LifeOS: A Constitutional Cognitive Operating System for Human–AI Co-Agency
Related: Open Trust Infrastructure (DOI: 10.5281/zenodo.17940484)
Current AI systems conflate language generation, cognitive processing, and world-affecting action into undifferentiated pipelines. This architectural confusion creates fundamental safety, controllability, and trust issues that cannot be resolved through post-hoc alignment techniques.
This thesis proposes LifeOS, a constitutional cognitive operating system that enforces structural separation between linguistic generation, semantic interpretation, and execution. Drawing on Montesquieu's separation of powers, Peircean semiotics, and speech act theory, we demonstrate that reliable human–AI co-agency requires constitutional guarantees rather than behavioral fine-tuning.
Scope clarification: This thesis does not propose a general theory of intelligence, but a design framework for human–AI cognitive systems with explicit constitutional guarantees.
The central invariant is simple: meaning is not causation — no symbol can directly affect the world. This principle, implemented as an architectural constraint, ensures that the system remains trustworthy regardless of the correctness of any individual component.
Modern AI systems, particularly those built on Large Language Models, suffer from a fundamental architectural confusion:
| What is conflated | Why it matters |
|---|---|
| Language generation ↔ Understanding | Models produce text without semantic grounding |
| Prediction ↔ Reasoning | Token prediction is mistaken for logical inference |
| Response ↔ Action | Outputs can trigger world-affecting consequences |
This conflation leads to:
Current "AI safety" approaches attempt to solve these problems through fine-tuning on human preferences (RLHF), Constitutional AI prompting, and output filtering. These approaches share a fatal flaw: they depend on the system being correct.
A system that requires correctness to be safe will eventually fail. The question is not if but when.
How can we design cognitive AI systems that remain structurally trustworthy regardless of the correctness of their linguistic outputs?
"Pour qu'on ne puisse abuser du pouvoir, il faut que, par la disposition des choses, le pouvoir arrête le pouvoir."
— Montesquieu, L'Esprit des lois (1748)
We transpose this principle to cognitive architecture:
| Political | Cognitive (LifeOS) |
|---|---|
| Legislative | Language generation (LLM) |
| Executive | ExecutorOS (action) |
| Judicial | Validation, constraints, traceability |
| Law | Invariant |
| Constitution | Architecture |
Key insight: The power to say is never the power to do.
The semiotic triangle provides the theoretical foundation:
Central principle: The relationship between signifiant and référent is arbitrary and mediated. A symbol cannot directly cause world-state changes.
Following Austin and Searle, we distinguish:
LifeOS architecturally separates these layers, ensuring that locutionary production (LLM output) never directly produces perlocutionary effects (world changes).
LifeOS is a constitutional cognitive operating system comprising modular, separable components:
| Module | Function | Key Property |
|---|---|---|
| CognitionOS | Pattern recognition, language generation | No world access |
| MemoryOS | Episodic, semantic, procedural memory | Persistent identity |
| LearningOS | Skill acquisition, adaptation | Supervised updates |
| BehaviorOS | Action planning and sequencing | Intent validation |
| EmotionOS | Salience, orientation, attention | Non-decisive signals |
| Harmonia | Constitutional layer, semiotic firewall | Invariant enforcement |
| ExecutorOS | World-affecting action execution | Sole action point |
Harmonia implements the core invariant through a layered processing pipeline:
Critical constraint: No layer can bypass another. The LLM (layer 1) can never directly invoke ExecutorOS (layer 5).
Meaning is not causation.
No symbol acts directly on the world.
The power to say is never the power to do.
This invariant is:
Redefining AI systems as cognitive operating systems rather than applications or agents:
Applying political philosophy to AI architecture:
A complete, executable architecture:
The "alter ego" paradigm:
The term "alter ego" is used strictly as a Human–Computer Interaction metaphor, not as a psychological or cognitive duplication model.
Demonstrating the path from principle to implementation:
Following Hevner et al. (2004), this thesis employs design science methodology:
Key properties will be verified using:
| Component | Status |
|---|---|
| Theoretical framework | Complete |
| Core architecture design | Complete |
| Harmonia implementation | Production |
| ExecutorOS | Production |
| MemoryOS | Production |
| EduOS (educational suite) | Production |
| Documentation (Constitution, Invariant) | Complete |
| Task | Estimated Duration |
|---|---|
| Scoped formal verification | 6 months |
| Comparative evaluation | 4 months |
| User studies | 4 months |
| Thesis writing | 6 months |
"Words can contradict each other. The world cannot."
"I build systems that protect humans from their own ideas."
"Trust does not rest on intentions, but on structure."
"I delegate execution, never sovereignty."
Final thesis statement:
This work argues that trustworthy human–AI systems should not rely on correct behavior, but on architectures that make harmful behavior structurally impossible.
Document version: 1.1 — December 2025
ivan-berlocher.github.io