



Network Working Group                                      F. Mittermair
Internet-Draft                                               Independent
Intended status: Informational                           18 January 2026
Expires: 22 July 2026


  Complex Information: A Conceptual Extension of Classical Information
                   Models for Human Decision Contexts
                draft-mittermair-complex-information-00

Abstract

   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.

Status of This Memo

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   This Internet-Draft will expire on 22 July 2026.





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Copyright Notice

   Copyright (c) 2026 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents (https://trustee.ietf.org/
   license-info) in effect on the date of publication of this document.
   Please review these documents carefully, as they describe your rights
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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   2
     2.1.  Classical Information . . . . . . . . . . . . . . . . . .   2
     2.2.  Physical Information  . . . . . . . . . . . . . . . . . .   3
     2.3.  Complex Information . . . . . . . . . . . . . . . . . . .   3
     2.4.  Decision Space  . . . . . . . . . . . . . . . . . . . . .   3
   3.  Problem Statement . . . . . . . . . . . . . . . . . . . . . .   3
   4.  Proposed Concept: Complex Information . . . . . . . . . . . .   3
   5.  Implications  . . . . . . . . . . . . . . . . . . . . . . . .   3
   6.  Security Considerations . . . . . . . . . . . . . . . . . . .   3
   7.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .   4
   8.  Informative References  . . . . . . . . . . . . . . . . . . .   4
   Author's Address  . . . . . . . . . . . . . . . . . . . . . . . .   4

1.  Introduction

   Modern information systems increasingly participate in contexts that
   extend beyond pure data transmission and computation.  These systems
   influence decision-making processes affecting individuals,
   organizations, and societies.

   Classical information theory intentionally excludes semantic meaning
   and interpretation.  While this abstraction enables reliable and
   scalable systems, it provides no formal representation for human
   decision context.

2.  Terminology

2.1.  Classical Information

   Classical information refers to information as defined in
   mathematical information theory, where information is represented as
   a function of symbol probabilities and is independent of semantic
   meaning or interpretation.




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   Classical information theory is commonly associated with the work of
   [Shannon1948].

2.2.  Physical Information

   Physical information refers to the treatment of information as a
   physical quantity bound to thermodynamic processes, including energy
   dissipation and irreversibility.

   Physical interpretations of information are commonly linked to
   [Landauer1961].

2.3.  Complex Information

   Complex information is a conceptual model in which information is
   described as having two components: a real component and an imaginary
   component.

2.4.  Decision Space

   Decision space refers to choices or judgments that cannot be fully
   derived from computable information alone and therefore require human
   interpretation or responsibility.

3.  Problem Statement

   When classical information models are applied directly to human-
   facing decision contexts, structural issues arise due to the absence
   of formal representation for non-computable decision factors.

4.  Proposed Concept: Complex Information

   The complex information model preserves existing computational models
   while explicitly acknowledging non-computable components relevant to
   human decision-making.

5.  Implications

   The model supports clearer analytical separation between computation
   and interpretation, without introducing new protocols or
   requirements.

6.  Security Considerations

   Failure to distinguish computable and interpretive components may
   lead to misattributed authority, misleading representations, or
   algorithmic overreach.  This document defines no security mechanisms.




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7.  IANA Considerations

   This document has no IANA considerations.

8.  Informative References

   [Shannon1948]
              Shannon, C. E., "A Mathematical Theory of Communication",
              1948.

   [Landauer1961]
              Landauer, R., "Irreversibility and Heat Generation in the
              Computing Process", 1961.

Author's Address

   Franz Mittermair
   Independent
   Email: fx@stwst.at
































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