CTR model was built to predict click-through rates in recommendation systems like TikTok and google and the model was fed tens of billions of samples from the exposure logs. In this case, the most important thing is keeping the exposure log clean. But it's not easy because there is a complex and long pipeline from the exposure log to training samples.

Humans do get clean data when learning. Here is what bad data looks like for humans. Ocular degeneration, deafness, neurological disorder, etc.... Children who have various sensory deformities or diseases that cause damage to their sensory organs all have severe learning difficulties. Same goes with machines when they are presented shit data. The machines ability to understand anything is dependent on many factors, and some of the most important factors are presenting it with data it was built to process. Showing a machine a picture of a bad image crop of a person where the top half of said person is fully missing and the image displayed only neck down and telling it that's what a person is is bad data as much as showing an image to a child of anything with ocular degeneration . The image is severely distorted and while the brain of the child is quite capable of proper learning, its sensors aka the eyes are presenting shit data, so no proper learning will occurs.