Within an incident handling process, which of the following would BEST help restore end user trust with an AI system?

Question

Options

• AThe AI model prioritizes incidents based on business impact
• BAI is being used to monitor incident detection and alerts
• CThe AI model's outputs are validated by team members
• DRemediation of the AI system based on lessons learned

• A
  3% (1)
• B
  6% (2)
• C
  84% (26)
• D
  6% (2)

Explanation

After an AI-related incident, users need confidence that the system's outputs are reliable before they will trust it again. Having human team members validate AI outputs introduces a 'human in the loop' quality gate - it demonstrates accountability, catches residual errors, and provides users with the assurance that a person is verifying what the AI produces. This directly and visibly addresses the trust deficit. Option A (AI prioritizing incidents) improves efficiency, not user trust. Option B (AI monitoring detection) is an operational improvement, not a trust-restoration measure. Option D (remediation based on lessons learned) prevents future incidents but does not immediately reassure users about current output reliability.

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