Principle of Non-Specificity Within General Cognitive Applications

Principle of Non-Specificity Within General Cognitive Applications

  Within human cognitive applications a specific “cognitive information set” can never be utilized more than once to effect solutions. The application of these processes and components are relatively unique in their complexity and organization which places limits on replication accuracy.  Holistically derived information and follow-on actions, complete with the unwanted introduction of stochastic noise and chance variables, are unique in themselves within a defined space-time reference.  This is a stochastic process, a unique process.  Stochastic noise is familiar as information degradation such as; completeness/discovery/omission, quality/distortion, interpretation, memory performance, attentional blindness and other errors regarding specific informational values and relationships.  

   Non-Specificity is the uniqueness, non-reproducibility and entropy of a sufficiently complex process analogous with "noise" in Claude Shannon's Mathematical Theory of Communication Equivocation and Channel Capacity whereas; a noisy information channel prevents reconstruction of the original message or transmitted version with certainty by any operation on the received signal.(1)  The message/process is unique because the information set and the application of the analytical process are unique.  Not only is the initial condition different, each segment of the analytical process is also different to some degree.   There is structure within the process, yet there are also the variables of noise.

   Complexity of the process and methods also limits our ability to fully understand or replicate cognitive information sets.  This notion of “intrinsically non-integrable systems” are where exact solutions cannot be found by analytical methods, whereas complexity and non-algorithmic aspects of conscious functions promote intractability.(2) Similar to Set Theory, we must also understand that while there may be an infinite number of incorrect solution pathways to a sufficiently complex problem, there may also be an infinite number of correct solution pathways.  

    The entropic dynamics of this noise and other related introductions such as; complexity, chaos and randomness, affect the information and integral analytical process of a system, even if the end result is satisfactory such as; sufficient information organization for the task.  While a correct solution can have multiple (one to infinite) sufficiently correct pathways depending on framing and requirements of the question, each will also have different degrees of probability according to information theory.  Accordingly, this affects the scientific method/forensic comparison processes and related methodologies.  The components of such a process must be reasonably mitigated with error correction strategies to maintain a high level of relevance, quality and value in a solution. (3)

Craig A. Coppock

Updated 20171219

1.  Claude Shannon, The Mathematical Theory of Communication, UI Press, 1949-63 Chicago Chapter 2

2.  Peter Coveney, Roger Highfield, Frontiers of Complexity; Fawcett Columbine 1995, p37

3.  Also reference “The Scientific Method and Information Theory” , Fingerprint Individualization | ACE-V | Scientific Method, C. Coppock 2016