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| Topic | Details |
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| Topic 1 | - 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.
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| Topic 2 | - 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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| Topic 3 | - 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.
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| Topic 4 | - 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.
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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q129-Q134):
NEW QUESTION # 129
All of the following are commonly adopted processes and policies in reducing potential risks introduced by third-party AI tools or applications EXCEPT:
- A. Requiring an independent third-party bias audit for third-party generative AI tools.
- B. Including clauses in the procurement agreement for buyers of generative AI tools to put certain liabilities on the tool supplier.
- C. Allowing publicly available information and personally identifiable information (pii) to be incorporated into the prompt.
- D. Requiring new use cases of the generative AI tools or applications to be reviewed and approved by the generative AI governance body.
Answer: C
Explanation:
Allowing publicly available information and personally identifiable information to be incorporated into prompts increases risk rather than reducing it, making it the least aligned with common risk- mitigation practices for third-party AI tools.
NEW QUESTION # 130
CASE STUDY
Please use the following to answer the next question:
A local police department in the United States procured an AI 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 AI system works by surveying 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 to 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 AI 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 AI 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 AI system gives a score of at least 90% and proceed directly with an arrest.
Which AI risk would NOT have been identified during the procurement process based on the categories of information requested by the third-party consultant?
- A. Security.
- B. Explainability.
- C. Discrimination.
- D. Accuracy.
Answer: A
Explanation:
The consultant evaluated accuracy, training data diversity (related to discrimination), and system workings (explainability), but security risks were not assessed during procurement.
NEW QUESTION # 131
The White House Executive Order from November 2023 requires companies that develop dual-use foundation models to provide reports to the federal government about all of the following EXCEPT?
- A. Any environmental impact study for each dual-use foundation model.
- B. The physical and cybersecurity protection measures of their dual-use foundation models.
- C. Any current training or development of dual-use foundation models.
- D. The results of red-team testing of each dual-use foundation model.
Answer: A
Explanation:
The White House Executive Order from November 2023 requires companies developing dual-use foundation models to report on their current training or development activities, the results of red-team testing, and the physical and cybersecurity protection measures. However, it does not mandate reports on environmental impact studies for each dual-use foundation model. While environmental considerations are important, they are not specified in this context as a reporting requirement under this Executive Order.
NEW QUESTION # 132
Which of the following use cases would be best served by a non-AI solution?
- A. A business analyst wants to forecast future cost overruns and underruns.
- B. A customer service agency wants automate answers to common questions.
- C. A non-profit wants to develop a social media presence.
OB. An e-commerce provider wants to make personalized recommendations.
Answer: C
Explanation:
Developing a social media presence for a non-profit is best served by non-AI solutions. This task primarily involves content creation, community engagement, and strategic planning, which are effectively managed by human expertise and traditional marketing tools. AI is more suitable for tasks requiring automation, large-scale data analysis, and personalized recommendations, such as e-commerce personalization, forecasting cost overruns, or automating customer service responses. Reference: AIGP Body of Knowledge on AI Use Cases and Applications.
NEW QUESTION # 133
A leading software development company wants to integrate AI-powered chatbots into their customer service platform. After researching various AI models in the market which have been developed by third party developers, they're considering two options:
Option A - an open-source language model trained on a vast corpus of text data and capable of being trained to respond to natural language inputs.
Option B - a proprietary, generative AI model pre-trained on large data sets, which uses transformer-based architectures to generate human-like responses based on multimodal user input.
Option A would be the best choice for the company because:
- A. It can handle voice commands and is more suitable for phone-based customer support.
- B. It may be better suited for applications requiring customization.
- C. It is built for large-scale, complex dialogues and would be more effective in handling high-volume customer inquiries.
- D. It is less expensive to run.
Answer: B
Explanation:
Open-source models can be customized extensively, making them better suited for applications requiring specific adaptations.
NEW QUESTION # 134
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