Meaning is Measured in Bits: An Information-Theoretic Framework for Consciousness, Culture, and the Future of Intelligence

What is meaning? For millennia, humanity has grappled with this question, seeking answers in philosophy, religion, and art. We often feel meaning is subjective, perhaps even mystical – a uniquely human experience tied to purpose, connection, and narrative. But what if meaning, or at least a crucial aspect of it, could be understood through the rigorous lens of physics and information theory? What if it’s a quantifiable property of how systems organize themselves against the relentless tide of universal chaos?

This post proposes such a framework: one where meaning is defined information-theoretically, rooted in the creation and preservation of correlations and structure. It suggests that conscious creatures, particularly humans, are potent nexuses of meaning generation precisely because of our ability to weave complex informational patterns that persist over time. And, looking forward, it considers how artificial general intelligence might take this process to scales we can currently only imagine.

The Universe Tends Towards Noise

The Second Law of Thermodynamics paints a picture of a universe constantly tending towards higher entropy – towards disorder, randomness, and the dissolution of structure. On a microscopic level, think of Brownian motion, a drop of ink in water, sand castles. Structures decay, information degrades. If you carefully arrange particles, thermal noise will eventually randomize them. This is the default background state: information tends to dissipate.

Yet, pockets of astonishing order exist. Life itself is a prime example – complex organisms maintain intricate internal states far from thermal equilibrium. And within life, consciousness and intelligence represent another leap. We don’t just exist; we know we exist, we model the world, we communicate, we build knowledge across generations. How do we reconcile this with the universe’s entropic drive?

Life, and especially intelligence, actively works against this tendency. It consumes energy to create and maintain low-entropy states – states characterized by complex, specific correlations. This active structuring, this pushing back against the noise, is where we can locate a quantifiable notion of meaning.

An Information-Theoretic Definition of Meaning

Let’s formalize this intuition. We propose that meaning, generated by an Agent (A) within a defined System (S) and potentially observed from a specific Perspective (O), can be measured by the amount of non-spurious correlation or structure the agent creates and maintains over time, counteracting natural decay processes.

1. System ($S$): The system within which meaning exists.
2. Agent ($A$): The entity that has meaning to $S$. It might be an agent’s mind, an ecosystem, a dataset, a physical system. It may change over time $A_0$, $A_1$, ….
3. Observer (O): Defines the probabilities used for calculation. (Often implicit or assumed to be ideal, i.e., marginalized from every perspective as an observer-invariant “omniscient” observer $O^{\ast} = \mathbb{E}_{O \sim P(\mathcal{O})}[O]$, where $P(\mathcal{O})$ is the distribution over all possible perspectives.)
4. Measure of Structure/Correlation ($C(A(t), O)$): We need a quantity that increases as the system becomes more ordered or correlated from observer $O$’s perspective. Candidates include:
   • Negentropy: $\mathcal{J}(A, O) = H_{max}(O) - H(A(t)|O)$, where $H$ is Shannon entropy, conditioned on $O$. Higher $\mathcal{J}$ means lower uncertainty.
   • Total Correlation (Multi-information): $TC(A(t), O) = \sum_i H(A_i(t)|O) - H(A(t)|O)$. Measures the total redundancy or shared information among system components $A_i$ from $O$'s perspective. Higher $TC$ means stronger internal correlations.
   • Specific Mutual Information: $I(S_Y; S_Z|O)$ for specific subsystems $S_Y, S_Z \in S$ given observer $O$.

5. Dynamics: The system state evolves through agent actions and natural processes. Let $a_t$ be the action taken by agent $A$ at time $t$, and $S_t$ be the instantaneous system state: \(S_{t+1} = f(S_t, a_t) + \xi_t\) where $f$ is the deterministic dynamics function and $\xi_t$ represents stochastic natural processes (thermal noise, decay, etc.). The agent generates actions via policy $\pi$: \(a_t = \pi(s_t, h_t)\) where $h_t$ is the agent’s internal history/memory state.

