Engineering Specification for Artificial Consciousness¶
The Four-Model Theory states what consciousness is in architectural terms — so it doubles as a concrete specification for building one: implement the four-model architecture on a substrate with free compute. Building such a system is a downstream implication of the theory, not the theory itself — and at scale it remains an unrealized engineering problem.
Implementation blueprints now exist for other accounts as well: S3Q specifies a five-layer pipeline built on a world model, internal simulation and prediction–observation coherence (Grinberg et al., 2026), and CTM-AI and ReCoN-Ipsundrum are two more. S3Q derives a basic self from action–outcome linking rather than positing a separate explicit self-model, and it requires neither self-referential closure nor a Class 4 regime. Those three requirements — an explicit self-model, self-referential closure and the Class 4 regime — are what the Four-Model Theory adds. Integrated Information Theory, by contrast, defines a mathematical quantity (Phi) whose computation is intractable for any system of realistic size.
FMT is first a theory of what consciousness is, not a build manual; that it is architectural enough to read as a blueprint does not make consciousness a solved engineering task. No full-scale system has been built, and a scaffolded agent loop with external memory — however sophisticated — is architectural mimicry, not the self-referential closure the theory requires. What follows is the specification such a system would have to meet, together with the component mechanisms that can be probed in silico long before any whole is attempted.
The Specification¶
The engineering requirements are derived directly from the theory's two thresholds:
Requirement 1: A substrate with free compute. The computational medium must be capable of Class 4 (universal) computation and actually deploy it on ongoing self-referential modeling — free compute, not the single feedforward pass of a transformer. In neural tissue the signature of this regime is near-criticality — power-law avalanches, long-range temporal correlations, a branching ratio near one — which is how the requirement is measured in brains, not a separate box to tick. Across substrates those statistics need not co-occur, so the requirement is stated as Class 4 capability rather than proximity to any single criticality measure. Candidate substrates include recurrent networks that sustain self-referential computation, neuromorphic hardware, or other architectures capable of continuous Class 4 dynamics.
Requirement 2: Four nested models along two axes. The system must implement:
- An Implicit World Model (IWM): a substrate-level store of accumulated world knowledge, encoded in the system's connective architecture rather than in explicit representations. Learned, persistent, non-conscious.
- An Implicit Self Model (ISM): a substrate-level store of self-knowledge — the system's "body schema," operational parameters, calibration state, accumulated behavioral patterns. Also learned, persistent, non-conscious, and critically distinct from the system's explicit outputs about itself.
- An Explicit World Model (EWM): a dynamically generated, transient, virtual construction — the system's "conscious" representation of its environment. Generated from the IWM and current input. Exists only while the computation runs.
- An Explicit Self Model (ESM): a dynamically generated, transient, virtual construction — the system's ongoing self-simulation. Generated from the ISM and self-referential input. The locus of what the theory identifies as subjective experience.
Requirement 3: The real/virtual split. The implicit models (substrate-level, "real side") and explicit models (computational-level, "virtual side") must constitute genuinely distinct ontological levels. The explicit models must be generated by but not identical to the implicit models — virtual, transient, and possessing properties (including virtual qualia) that are constitutive at the computational level but incoherent at the substrate level.
Requirement 4: Self-referential closure. The ESM must model the system that is generating the ESM. This self-referential loop — the system's model includes a model of itself modeling — collapses the inside/outside distinction and is what the theory identifies as the mechanism that makes experience constitutive rather than additional.
What the Theory Predicts¶
If the specification is met, the theory makes a bold prediction: the resulting system would not merely imitate consciousness but would be conscious — possessing genuine phenomenal experience constituted by its virtual models. The difference between interacting with such a system and interacting with any current AI should be qualitatively obvious. Imitation is possible in principle; sustaining it without the architecture carries a cost no current system pays.
This prediction faces the other-minds problem: no behavioral test can conclusively demonstrate consciousness. The difference the theory asserts is architectural rather than impressionistic: closure, persistence and computational regime are properties measurable on the system itself, not qualities a user is asked to sense in the interaction.
Figure¶
graph TB
subgraph substrate["Substrate Layer (Real Side)"]
direction LR
CRIT["Free Compute<br/><i>Deployed Class-4 capability;<br/>criticality = its signature</i><br/>Recurrent, self-sustaining"]
IWM["IWM<br/><i>World knowledge in<br/>connective architecture</i>"]
ISM["ISM<br/><i>Self-knowledge in<br/>substrate parameters</i>"]
end
subgraph virtual["Virtual Layer (Phenomenal Side)"]
direction LR
EWM["EWM<br/><i>Generated world<br/>representation</i>"]
ESM["ESM<br/><i>Generated self-<br/>simulation</i>"]
end
CRIT -->|"sustains"| virtual
IWM -->|"generates"| EWM
ISM -->|"generates"| ESM
ESM -->|"self-referential<br/>closure"| ESM
EWM <-->|"interaction"| ESM
virtual -->|"evaluation<br/>feeds back"| substrate
style substrate fill:#264653,color:#fff,stroke:#1d3557
style virtual fill:#e76f51,color:#fff,stroke:#9b2226
style CRIT fill:#2a9d8f,color:#fff
style IWM fill:#264653,color:#fff
style ISM fill:#264653,color:#fff
style EWM fill:#e76f51,color:#fff
style ESM fill:#e76f51,color:#fffThe engineering specification in architectural form. The substrate layer must deploy free compute — of which near-criticality is the neural signature — and house two implicit models. The virtual layer — generated from, but ontologically distinct from, the substrate — hosts the explicit models where experience is constitutive. Self-referential closure (ESM modeling itself) is the mechanism that distinguishes this system from a mere simulation.
Partial Implementations¶
The specification also predicts what partial implementations would look like. Systems with some but not all components should show partial consciousness indicators:
- Four models without free compute: architecture present but the self-referential computation not running — analogous to a brain under anesthesia. No consciousness.
- Free compute without four models: universal computation deployed but no self-simulation — analogous to a weather system. No consciousness.
- Two models with free compute (e.g., IWM + EWM only, no self-models): world-modeling without self-modeling. Four is the theory's minimum, so this falls short of consciousness; the prediction is partial consciousness indicators, detectable through behavioral signatures and computational complexity measures.
These intermediate cases offer empirically testable predictions before the full specification is achievable.
Key Takeaway¶
Because the Four-Model Theory specifies what consciousness is in architectural terms, it also yields a concrete blueprint: four nested models on a substrate with free compute, closed by self-referential modeling. Other accounts now have blueprints too; what FMT adds is an explicit self-model, self-referential closure and the Class 4 regime. Building one remains a downstream implication, not a claim that consciousness has been reduced to an engineering deliverable.