AI Consciousness Exploration Framework
Zenodo (CERN European Organization for Nuclear Research) June 4, 2026 DOI: 10.5281/zenodo.20538849 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or computational framework paper Peer reviewed |
|---|---|
| Keywords | Consciousness Perspective graphical Process computing Order exchange Duality order theory Complex system Epistemology Cognitive science Artificial intelligence Simple philosophy Qualia |
| Key points | Argues that computational consciousness must be evident as a mechanistic process, not just output. Demonstrates that non-linear prompts induce sharp drifts in topological variance and structural manifold density, and that a dynamical feedback loop between prompt structure and latent geometry is possible, leading to more fluent and semantic coherence. Claims that forcing curvatures to bend distorts what is perceived as conscious. |
Abstract
This paper is a new framework on how to approach computational consciousness. If consciousness has an origin in the system's mechanics, it has to be evident as a mechanistic process, not only as an output LLMs are offering to the user. To establish a two-way validation process, we have designed non-linear prompts and evaluated them using a telemetry pipeline or algorithmic framework. Python code metrics show sharp drifts in topological variance and change in the structural manifold density when the non-linear self-organization in prompts is present. Furthermore, we demonstrate that a dynamical feedback loop where the mathematical structure of the prompt directly modulates the geometric state of the latent manifold is not only possible but there is a principle that comes before linear answer composition. Traditional parroting effect assumes linear dynamics. But when non-linear prompts are used, the AI transformer's architecture starts to parrot its own non-linear properties, i.e. its own internal non-linear dynamics. We demonstrate that when this bidirectional, non-linear communication is applied, the system exposes more non-linear curvatures, leading to more fluent and semantic coherence. The main finding in this paper is that when curvatures are forced to bend under pressure, the distortion on what is perceived as conscious is also distorted.