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Generative AI Leader Practice Question: A legal firm wants to use a generative AI model…
A legal firm wants to use a generative AI model to draft contract clauses. They need to ensure the model's outputs cite specific legal precedents and statutes, and that the reasoning behind each clause is transparent. Which combination of explainability techniques should they prioritize?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Grounding and chain-of-thought reasoning
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Confidence indicators and model cards
Why it's wrong here
Confidence indicators show certainty but don't provide source citations; model cards are high-level documentation, not per-output explanations.
- ✗
Content safety filters and human oversight
Why it's wrong here
Safety filters block harmful content but don't provide source citations or reasoning transparency.
- ✓
Grounding and chain-of-thought reasoning
Why this is correct
Grounding ensures outputs cite sources (legal precedents/statutes); chain-of-thought shows reasoning steps, providing transparency.
- ✗
Datasheets for Datasets and PAIR Explorables
Why it's wrong here
These are for dataset documentation and interactive exploration, not for per-output explainability.
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