RESEARCH · AI TRUST
In a few words
Trust should not depend on whether a model sounds confident. For consequential action, something more concrete matters: what evidence exists, what authority was delegated, which limits still apply and when a person must be able to change the outcome.
UNDERSTAND MORE
EXAMPLE
Think of an employee badge. Identity and access can be valid without giving permission to approve any payment. AI is similar: authentication and technical capability are different from authority to execute one exact action.
A system may be appropriate for summarizing a document and still not be authorized to move money, change an account or make a high-impact decision. The useful question is not “do we trust this AI?” but “what may it do, under what evidence and mandate, now?”
A person “in the loop” adds little control if they arrive too late, lack enough context or do not have authority to stop, redirect or approve the action.
HHT evaluates the action before effect and separates evidence, authority and decision. Its public Trust Gate lets people explore ALLOW, ESCALATE and STOP without customer data or real-world consequences.
FROM INSIGHT TO ACTION
When an action matters, we should be able to answer why it was allowed, what evidence existed and who remained accountable.