The Illusion of Accuracy

The Danger of Automation Bias

 Somewhere between adolescence and adulthood, we learned that “because I said so” was not a real answer.

We questioned it. We pushed back. We wanted to understand why.

That instinct was not a rebellion. It was learning. It was the beginning of judgment.

Yet today, in many organizations, that same question has quietly disappeared.

“The system says so." “The model recommends it." “The data is clear.”

The conversation ends.

Accuracy Isn’t the Same as Judgment. A system can be statistically right and still lead organizations in the wrong direction.

A Forbes article by Bryce Hoffman explains why.

In this week’s study, we dive into the dangers of automation bias.  In a recent Forbes article, Bryce Hoffman, who writes on leadership, strategy, and decision-making, revisited a concept that quietly shapes more decisions than most leaders realize: automation bias.

Automation bias is not about people being careless or unskilled. It is about how the brain works.

Once we begin to trust an automated system, we naturally defer to it even when contradictory information is visible. Even when something feels off. Research across aviation, medicine, finance, and business shows that people will follow incorrect automated recommendations more than half the time once trust is established.

This happens because the brain is efficient. When a system appears reliable, questioning it starts to feel unnecessary. Over time, it becomes unnatural.

The danger is not speed. The danger is quiet erosion.

As Hoffman notes, the consequences of automation bias have been severe in real-world settings, from airline disasters to major financial losses. As organizations delegate more planning and decision support to AI, this risk increases, not because leaders stop caring, but because systems stop asking humans to think.

This is where the difference shows up in practice.

Not by rejecting automation, but by slowing decisions when judgment matters most, creating space for explanation, reflection, and human ownership. This is the discipline at the heart of Cross-Intelligence Leadership.

Because accuracy alone does not guarantee wisdom. And efficiency does not replace responsibility.

Reflective question: Which decisions in your organization no longer require anyone to explain why they make sense?

Source: Forbes — Automation Bias: What It Is And How To Overcome ItBy Bryce HoffmanForbes https://www.forbes.com/sites/brycehoffman/2024/03/10/automation-bias-what-it-is-and-how-to-overcome-it/

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