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| Section | Objectives |
|---|---|
| Foundations of AI Systems and Governance | - Governance principles and accountability
|
| AI Lifecycle Governance Implementation | - Operational governance controls
|
| Regulatory and Legal Frameworks for AI | - Global AI governance regulations
|
| AI Risk Management and Impact Assessment | - Risk identification and mitigation
|
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NEW QUESTION # 55
CASE STUDY
Please use the following to answer the next question:
A leading insurance provider that offers a range of coverage options to individuals has decided to utilize AI to streamline and improve its customer acquisition and underwriting process, including the accuracy and efficiency of pricing policies. The company has engaged a cloud provider to utilize and fine-tune its pre-trained, general purpose large language model ("LLM").
The company intends to use its historical customer data - including applications, policies and claims - and proprietary pricing and risk strategies to provide an initial qualification assessment of potential customers, which would then be routed to a human underwriter for final review.
The company and the cloud provider have completed training and testing the LLM, performed a readiness assessment, and made the decision to deploy the LLM into production. They have designated an internal compliance team to monitor the model during the first month, specifically to evaluate the accuracy, fairness and reliability of its output.
After the first month in production, the company realizes that the LLM declines a higher percentage of women's applications.
The best approach to enable a customer who wants information on the AI model's parameters for underwriting purposes is to provide:
Answer: D
Explanation:
Providing a transparency notice informs customers about how the AI model's parameters affect underwriting decisions, meeting regulatory and ethical requirements for explainability.
NEW QUESTION # 56
CASE STUDY
Please use the following to answer the next question:
Good Values Corporation (GVC) is a U.S. educational services provider that employs teachers to create and deliver enrichment courses for high school students. GVC has learned that many of its teacher employees are using generative AI to create the enrichment courses, and that many of the students are using generative AI to complete their assignments.
In particular, GVC has learned that the teachers they employ used open source large language models ("LLM") to develop an online tool that customizes study questions for individual students.
GVC has also discovered that an art teacher has expressly incorporated the use of generative AI into the curriculum to enable students to use prompts to create digital art.
GVC has started to investigate these practices and develop a process to monitor any use of generative AI, including by teachers and students, going forward.
What is the best reason for GVC to offer students the choice to utilize generative AI in limited, defined circumstances?
Answer: D
Explanation:
Allowing limited use of generative AI helps students learn how to use AI responsibly and effectively as a supportive tool in their education.
NEW QUESTION # 57
To maintain fairness in a deployed system, it is most important to?
Answer: C
Explanation:
To maintain fairness in a deployed system, it is crucial to monitor for data drift that may affect performance and accuracy. Data drift occurs when the statistical properties of the input data change over time, which can lead to a decline in model performance. Continuous monitoring and updating of the model with new data ensure that it remains fair and accurate, adapting to any changes in the data distribution. Reference: AIGP Body of Knowledge on Post-Deployment Monitoring and Model Maintenance.
NEW QUESTION # 58
Which of the following is a subcategory of Al and machine learning that uses labeled datasets to train algorithms?
Answer: A
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 # 59
Retrieval-Augmented Generation (RAG) is defined as:
Answer: B
Explanation:
RAG integrates large language models with external or private knowledge bases so the model can retrieve relevant information and generate more accurate, context-aware outputs.
NEW QUESTION # 60
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