noise

Broadly speaking, anything that obscures the signal in a dataset. Noise can be introduced into data in a variety of ways. For example: - Human raters make mistakes in labeling. - Humans and instruments mis-record or omit feature values.

Practitioners refer to noise when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.