informationnonaugmenting

Informationnonaugmenting is a neologism used in some discussions of information theory and data processing to describe operations that do not increase the information content about a given source. The term highlights the distinction between transformations that preserve or reduce information and those that could reveal new information about the source.

Definition and scope: In a minimal reading, an operation on a random variable X producing Y is information non-augmenting with respect to X if the processing cannot generate information about X beyond what the original data already contained. In practice, deterministic invertible transformations preserve information; non-invertible or noisy transformations reduce information, and are therefore information non-augmenting. The concept is not standard, and different authors may formalize it differently, often drawing on related ideas from the data processing inequality and sufficiency.

Applications and examples: The idea is used in privacy-preserving data releases, where outputs are designed not to reveal more about the underlying data than needed. Adding independent noise or aggregating data typically fulfills the non-augmenting notion. Conversely, incorporating external data that helps infer the original state can be information-augmenting.

Relation to other concepts: The term overlaps with notions of information preservation, sufficiency, and the data processing inequality. It is mainly a descriptive concept rather than a mathematically rigid class in standard texts, and its precise meaning may vary by context.

See also: information theory, data processing inequality, sufficiency, differential privacy.