AWS Certified AI Practitioner AIF-C01 Practice Question
A startup plans to publish blog posts created with a generative text model. Before making the posts public, which legal risk should the team evaluate to help avoid future litigation?
Generating content in several languages could require additional localization work.
Because the model was trained on public data, the team can skip any content review.
The model might output copyrighted text, leading to intellectual property infringement.
Running the model may raise cloud compute expenses beyond the project budget.
Generative models can sometimes reproduce passages that are substantially similar to or copied from works still protected by copyright. Publishing such material without permission could expose the company to intellectual property infringement claims. Higher compute costs, multilingual output, or relying on publicly available training data are important operational considerations, but they do not in themselves represent a primary legal risk.
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What is intellectual property infringement in the context of generative models?
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How can a company detect copyrighted content in generative model outputs?
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Why is using public data for training models not a guarantee of safe outputs?
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AWS Certified AI Practitioner AIF-C01
Guidelines for Responsible AI
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