Noise as information and information as noise – Unsung
The article explores the blurred boundary between noise and information, arguing that noise can carry meaningful information depending on context and perspective, while what is considered useful information can become noise when misinterpreted or irrelevant. It examines how signal, noise, and interpretation interact in communication and perception systems.
Background
- The piece explores the counterintuitive idea that "noise" (random, meaningless signals) can sometimes carry valuable information, while "information" (structured, meaningful data) can function as noise — depending on context and perspective.
- It draws on concepts from information theory (Claude Shannon), cybernetics, and systems thinking, where noise is defined as any unwanted or unpredictable variation in a signal.
- The article argues that dismissing noise as useless can be a mistake: in biological systems, financial markets, or creative processes, apparently random variation can enable adaptation, innovation, and resilience.
- Conversely, too much structured information can overwhelm cognitive capacity, producing the same effects as noise — confusion, distraction, and loss of signal fidelity.
- This is relevant to contemporary debates about data overload, algorithmic feed saturation, and the difficulty of distinguishing signal from noise in digital culture.