Indeed. And the obvious reason is that when you simulate the "self-assessment" using a Gaussian noise around the "actual intelligence", and clamp it to [0, 100] so that it doesn't go "out of bound" (eg "negative intelligence" is not allowed), you will necessarily skew the low scores upward and the high scores downwards.

But it's not because "some statistical model exhibit a bias that's similar to the result" that this implies "therefore the result is a statistical error"... that's a backward reasonning