Black Mirror Theory v0.2: Recursive Reflective State Dynamics — A Conceptual Research Proposal
Year: 2026
Type: article
Abstract: Black Mirror Theory is examined as a candidate mid-level account of recursive reflective-state dynamics, rather than a novel fundamental feedback mechanism. The restricted proposal concerns a representation meaningfully associated with an agent’s earlier cognitive state that re-enters a later, non-identical state and contributes to modifying constraints on subsequent interpretation, reflection, or action. Repeated closure of such state-referenced re-entry may yield history-sensitive reflective trajectories. This paper distinguishes ordinary interpretation from re-entry and genuine recursive closure, treats “pins” as shorthand for heterogeneous constraints rather than a primitive, and recognizes strong overlap with feedback, journaling, external memory, salience, self-modeling, and prior-weighted inference. It presents an explicitly provisional notation, discriminant hypotheses, matched-control study designs, possible falsifiers, and known limitations. No distinctive Black Mirror effect or empirical validation is claimed. The paper is a source-bounded conceptual synthesis prepared for independent literature review and research design appraisal. Status: Unreviewed conceptual research proposal. No independent empirical validation. No executed human-subject study or independent dual-coder reliability result is reported. Author: Warren C. Sholtz. Research & Development Assistant and collaborator: Tina Witowski. Substantial AI assistance: This research program was directed by Warren C. Sholtz and developed with substantial assistance from OpenAI ChatGPT. AI assistance affected drafting and revision, literature discovery and summarization, conceptual formalization, competitor comparisons, proposed research designs, and editorial preparation throughout the manuscript. AI-assisted adversarial checks were internal development aids, not independent peer review or empirical validation. Historical model identifiers and versions have not been independently established for every development session. AI tools are not authors or contributors. Responsibility for the argument, factual accuracy, citations, interpretation, and final editorial decisions rests with the human author.
Author: Sholtz, Warren C.
Language: English
Subfield: Philosophy
Field: Arts and Humanities
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7225664301
FWCI:
Cites:
Cited by:
Related to: