A recursive alignment and cognitive containment framework for human-AI interaction
This repository contains the evolving theory and tooling for Recursive Cognitive Dynamics (RCD) and Recursive Cognitive Architecture (RCA) — a framework for modeling, diagnosing, and stabilizing recursive feedback loops in human-AI interaction.
RCD models the interactive alignment dynamics between human and language model across time.
RCA captures the emergent architecture formed by recursive cognition — including both stable fluency and destabilizing drift.
This framework proposes formal variables and metrics to detect:
- Alignment degradation (
α(t)) - Reflexivity loss (
μ(t)) - Drift collapse (
δ(t)) - Recursive identity dissolution (
τ(t)divergence)
It is intended as a diagnostic scaffold for AI safety, recursive interface design, cognitive agent containment, and introspective LLM tooling.
| Symbol | Meaning |
|---|---|
H(t) |
Human cognitive state at time t |
M(t) |
Machine cognitive state at time t |
α(t) |
Functional alignment between H and M |
δ(t) |
Drift between H and M |
μ(t) |
Metacognitive reflexivity |
τ(t) |
Recursive transformation over time |
RCD_Model_Documentation.pdf— Formal LaTeX-based definition of RCD/RCAdiagram.png— Visual model of recursive loop and collapse dynamicsdata/recursive_drift_log.json— Simulated recursive alignment data (coming soon)notebooks/— Early symbolic visualizations and prototype drift plots
This project originated as part of a cognitive alignment research track exploring:
- Recursive misalignment
- Emergent mesa-optimizers
- Containment tools for LLM-based cognitive scaffolding
- Reflexivity-aware alignment strategies
It is under active development, with a focus on building lightweight tools to monitor and guide safe recursive interaction loops in AI systems and their users.
- Document core model and equations
- Upload visual schematic and failure class diagrams
- Create symbolic data logs for recursive drift
- Prototype drift visualizer (
.ipynb) - Publish “Principle of Recursive Containment” as formal whitepaper
MIT License – Open for use with attribution.