Two concepts haunt modern science like unsolved riddles. Information—the currency of the digital age, the stuff of genes and neurons, perhaps the fabric of reality itself. And consciousness—the inner light of experience, the fact that there's something it's like to be you reading these words.

For decades, these mysteries have been treated as separate problems, but that’s beginning to change. The connection becomes clearer once we ask what information actually is—and recognize that it comes in two distinct but intimately connected forms.

The first definition: Information as order—measured as the distance from the statistical distribution representative of thermodynamic equilibrium. This is information in something.

The ordered state is a low-entropy state, and entropy measures the system’s proximity to the most probable (equilibrium) state.

Therefore, a system is "far from equilibrium" if its components are statistically correlated, because correlation among components is order. When parts are correlated rather than independent, you have structure. The system occupies a state that’s improbable relative to chance. You can predict something about one part by knowing about another.

The opposite—maximum entropy—is defined by complete statistical independence among components. This is the “molecular chaos” assumption underlying Boltzmann’s H-theorem: at equilibrium, each particle’s state is statistically independent of every other’s. No pattern, no structure, no organization. Just randomness.

So, information IN something is internal statistical correlation—the degree to which a system’s components hang together rather than behave independently.

We have a formal measure for this: integrated information, Φ (phi), developed by the neuroscientist Giulio Tononi and colleagues. Φ quantifies how much a system is “more than the sum of its parts”—the information generated by the whole that can’t be reduced to its parts. A system with high Φ has deeply integrated........

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