Draft:Cognitive Memoisation

Summary

The Cognitive Memoisation (CM) corpus [1] is a publicly available, open-licensed body of work documenting the development of an approach to preserving human reasoning during interaction with large language models (LLMs) and other computational systems. The corpus is authored and curated as a longitudinal record, capturing conceptual foundations and applied observations arising from sustained human–AI engagement.

The central concern of the corpus is the loss of reasoning, context, and intent that typically accompanies iterative problem-solving in complex technical and intellectual domains, particularly when mediated by tools that are stateless, probabilistic, or optimised for short-term interaction. Cognitive Memoisation addresses this problem by emphasising the externalisation of thought into durable artefacts that retain temporal anchoring, provenance, and contextual meaning across time.

Rather than proposing a single formal framework or software system, the corpus adopts a descriptive and practice-oriented stance. It introduces terminology, distinctions, and invariants intended to clarify how reasoning may be captured, revisited, and curated without asserting epistemic authority by default. A recurring theme is the explicit separation between content and epistemic state, allowing ideas to persist without being prematurely classified as correct, complete, or canonical.

The corpus further examines implications of human–AI interaction for knowledge durability, curation, and long-lived technical practice. Particular attention is given to risks associated with fluent but ungrounded machine-generated output, and to the necessity of maintaining human authority over what is retained, promoted, or discarded. These considerations are developed through normative specifications, reflective essays, and case-based analyses drawn from real-world technical contexts.

All materials in the corpus are published using MediaWiki as a durable documentation substrate, providing transparent revision history, stable page identifiers, and long-term reference URLs. The corpus is released under the Apache License 2.0 to permit reuse, citation, and adaptation without restriction.

Conflict of Interest

The author declares a conflict of interest insofar as the corpus documents concepts, terminology, and practices developed through the author’s own professional and intellectual work. The materials are therefore presented as a reference archive rather than as an established consensus or standard, and are intended to be evaluated, extended, or critiqued independently by readers.

References

Category:Artifical Intelligence Category:Large Language Models

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