliant AI implementation.

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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q74-Q79):NEW QUESTION # 74
An autonomous vehicle maker deploys an AI system whereby the car is equipped with AI that makes decisions locally, without calling in to the AI's central server.
- The AI is capable of making decisions without waiting for a response
from a remote system.
- The AI can continue to function if it temporarily loses its
connection to the central server, such as driving through tunnels or
areas where its signal is lost.
- The AI can periodically receive updates to its model from its central server.
- A subset of anonymized data can be used to train the manufacturer's
AI model, depending on user privacy settings.
The manufacturer has deployed the AI using:
  • A. A multimodal model.
  • B. An edge model.
  • C. A federated model.
  • D. A cloud model.
Answer: B
Explanation:
An edge model processes data and makes decisions locally on the device, enabling operation without continuous connection to a central server.

NEW QUESTION # 75
A French medical research center wishes to develop an AI-based system which will predict the risk of serious diseases based on the patient's genetic data. In order to do so it contracts with a tech company and provides it with patients' data previously obtained by the center during the research. To guarantee compliance when processing special categories of personal data, the medical research center must ensure that:
  • A. The AI-based system is designed for the purposes of preventive medicine.
  • B. The tech company is located in the EU and is not cloud-based.
  • C. The patients have given explicit consent to using the data.
  • D. The patients' health and genetic data is anonymized.
Answer: C
Explanation:
Processing special categories of personal data, like health and genetic data, requires explicit consent from patients to ensure compliance with data protection laws.

NEW QUESTION # 76
CASE STUDY
Please use the following answer the next question:
A local police department in the United States procured an Al system to monitor and analyze social media feeds, online marketplaces and other sources of public information to detect evidence of illegal activities (e.g., sale of drugs or stolen goods). The Al system works by surveilling the public sites in order to identify individuals that are likely to have committed a crime. It cross-references the individuals against data maintained by law enforcement and then assigns a percentage score of the likelihood of criminal activity based on certain factors like previous criminal history, location, time, race and gender.
The police department retained a third-party consultant assist in the procurement process, specifically to evaluate two finalists. Each of the vendors provided information about their system's accuracy rates, the diversity of their training data and how their system works. The consultant determined that the first vendor's system has a higher accuracy rate and based on this information, recommended this vendor to the police department.
The police department chose the first vendor and implemented its Al system. As part of the implementation, the department and consultant created a usage policy for the system, which includes training police officers on how the system works and how to incorporate it into their investigation process.
The police department has now been using the Al system for a year. An internal review has found that every time the system scored a likelihood of criminal activity at or above 90%, the police investigation subsequently confirmed that the individual had, in fact, committed a crime. Based on these results, the police department wants to forego investigations for cases where the Al system gives a score of at least 90% and proceed directly with an arrest.
What is the best reason the police department should continue to perform investigations even if the Al system scores an individual's likelihood of criminal activity at or above 90%?
  • A. Because Al systems that affect fundamental civil rights should not be fully automated.
  • B. Because investigations may uncover information relevant to sentencing.
  • C. Because investigations may identify additional individuals involved in the crime.
  • D. Because the department did not perform an impact assessment for this intended use.
Answer: A
Explanation:
The best reason for the police department to continue performing investigations even if the AI system scores an individual's likelihood of criminal activity at or above 90% is that AI systems affecting fundamental civil rights should not be fully automated. Human oversight is essential to ensure that decisions impacting civil liberties are made with due consideration of context and mitigating factors that an AI might not fully appreciate. This approach ensures fairness, accountability, and adherence to legal standards. Reference: AIGP Body of Knowledge on AI Ethics and Human Oversight.

NEW QUESTION # 77
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 marketing company and its tech provider have taken reasonable steps to govern the AI's use, including legal disclosures, impact assessments, and bias mitigation. However, the company wants to take one more step to improve governance and reduce risks related to ongoing oversight and accountability.
While the marketing agency took steps to mitigate its risks, the best additional step would be to:
  • A. Negotiate an intellectual property indemnity from the technology company
  • B. Evaluate the use of AI in the marketing industry to identify best practices
  • C. Engage a third party to lead the procurement selection process
  • D. Establish a governance committee to oversee the project
Answer: D
Explanation:
The correct answer is D. Forming a dedicated governance committee ensures continuous oversight, role clarity, and accountability throughout the AI lifecycle.
From the AIGP ILT Guide - Governance Structures:
"Organizations using AI in high-impact scenarios should establish a governance body responsible for oversight of risk, compliance, and ethical alignment." Also reflected in AI Governance in Practice Report 2024:
"Committees support cross-functional decision-making, provide guidance for updates, and maintain accountability. This is especially critical for high-stakes applications like marketing to diverse audiences." Options A, B, and C are valid supplementary actions, but D offers a long-term and systematic governance mechanism.

NEW QUESTION # 78
What type of organizational risk is associated with Al's resource-intensive computing demands?
  • A. Security risk.
  • B. People risk.
  • C. Environmental risk.
  • D. Third-party risk.
Answer: C
Explanation:
AI's resource-intensive computing demands pose significant environmental risks. High-performance computing required for training and deploying AI models often leads to substantial energy consumption, which can result in increased carbon emissions and other environmental impacts. This is particularly relevant given the growing concern over climate change and the environmental footprint of technology. Organizations need to consider these environmental risks when developing AI systems, potentially exploring more energy-efficient methods and renewable energy sources to mitigate the environmental impact.

NEW QUESTION # 79
......
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Posted at 5 hour before        Only Author  2#
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