What is exposure bias in recommendation systems?

Exposure bias occurs when only previously shown items are used as training data.

In recommendation systems, users can only interact with items they are exposed to. This creates a biased dataset where missing interactions do not mean dislike. Models trained on this data learn biased patterns. Counterfactual learning and inverse propensity scoring are commonly used to correct exposure bias.