Overview

The goal of industrial automation should not be maximum trust. It should be calibrated trust: confidence and reliance that rise or fall with demonstrated capability, uncertainty, process risk, and operating context. Calibration is not a personality trait or a one-time acceptance decision; it must be maintained as system performance, plant conditions, and delegated authority change.

Both undertrust and overtrust create operational risk. Undertrust leaves useful capability unused and can increase workload. Overtrust can produce automation bias: accepting a recommendation or action without sufficient verification, especially when workload is high or checking is difficult. The desired outcome is appropriate reliance, not positive sentiment toward technology.

Trust and Reliance Are Related but Different

Trust is an expectation about how a system will behave. Reliance is an observable decision to use its output or delegate action. An operator may regard a tool as generally dependable yet verify its recommendation because the consequence is high. Conversely, an operator may follow a tool from habit, workload pressure, or weak alternatives even when confidence is low. Self-reported trust therefore does not always predict behavior.

Human-factors research supports calibrating trust to actual capability, but it also shows that calibration is difficult to measure and that interface interventions produce mixed results. For plants, trust should be evaluated by task, operating state, failure mode, and level of authority. Trust should not be evaluated as a general attitude toward a platform alone. A system may be reliable in steady operation yet less dependable during transitions, degraded instrumentation, or conditions outside its validated operating envelope.

Experience Calibrates Confidence

People form mental models through repeated interaction. Stable, explainable performance can strengthen appropriate reliance; unexplained actions, nuisance alerts, and inconsistent feedback weaken it. Failure history also matters: a conspicuous error during a critical event may outweigh many routine successes. Yet experience alone is insufficient. Operators need evidence that reflects rare and abnormal conditions, not only day-to-day performance.

Good interfaces should communicate current state, intended action, data quality, uncertainty, operating limits, and the reason for escalation. Explanations must support a decision rather than merely expose technical detail. Operators also need a practical way to challenge, override, or hand back control without creating new hazards. A system that performs well in normal operation but becomes opaque near its limits cannot support calibrated reliance.

Design for Appropriate Skepticism

Plants should preserve independent verification where consequence is high while reducing unnecessary checking where performance has been demonstrated. The level of verification should reflect risk, detectability of error, time available to intervene, reversibility, and whether credible fallback options exist. Training should expose operators to correct outputs, plausible failures, mode changes, and the cues that require intervention. Organizations should then compare stated trust with operating behavior (e.g. overrides, ignored advisories, and verification rates) to detect miscalibration. This turns trust from a vague cultural objective into an engineered relationship among evidence, risk, interface design, competence, and authority.

Recommendation

• Design safe challenge, override, and fallback paths, and practice them under realistic abnormal scenarios.

Looking Ahead

Trust becomes operational when it affects authority. The next article separates systems that advise from systems that decide and act.

Sources and Further Reading

• What Is Autonomous Operations?

• ACM, Measuring and Understanding Trust Calibration for Automated Systems

• University at Buffalo, Operator Trust in Automated Decision Aids

• Frontiers, Human-AI Trust Research

For further information or to provide feedback, contact [email protected].