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.
Which of the following is the most important reason to train the underwriters on the model prior to deployment?
Which type of existing assessment could best be leveraged to create an AI impact assessment?
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:
Which risk management framework/guide/standard focuses on value-based engineering methodology?
What is theprimary purposeof an AI impact assessment?
