IAPP AIGP Actual Tests : IAPP Certified Artificial Intelligence Governance Professional

CASE STUDY
Please use the following answer the next question:
ABC Corp, is a leading insurance provider offering a range of coverage options to individuals. ABC has decided to utilize artificial intelligence to streamline and improve its customer acquisition and underwriting process, including the accuracy and efficiency of pricing policies.
ABC has engaged a cloud provider to utilize and fine-tune its pre-trained, general purpose large language model ("LLM"). In particular, ABC 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 .. human underwriter for final review.
ABC 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. ABC has 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, ABC realizes that the LLM declines a higher percentage of women's loan applications due primarily to women historically receiving lower salaries than men.
During the first month when ABC monitors the model for bias, it is most important to?

• A. Analyze the quality of the training and testing data.
• B. Seek approval from management for any changes to the model.
• C. Compare the results to human decisions prior to deployment.
• D. Continue disparity testing.

A company initially intended to use a large data set containing personal information to train an Al model. After consideration, the company determined that it can derive enough value from the data set without any personal information and permanently obfuscated all personal data elements before training the model.
This is an example of applying which privacy-enhancing technique (PET)?

• A. Federated learning.
• B. Pseudonymization.
• C. Differential privacy.
• D. Anonymization.

Scenario:
A U.S.-based AI governance professional is evaluating resources from the National Institute of Standards and Technology (NIST) to guide the organization's AI risk assessment strategy. They are particularly interested in programs focused on assessing AI-specific impacts.
The main purpose of NIST'sAssessing Risks and Impacts of AI (ARIA)program is to:

• A. Provide a suite of resources to manage risks
• B. Offer a regulatory sandbox for risk reporting
• C. Promote interoperability across AI systems
• D. Pilot new standards for AI red-teaming

You asked a generative Al tool to recommend new restaurants to explore in Boston, Massachusetts that have a specialty Italian dish made in a traditional fashion without spinach and wine. The generative Al tool recommended five restaurants for you to visit.
After looking up the restaurants, you discovered one restaurant did not exist and two others did not have the dish.
This information provided by the generative Al tool is an example of what is commonly called?

• A. Prompt injection.
• B. Hallucination.
• C. Model collapse.
• D. Overfitting.

A company deploys an AI model for fraud detection in online transactions. During its operation, the model begins to exhibit high rates of false positives, flagging legitimate transactions as fraudulent.
Which is the best step the company should take to address this development?

• A. Deactivate the model until an assessment is made.
• B. Maintain records of all false positives.
• C. Conduct training for customer service teams to handle flagged transactions.
• D. Dedicate more resources to monitor the model.