Thank you for visiting When working on a deliverable with a generative AI tool what are the best practices to ensure data protection Select all that apply A Never. This page is designed to guide you through key points and clear explanations related to the topic at hand. We aim to make your learning experience smooth, insightful, and informative. Dive in and discover the answers you're looking for!
Answer :
Final answer:
To ensure data protection when using generative AI tools, never input sensitive client information without proper approval, avoid submitting entire deliverables for proofreading, and always verify the information's accuracy. These practices help safeguard sensitive data and ensure reliable outputs. Protecting data should be a priority during such endeavors.
Explanation:
Best Practices for Data Protection with Generative AI Tools
When working on a deliverable with a generative AI tool, ensuring data protection is crucial. Here are some best practices:
- Never input Accenture or client information into a third-party generative AI tool unless you obtain approval from the Generative AI and Language Model Center of Excellence. This is essential to protect sensitive information and comply with company policies.
- Do not put the entire deliverable into the tool for proofreading. Instead, choose specific sections that do not contain confidential information, as this reduces the risk of data exposure.
- Verify the accuracy and reliability of the information. AI-generated content can have errors, so always cross-check and validate the information before including it in your deliverable.
By following these guidelines, you can help ensure that you maintain data security while using generative AI tools.
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