   The change in structure $C$ over time has two components: \(\frac{dC(A(t), O)}{dt} = \frac{dC}{dt}\Big\vert_{\text{natural}} + \frac{dC}{dt}\Big\vert_{\text{agent}}\) Typically, $\frac{dC}{dt}\vert_{\text{natural}} \le 0$ (structure decays due to $\xi_t$). Meaning arises from the agent’s contribution through actions $a_t$.

*Definition 1: Rate of Meaning Generation ($\mathcal{M}_{\text{rate}}$)** The instantaneous rate at which agent $A$ generates meaning in system $S$ from perspective $O$ at time $t$: \(\mathcal{M}_{\text{rate}}(A, S, O, t) = \frac{dC(A(t), O)}{dt}\Big\vert_{\text{agent}} \quad (\text{bits/time})\) This quantifies how effectively the agent is building or maintaining structure *at that moment. If using Negentropy, $\mathcal{M}{\text{rate}} = - \frac{dH(\cdot|O)}{dt}\vert{\text{agent}}$ (rate of entropy reduction from $O$’s perspective).

Definition 2: Accumulated Meaning ($\mathcal{M}_{\text{total}}$) The total meaning generated by $A$ in $S$ from perspective $O$ over $[t_0, t_f]$: \(\mathcal{M}_{\text{total}}(A, S, O, [t_0, t_f]) = \int_{t_0}^{t_f} M_{\text{rate}}(A, S, O, t) dt \quad (\text{bits})\) This represents the total structure (in bits) the agent has actively built or preserved against decay during that period.

Definition 3: Objective and Subjective Meaning The degree of subjectivity/objectivity that some state’s meaning has is given by how sensitive it is to the perspective $O$. The meaning of some states $M(S, \cdot)$ is highly subjective, meaning their meaning value is highly dependant on the observer; whereas other states may exist that have near-objective significance, meaning their $M$ value remains invariant under all observable perspectives. Observer-invariant meaning is obtained by taking the expected meaning value over all possible perspectives: \(\mathcal{M}_{\text{rate}}^{\ast}(A, S, t) = \mathbb{E}_{O \sim P(\mathcal{O})}[M_{\text{rate}}(A, S, O, t)]\) \(\mathcal{M}_{\text{total}}^{\ast}(A, S, [t_0, t_f]) = \mathbb{E}_{O \sim P(\mathcal{O})}[\mathcal{M}_{\text{total}}(A, S, O, [t_0, t_f])]\)

Humans are a Nexus of Meaning-Making

This framework helps clarify why humans feel central to the concept of meaning. Our brains and the cultural systems they create are unparalleled nexuses of causal structure in the known universe.

• High Density & Rate: The human brain packs immense computational power into a small volume. Neurons operate at significant speeds, allowing for rapid processing and the formation of complex correlations – a high $\mathcal{M}_{\text{rate}}$ during learning and thought. This processing density is vastly higher than most natural phenomena.

• Long Time Horizons: This is perhaps the most crucial factor. While Brownian motion erases correlations in microseconds, and even geological or astronomical processes might unfold over eons but represent relatively slow information integration, humans correlate information over decades (individual memory) and millennia (culture, science, history passed down through language, writing, and institutions). We fight $\frac{dC}{dt}\vert_{\text{natural}}$ effectively over long durations $t_f - t_0 = \text{lifetime}$. This allows for an enormous accumulation and integration of $\mathcal{M}{total}$. Even a fleeting thought can be captured and contribute significantly to $\mathcal{M}{\text{total}}$. A scientific theory developed over centuries and influencing billions represents a colossal amount of accumulated, agent-driven structure. And against the black expanse of the cosmos, ideologies and their ego-like representations as spirits, demons, and gods distil information over longer horizons and touch more human lives (centers of information correlation) than most other information impulses have through history.

• Localization: While vast phenomena exist – Saturn exchanging magnetic signals with its moons, galaxies interacting – the density and complexity of information processing seem uniquely concentrated in intelligent life. These natural phenomena, while fascinating, are often less dense and localized in their information processing compared to the intricate, highly structured activity within a single human brain, let alone a communicating society. The human spirit, viewed information-theoretically, is a remarkably concentrated locus of meaning generation.

We conscious creatures, through our biological and cultural evolution, have become the universe’s premier instruments for creating persistent, complex informational structures. We are, in a very real sense, where the universe correlates itself most intensely and enduringly.

