According to the AWS responsible AI documentation, Amazon SageMaker Clarify specifically assists in mitigating bias by detecting potential bias during data preparation, after model training, and in deployed models by examining specific attributes.
AWS AI Service Cards act as a single source of information on intended use cases, limitations, responsible AI design choices, and performance optimization best practices for AWS AI services and models.
Amazon Bedrock is a fully managed service designed to build and scale generative AI applications by offering secure, enterprise-grade access to more than 100 high-performing foundation models from industry-leading providers such as Amazon, Anthropic, DeepSeek, Moonshot AI, MiniMax, and OpenAI. Additionally, Amazon Bedrock provides capabilities to customize these models to improve performance and quality for specific customer use cases.
Amazon Bedrock is a fully managed service designed for secure, enterprise-grade access to over 100 high-performing foundation models from leading providers (including Amazon, Anthropic, DeepSeek, Moonshot AI, MiniMax, and OpenAI). It also enables developers to customize foundation models to improve performance and quality for specific enterprise use cases.
A financial organization is preparing to deploy a new credit scoring machine learning model. The compliance team requires a solution that can specifically mitigate bias by detecting potential bias during data preparation, after model training, and in the deployed model. Which AWS service or feature should they use to meet these requirements?
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