Evaluation & Human Judgement
Handling uncertainty and high-stakes AI
Ask for stronger review when AI affects customers, employees, money, compliance, or reputation.
5 min readEvaluation
Workplace example
Employee-affecting recommendation
If AI gives a low-confidence recommendation in an employee case, ask for proper human review. Do not treat the model as final authority.
What this means
- •High-stakes AI use affects meaningful outcomes for people or the organisation.
- •Low-confidence or uncertain output in a high-stakes context should not be treated as final authority.
- •Escalation is a sign of good judgement, not failure.
Why it matters
- •The same error has different consequences in different contexts.
- •AI uncertainty can be hidden by confident wording or ignored under time pressure.
- •Appropriate human review protects fairness, quality, and trust.
Common mistakes
- •Re-prompting until the answer sounds more certain.
- •Hiding uncertainty from the decision record.
- •Proceeding because the recommendation supports a preferred outcome.
What good judgement looks like
- •Identify whether the decision affects people, money, compliance, or reputation.
- •Keep uncertainty visible.
- •Ask a manager, expert, or policy owner for review when required.
Try this at work
- •Take one AI use case and rate its impact if wrong.
- •Write what review would be required before use.
- •Define who should approve or challenge the output.
How this helps your reassessment
- •You know when expert review is needed.
- •You do not use AI as final authority in high-risk situations.
- •You can keep uncertainty visible in decision-making.