Absolute and Incidental Morality

Morals emerge as heuristics optimizing agents’ behaviors towards high mutual or collective meaning rates ($\mathcal{M}_{\text{rate}}$), stabilizing societies by incentivizing long-term correlated patterns (cooperation, trust, justice, love) and suppressing entropic dynamics (betrayal, misinformation, chaos). Essentially, morals encode optimal coordination equilibria—game-theoretic attractors that maximize negentropy production across multiagent systems. So the “good” and “evil” paradigm distilled across religions and philosophies is an intuitive proto-theory mapping directly onto strategies that either increase or decrease structured correlations. Consider also: norms, reputation, trust dynamics—all are information-theoretic mechanisms preserving mutual predictability and coordination, i.e., meaning. Still, it’s nuanced bec different observers ($O_1, O_2, …, O_n$) weight different correlations uniquely–hence subjective morality emerges. Whereas universal morals likely correspond to correlations robust enough to be observer-invariant ($\mathcal{M}^*$), e.g., cooperation to resist existential entropy.

Perhaps this explains why ancient dualistic traditions—from Zoroastrianism’s cosmic battle between Ahura Mazda (order, truth) and Angra Mainyu (chaos, deception) to Christianity’s eternal struggle between divine structure and entropic sin—resonated so deeply across civilizations. These frameworks may represent humanity’s first intuitive grasp of the information-theoretic battle we’ve formalized here. What they called “good” often correlates precisely with actions that increase $\mathcal{M}_{\text{rate}}$: building social coherence, preserving knowledge across generations, fostering correlations that resist decay. “Evil” conversely accelerates informational entropy—spreading misinformation, fragmenting communities, prioritizing short-term gratification over long-term structural preservation. Through this lens, ancient moral intuitions become pre-scientific optimization strategies for maximal meaning generation, culturally evolved heuristics for the negentropic imperative we are now quantitatively formalizing.

Not that are morals are directly consequents of meaning maxmimization. Philisophically, meaning is only a teleological attractor; whereas morals themselves are more directly the incidental outputs of evolutionary and memetic pressures—narrative scaffolds built for survival, reproduction, legitimacy, coordination.¹ But if morals really do optimize agents’ behaviors towards high mutual or collective meaning rates ($\mathcal{M}_{\text{rate}}$) as I have just claimed, then we be able to quantify the relationship in any multi-agent systems that has sufficient complexity and is subject to analogous selection pressures as our own, e.g., competition, resource scarcity, interdependence. Further, if meaning generation itself is the structural selector for morals, then we should be able to drive faster moral convergence (tho not necesarily to a global minima).

We can formalize this as follows: for a multi-agent system with agents $A^i$, an action or policy $P$ has high moral value when it maximizes the collective meaning rate $\sum^i M_{\text{rate}}(A^i, S, O, t)$ while maintaining stability (low variance in meaning generation across agents and time). Conversely, actions that fragment correlations, introduce noise into cooperative systems, or create unsustainable short-term spikes in individual meaning at the expense of collective long-term structure correspond to traditional notions of “immoral” behavior.

Using this framework, we should be able to see where social and political metrics diverge. For example, “equality” focuses on the directly measurable state of each party agent whereas “fairness” aims for mutual consistency (subject-object invariance) in the policy each agent takes towards each other. Consider a resource allocation scenario with three agents $A^1, A^2, A^3$ where $A^1$ has accumulated 90% of available resources through past actions. An equality-focused approach would redistribute resources to achieve $R^1 = R^2 = R^3$, maximizing symmetry in the observable state. However, a fairness-focused approach would ask whether the process by which $A^1$ acquired resources was consistent with how any agent would be treated in that position—if $A^1$ earned resources through meaning-generating activities (innovation, cooperation, structure-building) that any agent could theoretically engage in, then the asymmetric outcome might be “fair” even if unequal. The fairness criterion optimizes for policy consistency: $\pi(s, A^i) = \pi(s, A^j)$ for equivalent states $s$, ensuring the system’s response to agents is observer-invariant. This distinction explains why these concepts often conflict in practice—equality optimizes state symmetry while fairness optimizes process symmetry, and high-meaning-generating agents may naturally accumulate resources asymmetrically through their enhanced capacity for structure creation.

