Einstein Generative AI & Trust
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Questions and Answers

What is the primary value that Salesforce aims to uphold while using Einstein generative AI?

  • Innovation
  • Trust (correct)
  • Cost efficiency
  • Speed
  • Which principle focuses on ensuring that model responses are verifiable and can be corroborated?

  • Empowerment
  • Accuracy (correct)
  • Transparency
  • Sustainability
  • What should organizations do before sharing LLM-generated responses with external audiences?

  • Publish immediately to save time
  • Disregard the potential for errors
  • Ensure content aligns with company values (correct)
  • Allow LLM to verify its own responses
  • How does Salesforce strive to reduce the environmental impact of its AI models?

    <p>By prioritizing accuracy and minimizing carbon footprint</p> Signup and view all the answers

    What challenge does Salesforce specifically address to ensure safety in generative AI responses?

    <p>Bias, toxicity, and harmful responses</p> Signup and view all the answers

    What is a characteristic of generative AI that users must be cautious about?

    <p>The tendency to produce fabricated or inaccurate responses</p> Signup and view all the answers

    Which of the following is NOT one of the five principles of trusted generative AI according to Salesforce?

    <p>Agility</p> Signup and view all the answers

    What is crucial to do after receiving LLM-generated content intended for customers?

    <p>Review for precision and ensure it represents your brand accurately</p> Signup and view all the answers

    Study Notes

    Einstein Generative AI & Trust

    • Salesforce prioritizes data security and accurate, safe AI experiences
    • Agreements with LLM providers (e.g., OpenAI) prevent private data retention
    • Salesforce's generative AI follows five principles for trusted AI

    Five Principles for Trusted Generative AI

    • Accuracy: Model responses backed by explanations and sources; human review recommended
    • Safety: Detects and mitigates bias, toxicity, and harmful responses
    • Transparency: Models respect data provenance, grounded in client data
    • Empowerment: Tools augment human capabilities, improve efficiency
    • Sustainability: Focus on optimized, efficient models with reduced carbon footprint

    Reviewing Generative AI Responses

    • Generative AI is a tool, not a replacement for human judgment

    • Users are responsible for any LLM-generated responses shared with customers

    • External responses should align with company values, voice, and tone

    • Focus on accuracy and safety during review

    • Accuracy: Check for factual accuracy, ensure details are correct; data up-to-date and accurate

    • Bias and Toxicity: Actively check for bias and harmful language due potential for inaccurate language present in the training data

    • Responses don't meet standards? Don't use them or re-generate. Some solutions allow editors for changes

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    Description

    This quiz explores the five principles of trusted generative AI, focusing on accuracy, safety, transparency, empowerment, and sustainability. It highlights the importance of human judgment in reviewing AI responses and discusses Salesforce's commitment to data security and ethical AI practices. > https://help.salesforce.com/s/articleView?id=sf.generative_ai_trust_overview.htm&type=5

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