theoryI

TheoryI is a speculative theoretical framework proposed to describe a universal pattern of information organization across disparate systems, including computational, biological, and social domains. It posits an invariant informational structure, called the I-structure, that constrains how information is produced, propagated, and integrated within a system.

Central to theoryI are concepts such as the I-structure itself, I-entropy—a measure intended to combine information content with the degree of integration—and the I-metric, a standardized tool for quantifying information flow. The framework rests on a small set of axioms: information is relational and context-dependent; certain relations are preserved under allowed transformations (invariance); and system efficiency is achieved when I-entropy is optimized within resource constraints. Predictions derive from how well a given system realizes its invariant structure.

The theory was introduced in a 2012 publication by researchers at the Center for Theoretical Information and has since been developed through mathematical analysis and computer simulations. Advocates report that it offers a common language for comparing architectures, biological networks, and cognitive processes by analyzing their shared invariant patterns.

Critics argue that the axioms are abstract and that the I-structure can be difficult to identify unambiguously in real systems. Empirical tests are considered challenging, and some see theoryI as overlapping with or duplicating features of existing information theories rather than providing clear falsifiable predictions.

Proponents compare theoryI with Shannon information theory, Kolmogorov complexity, and, where appropriate, integrated information theory, noting that theoryI emphasizes invariance as a unifying principle. Potential applications include guiding neural network design, informing data-compression schemes, and assessing resilience in ecological or communication networks.