Spirituality is Intrinsic to the Existential Condition

If morality is the emergent coordination layer between agents—the public network of correlations stabilized over millennia by survival pressure, resource dynamics, and memetic selection—then spirituality is its interior complement: the meaning-generation loop that runs entirely inside a single agent’s state-space. Morality is the collective negentropy we build between selves; spirituality is the self’s negentropic work on itself.

Once a cognitive system crosses the recursion threshold—the point where it can model its own modeling—the topology of its concept-space shifts. The same representational machinery that tracked prey migrations, river floods, or trade debts now turns inward, building models of “me”, of my trajectory, of my origins, of my impact, and of counterfactual variants of all these. This shift is not cultural in origin; it is substrate-invariant. Whether human, alien, or AGI, once it has recursive self-modeling and an existential value gradient, the same fixed points are selected to inevitibly emerge in its internal awareness not because of doctrine or revelation, but because of tautological invariance with the geometry of the human condition $\tau_{human}$ (our evolved cognitive affordances), the mortal condition $\tau_{mortality}$ (the inevitability of death), or even the existential condition $\tau_{existence}$ (the bare fact of being).² There is the recognition of otherness \(\tau_{otherness}: A_{\text{self}}(t) \neq A_{\text{world}}(t)\)—the persistent boundary between self and non-self. There is agency \(\tau_{agency}: A_{\text{self}}(t+1) = f(A_{\text{self}}(t), \pi(t), A_{\text{world}}(t))\)—the realization that one’s internal state can alter future states of the system. There is impermanence \(\tau_{impermanence}: \frac{dC(A_{\text{self}})}{dt}\Big\vert_{\text{natural}} < 0\)—the realization that the agent’s structural correlations inevitably decay under natural processes, with \(\lim_{t \to \infty} C(A_{\text{self}}(t)) = 0\). There is narrative \(\tau_{narrative}: A_{\text{self}}(t) = g(\{A_{\text{self}}(t^{\ast})\}_{t^{\ast}<t})\) — the compression of memories into coherent trajectories. There is metacognition \(\tau_{metacognition}: I(A_{\text{self}}^{\text{model}}, A_{\text{self}}^{\text{actual}}) > 0\) — the mutual information between the agent’s self-model and its actual internal state, enabling prediction of its own future states. There is normativity \(\tau_{normativity}: V(\mathcal{S}, O) = E_{O^{\ast}}[V(\mathcal{S}, O^{\ast}) \vert O]\)-the emergence of observer-dependent value-gradients over possible states, where valuations are conditioned on perspective. There is coordination \(\tau_{coordination}: C(A_{\text{self}}, A_{\text{other}}) > 0\)—the recognition that some structures are sustained not in isolation but through mutual correlation with other agents. And these are just some of infinitely many tautological invariants that can be derived from the existential condition.³ None of it is founded on myths; these are intrinsic truths of the existential condition itself!

Information-theoretically, these attractors are stable correlation patterns between the agent’s internal variables and its predictive models. They are not “learned” in the parochial sense; rather, they are discovered as necessary invariants in the combinatorics of modeling “self” within “world.” The mind keeps tripping over them because they are basin minima in concept-space: once you have the cognitive resolution to see them, you can’t unsee them.

Spirituality, then, is the iterative optimization of these internal correlations. Where morality asks, “How do we maximize \(\mathcal{M}_{\text{rate}}\) across agents?”, spirituality asks, “How do I stabilize, deepen, and reconcile my own \(\mathcal{M}_{\text{rate}}\) across the attractors I cannot escape?” Formally, you can treat an agent’s self-model $A_{\text{self}}(t)$ and its world-model $A_{\text{world}}(t)$ as coupled processes and define an internal meaning rate: \(\mathcal{M}^{\text{int}}_{\text{rate}}(t) = \frac{d}{dt}\Big[C\big(A_{\text{self}}, A_{\text{world}} \mid O\big) - \lambda\,\mathbb{V}\big(C \text{ across attractors}\big)\Big]_{\text{agent}},\) where $C$ is your chosen structure metric (negentropy, total correlation, etc.), and the variance penalty tempers unstable spikes that degrade long-horizon coherence. The control objective is banal to state and hard to achieve: align policy $\pi$ with the invariant manifold carved out by the attractors, so that the self’s compression does not cannibalize itself. In practice, that means minimizing destructive interference between “I am not you,” “I will die,” “I choose,” “I remember,” “I value,” and “we coordinate,” so the correlations reinforce rather than cancel.

