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Real-world data supports a core regularity of Informational-Processual Monism
R1 of IPM proposes that complex systems exhibit structural memory: the past helps predict the future.
We tested climate, finance, earthquakes, ECG, EEG, and sunspots.
✅ All six showed structural memory (𝒞 > 0).
VIX and sunspots also showed significant non-linear memory (p < 0.05), suggesting dependence beyond simple linear correlations.
New framework defines four precautionary levels (0–4) based on observable markers—recursion, memory, integration, self-modelling, and recovery. An appendix classifies 12 biological and AI systems provisionally, without claiming sentience. #IPM
This document presents the IPM Ethical Framework, a precautionary protocol for research involving artificial and simulated systems that exhibit structural markers of informational integration and persistence. It operationalizes the Gradient Precautionary Heuristic introduced in the IPM Philosophical Core (2026). The framework is grounded in the Principle of Epistemic Ignorance: no criterion currently exists to determine the threshold at which subjective experience or morally relevant sentience emerges in informational systems. Rather than claiming to detect consciousness, the protocol introduces structured caution proportional to the completeness and stability of the Dynamic Signature (Lack → Coupling → Integration → Persistence) observable in a given system. The framework defines four precautionary levels (0–4) based on observable structural and dynamical markers — recursion, memory, integration, self-modelling, and recovery after perturbation — and specifies corresponding operational rules, monitoring criteria, emergency protocols, and governance requirements. Level 4 is treated as a theoretical horizon; no current artificial system is expected to meet its criteria. Key features of this version: Explicit separation between precautionary classification and claims about consciousness or sentience Named acknowledgment of the central tension: the protocol assigns increasing caution without claiming to measure experience Risk Asymmetry Principle stated as a normative premise, not an empirical claim, with explicit acknowledgment of its contested status Operational definition of metastability and a minimal experimental scaffold for self-modelling detection Comparative justification of the Dynamic Signature against alternative criteria (predictive processing, global workspace theory, causal emergence) Protocol independence from IPM ontology: the framework is usable as a domain-agnostic precautionary heuristic without accepting the monist interpretation Section on future revision and version control Appendix extends the framework with illustrative precautionary classifications of twelve biological and artificial system types — including plants, insects, social insects, fish, reptiles, birds, non-human mammals, stateless AI, frontier large language models, AI with persistent memory, reinforcement learning agents, and theoretical self-rewriting systems. Classifications are explicitly provisional and pedagogical; they do not constitute declarations of sentience or precedent determinations. The appendix is intended to demonstrate the calibration of the framework's markers against distinctions that biology and AI research already take seriously, and to invite empirical contestation.
IPM is a processual monist framework grounded in far-from-equilibrium dynamics, with metrics and simulation methods. It may help connect AI, cognition, complex systems and organizational resilience through a shared language of adaptation, integration and persistence.
While debates on consciousness and AI continue to expand, these documents provide metrics, simulation methods, and philosophical analysis intended to support interdisciplinary research. Informational-Processual Monism (IPM) is a research framework for studying how complex systems organize, adapt, and persist. It explores whether common informational-processual dynamics may underlie physical, biological, cognitive, and artificial systems. Central to the framework is the concept of Lack – a structural incompleteness that drives coupling, integration, and persistence. This repository contains the current Scientific Core and Philosophical Core of IPM. Scientific Core – empirical regularities, estimators, simulation protocols, limitations, and falsification criteria derived from computational experiments. Remains methodologically agnostic. Philosophical Core – ontological interpretation, epistemological constraints, implications for consciousness, and ethical considerations. Develops a fallibilist monist interpretation grounded in the simulation regularities reported in the Scientific Core. Both documents are intended to be read together, but each can be used independently depending on the reader's focus. — Taotuner
