Complex Information: A Conceptual Extension of Classical Information Models for Human Decision Contexts

Classical information models have proven highly effective for the design and operation of machine-based communication and computation systems. These models intentionally abstract away meaning, interpretation, and human decision-making in order to achieve formal clarity and computability. This document describes a conceptual extension to classical information models, referred to as complex information, which represents information as consisting of two components: a real component, suitable for machine processing, and an imaginary component, representing human context, meaning, and non-computable decision factors. The proposed concept does not replace existing information theory, nor does it define new protocols or standards. Instead, it provides a descriptive framework for reasoning about information systems that interact with human decision processes, trust, and interpretation.