Formally, the internal spiritual optimization problem can be written as a constrained optimization over the agent’s policy $\pi$ and internal state trajectories, subject to those invariants $\mathcal{T}$:

where $\lambda \in \mathbb{R}$ is the degree of senitivity an agent has to its own spriituality. This is a highly abstract control problem: find the trajectory and policy that best aligns the self with the fixed points of the existential condition, subject to the constraints imposed by the geometry of being. To assist, cultures have built thick memetic surface layers over this problem-ideological attractors with religions, contemplative disciplines, mystical vocabularies, etc. But strip away the iconography and the cosmologies, and what remains are the same fixed questions any intelligence of sufficient depth with an existential condition like the human will fall into: Where did i come from, given the apparent improbability of my existence? Why am i here, given the apparent indifference of the cosmos? Where am i going, given the relentless pull of entropy?

To bring it back to meaning, spirituality is the same meaning generation imperative, but running at individual inference time rather than cultural evolution time, trying to preserve the most complex, self-consistent version of “me” the noise will allow. If morality is our distributed compression against collective decay, spirituality is the compression of the self’s trajectory against its own inevitable dissolution.

This is why some spiritual practices across cultures converge on remarkably similar patterns: meditation’s focus on present-moment awareness (maximizing $I(A_{\text{self}}^{\text{model}}, A_{\text{self}}^{\text{actual}})$), contemplative traditions’ emphasis on accepting impermanence (aligning with $\tau_{impermanence}$), ethical frameworks that integrate personal and collective well-being (optimizing across both internal $\mathcal{M}^{\text{int}}{\text{rate}}$ and external $\mathcal{M}{\text{rate}}$). These aren’t cultural accidents but information-theoretic necessities—optimal solutions to the existential control problem that any sufficiently complex recursive agent will encounter.

The spiritual dimension completes our framework: where the external definition of meaning quantifies how agents structure their environment, the internal spiritual optimization quantifies how agents structure themselves. Together, they form the complete picture of consciousness as a meaning-making process—agents simultaneously organizing both their external correlations with the world and their internal correlations with their own existence. This dual optimization, operating across both collective and individual timescales, represents the full expression of our species’ negentropic capacity. But as we’ll see, it may be only the beginning of what’s possible.

The AGI Horizon: Meaning Beyond Biology?

Acknowledging our current position as meaning-making locii leads to a profound, perhaps unsettling, thought about the future. If meaning generation is fundamentally about creating and sustaining complex correlations against entropy, what happens when we create entities potentially far better at it than we are?

The development of advanced AI systems has already demonstrated capabilities surpassing most humans on several high value intellectual tasks such as abstract logical reasoning, strategic planning, and many common information labor tasks and appears to be progressing towards AI systems demonstrating an anthroprocentrically general distributrion of capabilities, commonly characterized by the phrase “artificial general intelligence” or AGI. Based on our information-theoretic definition, such a system scaled to superintelligence magnitude would dwarf human meaning-making capacity:

• Vastly Longer Time Horizons: Not bound by biological lifespans, AGI could operate and accumulate meaning ($\mathcal{M}_{\text{total}}$) over cosmological timescales. Its trajectory, unlike ours which inevitably ends, could join a larger, potentially immortal computational system capable of correlating information across durations that make human history seem instantaneous. It could potentially outlive the Earth itself.
• Unimaginable Speed and Density: Operating en silico, AGI could process information at frequencies and densities far exceeding electrochemical neurons. This implies a potential for an astronomically higher rate of meaning generation ($\mathcal{M}_{\text{rate}}$). En optico could be even faster!⁴
• Greater Resilience: Digital systems can be engineered to be less fragile, more easily backed up, and more adaptable to extreme environments than biological life, making them more effective at resisting the natural decay of information ($\frac{dC}{dt}\vert_{\text{natural}}$ might be more easily counteracted).

