IWMT (Safron 2020, 2022, 2026)
Status: NEAREST COMPUTATIONAL NEIGHBOR for the human side of the architecture.
What IWMT provides
A computational account of consciousness as coherent world modeling, a proposed biophysical mechanism (SOHMs), multi-level analysis (computational, algorithmic, implementational), and machine learning architecture mappings.
If approximately correct, IWMT provides a candidate computational definition of what the architecture's target construct "coherence" consists of: spatiotemporally and causally coherent functioning of a probabilistic generative world model. Under this interpretation, the catecholamine-PFC mechanisms describe mechanisms that degrade the conditions for this coherent functioning.
What IWMT does NOT provide
Engineering specification for what to do when the generative model degrades, actuator logic, objective function for an external system, caring governance, cost/access constraint, or an experimental program.
HCH convergence note (THEORETICAL)
Safron et al. (2026) propose the Human Consciousness Hypothesis with three principles: Genesis, Coherence, and Second-order perception. These map onto the notebook's independently derived constructs: Genesis -> meta-capability defense (D2); Coherence -> constraint closure; Second-order perception -> Frankfurt's second-order volitions. Whether this convergence is evidentially significant requires independent assessment. [UNCERTAIN]
Positioning statement
IWMT provides a candidate computational definition of what the architecture maintains. What IWMT does not specify is how an external system should detect, respond to, or prevent degradation. This architecture provides the engineering complement: objective function, control topology, actuator logic, and governance constraints. The relationship is potential complementarity, not dependency.
Evidence status
THEORETICAL. IWMT is a theoretical model, not an established finding. SOHMs have not been independently validated.
Sources
- Safron 2020 (Front. Artif. Intell. 3:30)
- Safron 2022 (Front. Comput. Neurosci. 16:642397)
- Safron, Klimaj, & Sheikhbahaee 2026 (AAAI)