THE SHORT ANSWER
AI can help brainstorm alternatives, expose assumptions, structure evidence, generate counterarguments and compare scenarios. Treat those outputs as material to inspect—not as proof, final authority or a substitute for domain expertise and accountable human decisions.
Give AI a thinking role, not automatic authority
| AI can help | Human responsibility |
|---|---|
| Generate alternative explanations | Judge plausibility and seek evidence |
| Challenge stated assumptions | Notice omitted context and choose what matters |
| Summarize supplied evidence | Check the source and whether the summary is faithful |
| Create counterarguments | Distinguish a possible objection from a supported one |
| Compare scenarios | Set objectives, constraints and acceptable risks |
| Structure a decision note | Own the decision and review it |
Think first, use AI, then reconstruct the judgment
- Write your initial claim, assumptions and uncertainty.
- Ask for alternatives, missing questions and counterarguments.
- Extract consequential claims from the response.
- Verify them with independent evidence.
- Revise your view and explain each material change.
- Make and review the decision without citing fluency as evidence.
Appropriate reliance depends on role and consequence
NIST distinguishes systems that decide, defer to experts or provide an additional opinion. Calling every interaction ‘human in the loop’ does not show that the person has enough information, time, authority or expertise to provide meaningful oversight.
For uncertain factual output, use the existing guide to verify AI-generated information. For mechanism-level risk, read why AI hallucinates.
When capability, cost and consequence vary by task, choose an AI model through representative evaluation rather than treating model size or confident style as a proxy for decision quality.
Evidence & context: NIST AI Resource Center · NIST
Do not use assistance to hide responsibility
AI should not automatically become the source of truth, the final decision-maker or a substitute for qualified expertise. Protect sensitive information, respect applicable rules and add stronger review when errors affect rights, safety, money or access.
Sources & further reading
- AI Risk Management and Human-AI Interaction
NIST AI Resource Center. Official guidance on different human and AI decision roles and oversight. Appropriate reliance depends on context, consequence and system evidence.
- Generative Artificial Intelligence Profile (NIST AI 600-1)
NIST. Risk-management guidance, including confabulation. It does not establish a universal error rate.
- Guidance for generative AI in education and research
UNESCO. Guidance centring human agency and educational purpose. OpenSkool's proposed exercises are editorial suggestions, not validated interventions.
Examples and exercises are illustrative unless attributed to a source. No independent expert review is claimed.
A correction, a counterexample or an experience worth sharing?
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