Integrated Information Theory - IIT
Updated 2026-08-01
INTRODUCTION
English translation pending.
CORE DEFINITION
Proposed by Giulio Tononi, integrated information theory identifies consciousness with a system's capacity for integrated information, denoted phi. A system is conscious to the degree that it specifies a cause-effect structure that is both highly differentiated and irreducible to its parts. The qualifier is integration: complexity alone is not enough, since a system whose parts operate independently carries high entropy but low phi. The theory remains contested, and computing phi is intractable for large systems.
SCAFFOLDING EFFECT
Reduce cognitive load
- Integration test: ask whether a group's information is irreducible to its individual members. - Collective check: treat shared context and coupling as the basis of a group mind. - Structure scan: look for dense causal links rather than for headcount or raw complexity.
Anchor fast decisions
A system that can be decomposed into independent parts generates no information beyond what those parts already carry. When parts are tightly coupled, the state of the whole constrains its own past and future in ways no subset does, which is the quantity phi measures. On this view consciousness tracks that irreducible causal power, which is why integration rather than raw complexity is the criterion.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Integrated_information_theoryverified
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