CONCEPT
Redundancy and Information
Moles's information-theoretic axis: redundancy is the predictable portion of a message, information is the surprising portion, and the two exist in necessary tension — too much of either destroys the message's communicative value.
Redundancy, in information theory, is the proportion of a message predictable from its context. Its complement is information content — the surprising portion that carries meaning because it could have been otherwise. Moles elevated this engineering distinction into a general aesthetics: every message sits on an axis between total predictability (pure redundancy, zero information, banality) and total unpredictability (pure noise, zero intelligibility). Genuine aesthetic experience requires a calibrated ratio — enough redundancy to be parseable, enough surprise to carry meaning. The AI-mediated cultural environment threatens this calibration by making redundant output nearly costless to produce, flooding the channel with messages that confirm what receivers already know.
In The You On AI Field Guide
The framework begins with Shannon but Moles extends it into territory Shannon explicitly refused to enter. Shannon's 1948 theory treated information as a purely quantitative measure of uncertainty reduction, without reference to whether the message meant anything worth knowing. Moles argued that this limitation, while