AI and Foster Care Risk Scoring: Allegheny's Lessons Generalized

End-of-lesson check

10 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-ethics-safety-AI-and-foster-care-risk-scoring-r7a4-adults

1. What is the main idea of "AI and Foster Care Risk Scoring: Allegheny's Lessons Generalized"?

   1. Predictive child-welfare scores embed historical bias; mandate appeal rights and human-final-call before deployment.
   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 and Foster Care Risk Scoring: Allegheny's Lessons Generalized"?

   1. predictive scoring
   2. child welfare
   3. racial bias
   4. appeals

3. Which use of AI fits this topic best?

   1. Distinguish poverty signals from neglect signals
   2. Let the AI decide what matters without your review
   3. Aggregate referral history into a single workload signal
   4. Use the answer before checking whether it fits the situation

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

   1. Aggregate referral history into a single workload signal
   2. Explain the topic in plain language
   3. Organize a draft for human review
   4. Distinguish poverty signals from neglect signals

5. What should a careful learner remember about "Make every score appealable in writing"?

   1. Use AI to draft or organize ideas about child welfare, 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 child welfare 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 child welfare.

9. Which action would help you apply "AI and Foster Care Risk Scoring: Allegheny's Lessons Generalized" responsibly?

   1. Correct for over-reporting of Black and Indigenous families
   2. Use the tool to avoid thinking through the tradeoff
   3. Keep going even if the output conflicts with a trusted source
   4. Help screeners triage incoming hotline calls

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

    1. Correct for over-reporting of Black and Indigenous families
    2. Aggregate referral history into a single workload signal
    3. Ask for a plain-language explanation of predictive scoring
    4. Compare the answer with a trusted source