aif-grounded

To get 100% confident answers without hallucinations, you need an evidence-based reasoning process that enforces explicit uncertainty. This approach only provides a final response when confidence is fully backed by available evidence.

Evidence-based reasoning is a mechanism that prevents fabricated answers by explicitly signaling uncertainty. It evaluates available evidence and only outputs a final answer when confidence reaches 100/100.

To prevent AI from guessing, enforce a rule that outputs a concise what's-missing checklist when confidence is below 100. This checklist explains what information is required to reach full confidence.

Yes, grounded reasoning is designed for high-stakes safety applications. It prevents uncertain answers by enforcing evidence-based reasoning and explicitly requesting missing information when confidence is not 100%.

When confidence is not 100, the grounded reasoning mechanism outputs a short what's-missing checklist. This checklist details exactly what evidence is required to reach 100% confidence and provide a final answer.

A limitation of enforcing 100% confidence is that the AI will withhold final answers if evidence is incomplete. Instead of guessing, it outputs a checklist of missing information, which may halt progress until data is provided.