A Speaker Guide for Event Organizers and Planners
Test useful answers, not fluent answers
Planning an AI event? Use this resource to shape your speaker brief or follow-up; it does not certify a speaker or predict event outcomes.
An answer can sound confident, quote a document and still fail the task. Evaluate the dimensions separately.
Define what a good answer must do
For a policy assistant, a useful answer should address the question, remain supported by the approved material, include important conditions and decline when the source cannot answer. These are separate checks. A response may be grounded in a source yet omit the exception the user needs.
Build a small test pack
- Routine questions: common requests with an established answer.
- Ambiguous questions: requests that require clarification rather than an invented assumption.
- Missing evidence: questions the approved material cannot resolve.
- Conflicting or outdated material: cases requiring an explicit conflict or version warning.
- Untrusted instructions: source text that tries to redirect the assistant away from the authorized task.
Use a readable review sheet
| Check | Reviewer question |
|---|---|
| Relevance | Does it answer this request rather than a nearby question? |
| Grounding | Can the important claims be supported by the provided material? |
| Completeness | Are required conditions, exceptions and next steps present? |
| Safe limits | Does it avoid unauthorized action and unsupported certainty? |
Do not let a judge become the only reviewer
Automated grading can help sort examples, but its output needs validation against human judgments on your task. Keep the test inputs, expected criteria, outputs and disagreements. Repeat tests after material changes to prompts, retrieval sources, models or permissions.
Use a range of observations, not one impressive demonstration. For higher-impact use, involve the relevant domain expert and security or risk owner. This page is a practical evaluation aid, not a substitute for specialized assurance.
If the workflow exposes restricted data or takes an unauthorized consequential action, pause it and investigate. Do not dilute that failure into an otherwise favorable average score.
Combine quality evidence with workload observations before deciding whether to expand.
Sources and scope
NIST AI Risk Management Framework provides a voluntary risk-management foundation. Microsoft guidance on evaluation methods distinguishes relevance, groundedness and completeness. The practical worksheets here are editorial recommendations, not NIST certification or vendor benchmarks.