AIGP 문제 71
CASE STUDY
Please use the following to answer the next question:
A mid-size US healthcare network has decided to develop an AI solution to detect a type of cancer that is most likely to arise in adults. Specifically, the healthcare network intends to create a recognition algorithm that will perform an initial review of all imaging and then route records to a radiologist for secondary review pursuant to agreed-upon criteria (e.g., a confidence score below a threshold).
To date, the healthcare network has:
- Defined its AI ethical principles.
- Conducted discovery to identify the intended uses and success
criteria for the system.
- Established an AI risk committee.
- Assembled a cross-functional team with clear roles and
responsibilities.
- Created policies and procedures to document standards, workflows,
timelines and risk thresholds during the project.
해당 의료 네트워크는 솔루션 호스팅을 위해 클라우드 제공업체를 선정할 예정입니다. 또한, 소규모 데이터 과학 팀을 보완하고 의료 네트워크가 보유한 기존 데이터와 미국 대형 임상 연구 파트너로부터 라이선스 받은 익명화된 데이터를 활용하여 알고리즘을 개발하는 데 도움을 줄 대형 컨설팅 회사도 고용할 계획입니다.
인공지능 솔루션 학습 및 테스트 전에 차별 가능성을 가장 효과적으로 줄일 수 있는 조치는 다음 중 무엇입니까?
Please use the following to answer the next question:
A mid-size US healthcare network has decided to develop an AI solution to detect a type of cancer that is most likely to arise in adults. Specifically, the healthcare network intends to create a recognition algorithm that will perform an initial review of all imaging and then route records to a radiologist for secondary review pursuant to agreed-upon criteria (e.g., a confidence score below a threshold).
To date, the healthcare network has:
- Defined its AI ethical principles.
- Conducted discovery to identify the intended uses and success
criteria for the system.
- Established an AI risk committee.
- Assembled a cross-functional team with clear roles and
responsibilities.
- Created policies and procedures to document standards, workflows,
timelines and risk thresholds during the project.
해당 의료 네트워크는 솔루션 호스팅을 위해 클라우드 제공업체를 선정할 예정입니다. 또한, 소규모 데이터 과학 팀을 보완하고 의료 네트워크가 보유한 기존 데이터와 미국 대형 임상 연구 파트너로부터 라이선스 받은 익명화된 데이터를 활용하여 알고리즘을 개발하는 데 도움을 줄 대형 컨설팅 회사도 고용할 계획입니다.
인공지능 솔루션 학습 및 테스트 전에 차별 가능성을 가장 효과적으로 줄일 수 있는 조치는 다음 중 무엇입니까?
AIGP 문제 72
사례 연구
다음 질문에 답하실 때 아래 내용을 참고해 주십시오.
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.
What is the best strategy to mitigate the bias uncovered in the loan applications?
다음 질문에 답하실 때 아래 내용을 참고해 주십시오.
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.
What is the best strategy to mitigate the bias uncovered in the loan applications?
AIGP 문제 73
What is the best method to apply to an AI model so that it is statistically unlikely that a specific piece of training data can be identified from a model's output?
AIGP 문제 74
다음 중 독점 AI 모델 배포에만 해당하는 문제가 아닌 것은 무엇입니까?
AIGP 문제 75
실사 이미지와 비디오를 생성할 수 있는 AI 모델을 배포할 때 가장 큰 위험은 무엇일까요?