Trust Calibration
The process of aligning a user's trust in an AI system with the system's actual capabilities and reliability, avoiding both over-trust and under-trust.
In plain language
Helping users trust AI the right amount; not too much, not too little. Users should know when the AI is likely reliable and when they should double-check its work.
Why this matters
Trust calibration is a governance objective that directly affects AI adoption outcomes. Your organisation needs users to trust AI appropriately. Governance frameworks should support appropriate trust through transparency, clear communication of AI limitations and regular performance reporting.
Relevance
GovernanceEstablishes user trust as a governance outcome, not merely an adoption metric, requiring proactive communication about AI capabilities and limitations to ensure safe and effective deployment.
Related terms
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