AWS Certified AI Practitioner AIF-C01 Practice Question
A retailer plans to publish product descriptions that are written automatically by a generative AI model. Leaders are worried the model could invent attributes the products do not actually possess. Which risk does this concern highlight?
Loss of customer trust caused by misleading model outputs
Copyright infringement because the text might match protected content
Unexpected increases in cloud spending for model inference
Accidental exposure of personally identifiable information (PII) in training data
If the model produces descriptions that are inaccurate or misleading, a phenomenon known as hallucination, customers can feel deceived and lose confidence in the retailer's brand. This situation directly highlights the risk of losing customer trust. While the other options are valid risks associated with generative AI-such as copyright infringement, accidental data exposure, and unexpected costs-they are not the primary risk related to a model inventing false product attributes.
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What is hallucination in generative AI?
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How can retailers mitigate hallucination in generative AI outputs?
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What are the consequences of generative AI hallucination for businesses?
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What is hallucination in generative AI models?
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How can businesses prevent customer trust loss due to AI hallucinations?
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What other risks are associated with generative AI in retail scenarios?
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AWS Certified AI Practitioner AIF-C01
Guidelines for Responsible AI
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