The theory behind this is that no ML model is perfect. They will always make some errors. So if these errors they make are included in the training data, then future ML models will learn to repeat the same errors of old models + additional errors.
Over time, ML models will get worse and worse because the quality of the training data will get worse. It’s like a game of Chinese whispers.
The theory behind this is that no ML model is perfect. They will always make some errors. So if these errors they make are included in the training data, then future ML models will learn to repeat the same errors of old models + additional errors.
Over time, ML models will get worse and worse because the quality of the training data will get worse. It’s like a game of Chinese whispers.