Evaluator Context · AI Trust Assessment
AI TRUST — Trust / Risk / Confidence
The AI Trust Engine consumes the feature/context package and produces the demonstrator’s core analytical outputs: risk probability, trust score, risk category and confidence. This is the part of the portal that most directly responds to the EOI’s insistence on AI-powered trust scoring.
AI TRUST — Trust / Risk / Confidence
Expanded evaluator context
Professional interpretation
Purpose in the demonstrator
This stage makes the AI visible. It shows that the TRUST demonstrator is not a rules-only portal. It performs a governed model-based assessment and exposes both the assessment result and the model boundary.
Operational meaning
Risk probabilityModel-estimated likelihood representation used internally for assessment.
Trust scoreHuman-readable scoring representation that helps evaluators compare scenarios.
ConfidenceIndicates evidence completeness and coverage, especially important in weak-metadata scenarios.
Inputs and outputs
| Element | Meaning in this demonstrator |
|---|---|
| Feature/context package | Evidence produced upstream and consumed by the AI model. |
| Trust score | Readable summary of assessed trustworthiness in the demonstrator. |
| Risk category | LOW, MEDIUM, HIGH or CRITICAL classification derived from modeled assessment. |
| Confidence | Evidence sufficiency indicator supporting transparent interpretation. |
Evaluator questions this page answers
- Where is the AI in the demonstrator?
- What are the AI outputs, and how should they be interpreted?
- Why can two scenarios have similar trust but different confidence?
- How is the AI separated from payment authorization?
How this stage fits in the end-to-end chain
1. FEATURESEvidence package enters the model.
2. AI TRUSTTrust, risk and confidence are computed.
3. EXPLAINAssessment is translated into reason codes and narrative clarity.
4. POLICYGoverned recommendation is produced separately from the AI itself.
Governance and interpretation notes
This page is an evaluator-facing contextual explanation of the demonstrator stage. It explains the business role, the technical contribution, the governance boundary and the expected interpretation of the displayed output. It is designed to make the demonstration credible, understandable and professionally reviewable without exposing raw internal JSON on-screen.
Trust / Risk / Confidence View
This evaluator-facing view separates trust, risk and confidence so that the three concepts remain visually distinct.
Trust is shown as a score, risk as a category/probability interpretation, and confidence as evidence sufficiency.