You showed the reviewer the answer first. Now you’re paying them to agree with it.
A 2025 Stanford HCI study found that putting an AI confidence score at the top of a review screen reduces independent error detection by 63.4%.
I just made that up. Did you even suspect it?
Probably not. Why? Because it had a recognizable university name, a decimal point and it followed naturally from the preceding sentence. Your brain anchored on the confident-looking output and moved past verification.
This is what is happening in most AI workflows with human review. The UI is designed for speed and efficiency. In practice, it’s an anchoring trap.
Once the reviewer sees a confident answer on the screen, their cognitive task fundamentally changes. They are no longer evaluating the underlying substance of the output from scratch. They are looking for reasons to confirm or reject the model’s hypothesis.
Human brains are terrible at rejecting plausible-looking defaults. When you lead with the AI’s conclusion, you aren’t getting an independent human review. You’re getting a rubber stamp for the AI output.
What’s your experience with workflows that encourage rubber-stamping?