AI Incident Public Disclosure: When and How to Tell the World

End-of-lesson check

10 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-ethics-safety-AI-incident-disclosure-adults

1. What is the main idea of "AI Incident Public Disclosure: When and How to Tell the World"?

   1. Some AI failures harm users and warrant public disclosure.
   2. Use AI as the final authority for the whole decision
   3. Avoid checking the answer once it sounds polished
   4. Focus only on speed instead of judgment

2. Which concept is most central to "AI Incident Public Disclosure: When and How to Tell the World"?

   1. responsible AI
   2. incident disclosure
   3. stakeholder communication
   4. regulatory

3. Which use of AI fits this topic best?

   1. Substitute disclosure for actually fixing the underlying issue
   2. Let the AI decide what matters without your review
   3. Pre-define the categories of AI incident that warrant disclosure (systematic bias, safety failure, harmful capability, data exposure)
   4. Use the answer before checking whether it fits the situation

4. Which limitation should you watch for in this topic?

   1. Pre-define the categories of AI incident that warrant disclosure (systematic bias, safety failure, harmful capability, data exposure)
   2. Explain the topic in plain language
   3. Organize a draft for human review
   4. Substitute disclosure for actually fixing the underlying issue

5. What should a careful learner remember about "AI incident disclosure framework"?

   1. Use AI to draft or organize ideas about incident disclosure, then verify before acting.
   2. Skip the context so the tool can guess faster
   3. Treat the output as private even after sharing it online
   4. Use the answer without checking the source

6. You want to use AI after this lesson. What is the safest next step?

   1. Act immediately because the AI answer is written clearly
   2. AI cannot make the human values or safety decision for you.
   3. Hide uncertainty so the final answer looks cleaner
   4. Use private or sensitive details before checking permission

7. How should AI output about incident disclosure be treated?

   1. As proof that no other source is needed
   2. As a replacement for context, consent, or expert review
   3. As a draft or helper output that still needs human judgment and verification
   4. As something that becomes correct when it sounds confident

8. Name one way to verify an AI answer about incident disclosure.

9. Which action would help you apply "AI Incident Public Disclosure: When and How to Tell the World" responsibly?

   1. Replace regulatory notification requirements (those are mandatory)
   2. Use the tool to avoid thinking through the tradeoff
   3. Keep going even if the output conflicts with a trusted source
   4. Build the disclosure decision tree before you need it (not in the heat of an incident)

10. Which choice is a bad use of AI for this lesson?

    1. Replace regulatory notification requirements (those are mandatory)
    2. Pre-define the categories of AI incident that warrant disclosure (systematic bias, safety failure, harmful capability, data exposure)
    3. Ask for a plain-language explanation of responsible AI
    4. Compare the answer with a trusted source