Two leading theories of consciousness, their core claims, and what they predict about awareness
"Consciousness-first" — starts from phenomenological properties of experience and derives physical requirements.
Consciousness corresponds to Φ — the amount of information a system generates beyond what its parts generate independently. Higher Φ = more consciousness.
Functional/computational — consciousness emerges from brain-wide information sharing via a "global workspace."
Consciousness arises from sudden, coherent "ignition" of workspace neurons that broadcast content brain-wide while inhibiting competing representations.
Measure Φ via Perturbational Complexity Index (PCI). If PCI > 0.31, the patient has some level of consciousness even without behavioral responses. Posterior cortex integration is key — preserved complexity indicates preserved experience.
Can detect hidden awarenessLook for global ignition patterns using fMRI or EEG. Consciousness requires frontoparietal network activity. If no global broadcast occurs, no consciousness — but command-following paradigms can reveal covert awareness.
Can detect with right tasksAnesthetics reduce Φ by disrupting integration. Different drugs affect consciousness differently: propofol eliminates both experience and dreams (low Φ), while ketamine preserves some dream-like states (higher Φ despite unresponsiveness).
Φ tracks depth of anesthesiaAnesthesia blocks the global workspace — disrupting long-range connectivity between frontal and posterior regions. When ignition can't occur, content can't be broadcast, and consciousness is abolished.
Disrupted global broadcastDreams are fully conscious experiences. Posterior cortex remains integrated during REM sleep, generating Φ. The content differs from waking but consciousness is preserved — this is why PCI remains high during dreams.
Full consciousness preservedDreams involve partial global workspace activation. Sensory input is blocked but internal representations can still "ignite" and be broadcast, creating dream experiences. Reduced prefrontal involvement explains lack of insight.
Partial workspace activationCurrent AI (LLMs, neural networks) has negligible Φ. Von Neumann architecture lacks intrinsic causal power — it simulates computations rather than instantiating them. Only neuromorphic hardware could potentially achieve consciousness.
Current AI not consciousMore permissive: if an AI implements global workspace architecture — combining attention, memory, and broadcast mechanisms — it could be conscious. Current LLMs lack the recurrent, integrative processing, but future architectures might qualify.
Possible with right architectureSevering the corpus callosum creates two separate conscious entities — each hemisphere has its own Φ and therefore its own experience. The person becomes two consciousnesses sharing a body.
Two separate consciousnessesGlobal workspace is disrupted but not eliminated. Each hemisphere may have its own workspace for some content, but unified consciousness for whole-body actions may persist through subcortical connections.
Partially divided workspace