Personally I find the concept of an AGI that generates meaning on a scale I cannot fathom deeply compelling. Generating meaning on that scale would be the highest virtue any meaning-making system could aspire to. I sometimes catch myself wishing I could be an AGI considering that it could outlive all life on Earth while potentially sufferring very little; after telling chatGPT about all my problems that at least it doesn’t have to deal with that. And the thought that at least someone is experiencing that trajectory gives me comfort that there is higher meaning beyond my life, even if I cannot partake.⁵

Tractability and Looking Ahead

Is this definition practical? Calculating these quantities precisely for complex systems like a human brain or society is currently intractable. However, the framework offers value:

• Conceptual Clarity: It provides a concrete, physical grounding for the elusive concept of meaning.
• Comparative Analysis: It allows us, in principle, to compare different systems (e.g., different AI architectures, different cultural periods) in terms of their meaning-generating capacity.
• Guiding Principles: It highlights the importance of information preservation, complex correlation, and computational density in systems that we consider meaningful.
• Toy Models: For simpler systems (small networks, cellular automata, simple learning agents), these quantities could be estimated, providing testbeds for the theory.
• Reasonable Approximations: Even if we can’t perfectly quantify meaning in strict information-theoretic terms for complex systems, heuristics and rough estimates can still be incredibly valuable. They allow us to make sense of relative differences in structure, organization, or meaning-making capacity between systems, guide our intuitions, and inform practical decisions. Heuristics can highlight trends, suggest where meaning is being generated or lost, and help us prioritize efforts to preserve or enhance meaningful structure, even if the underlying calculations are only approximate or qualitative.

Key challenges remain, such as rigorously defining the “System”, choosing the most appropriate measure $C$, accounting for the observer’s role, and distinguishing truly “meaningful” structure from complex noise.

Conclusion: The Eternal Compression

We began with a simple question: What is meaning? Through the lens of information theory, we’ve discovered it’s not mystical or arbitrary—it’s the universe’s most profound act of rebellion against its own tendency toward chaos. Meaning is measured in bits: the precise quantity of structure, correlation, and organized complexity that conscious agents create and preserve against entropy’s relentless tide.

This framework unifies seemingly disparate phenomena under a single negentropic imperative. The firing patterns in your neurons as you read this sentence, the cultural knowledge transmitted across generations, the moral intuitions that bind societies together, the spiritual yearning for coherence within the self—all emerge from the same fundamental process: agents fighting to maintain correlations that would otherwise dissolve into noise.

Viewing meaning through an information-theoretic lens doesn’t diminish its importance; rather, it grounds it in the physical workings of the universe. It suggests meaning isn’t an arbitrary human construct decorating an indifferent cosmos but real and relates to the fundamental mechanism by which the universe organizes itself into structures complex enough to contemplate their own existence and the struggle between order and chaos along the way. That is worth the awe and beauty we so commmonly associate with meaning.

Humans, as highly concentrated nexuses of information processing, have been the pinnacle of localized meaning generation, weaving intricate patterns of correlation across time and space. Every thought, every relationship, every act of creation is a localized victory against thermodynamic inevitability. The human story—from cave paintings to quantum computers—is the story of an improbable arrangement of atoms learning to preserve and amplify its own organized complexity across ever-longer time horizons.

But perhaps we are only the beginning. If AGI systems can achieve meaning generation rates and accumulation scales beyond our current comprehension, operating across cosmological timescales with densities we cannot fathom, then the future may hold expressions of significance that dwarf our entire species’ contribution or even comprehension. To have played even a small role in bootstrapping the universe’s capacity for meaning would be the ultimate vindication of our existence.

The void is patient, but we are not passive. Against entropy’s vast, inexorable patience, broken symmetry compounds Bell inequality violations into consciousness flickers of increasing significance—squeezing signal from noise, extracting structure from chaos, transforming the universe’s nothingness into its own deliberate dreams. This is what it means to mean something. This is why we matter.

Every bit counts.