AWS Certified AI Practitioner AIF-C01 Practice Question
A retail company plans to send customer chat logs that include credit-card numbers to an external generative AI API for sentiment analysis. Under responsible AI practices, which legal risk is the company most likely to face if it transmits the logs without first removing or masking this information?
Disclosure of sensitive customer data, resulting in a confidentiality and privacy breach.
Unexpectedly high infrastructure charges from excessive GPU usage during inference.
Model underfitting that reduces the accuracy of sentiment predictions.
Infringement of intellectual property due to reuse of copyrighted model outputs.
Because the chat logs contain personally identifiable and financial data, sending them unchanged to a third-party generative AI service can expose that information outside the company's control. This creates a confidentiality and data-privacy breach risk, potentially violating regulations such as PCI-DSS or data-protection laws. The other options describe possible problems with intellectual-property use, model accuracy, or cost management, but they do not represent the primary legal liability created by sharing unredacted customer data.
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What is PCI-DSS, and how does it apply to this scenario?
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How can sensitive data like credit-card numbers be masked in this context?
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What are the key legal regulations protecting customer privacy in AI use cases?
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What is PCI-DSS, and why is it relevant in this scenario?
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What is meant by responsible AI practices?
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How can data masking be used to prevent confidentiality breaches?
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AWS Certified AI Practitioner AIF-C01
Guidelines for Responsible AI
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