More Profound Than Fire: How AI and Ancient Wisdom Are Teaming Up

The Second Law of Thermodynamics establishes that entropy in an isolated system never decreases. Schrödinger extended this to biology in 1944: organisms maintain their ordered state by importing negative entropy from their environment. Prigogine formalised how open systems maintain local order only by exporting entropy — at an energy cost that increases with distance from equilibrium.

A marriage, a business, a body, and a nation are all dissipative structures. The moment energy input falls below the maintenance threshold, the system doesn't pause — it degrades. Ginsberg documented that US universities hired 517,636 administrators from 1987–2012 while educational output stagnated. Tainter demonstrated across seventeen civilisations that collapse occurs when the marginal cost of complexity exceeds its marginal benefit.

Shannon's noisy channel coding theorem proves mathematically that for any communication channel with a given noise level, there exists a maximum rate C at which information can be reliably transmitted. This is not a guideline — it is as absolute as the speed of light. A person can process approximately 120 bits per second of conscious information. Understanding speech requires roughly 60 bits/second. Attending to two simultaneous conversations is not difficult — it is physically impossible.

The epidemic of burnout is not a motivational failure — it is a channel capacity violation. The solution is never to try harder. It is to reduce noise or increase bandwidth through rest, focus, or structural simplification.

Eagleman & Pariyadath (2009) demonstrated that subjective duration is a signature of coding efficiency. Repeated stimuli undergo neural repetition suppression — the brain allocates fewer resources because familiar events carry less information in the Shannon sense.

This creates a fundamental asymmetry: routine feels slow while happening but fast in retrospect (few memories encoded). Novelty reverses both — novel experiences feel fast in the moment but slow looking back (dense memory encoding). This is why a two-week holiday in a new country feels like it lasted a month, while six months of office routine compresses into a blur.

Schultz, Dayan & Montague (1997, Science) established that midbrain dopamine neurons fire in direct proportion to reward prediction errors. This is the physical mechanism by which the brain updates its model of reality. In Shannon's framework, the information content of an event is I = −log₂(p). An event with certainty carries zero information. The dopamine system is, functionally, a biological implementation of Shannon's surprise metric.

Karl Friston's Free Energy Principle resolves an apparent paradox: if organisms minimise surprise (to maintain homeostasis), why do they actively seek novelty? The answer lies in active inference — organisms deliberately forage for information that they have the current channel capacity to integrate, because reducing future uncertainty requires seeking present prediction errors. Curiosity is mathematically required by surprise-minimisation.

In network science, betweenness centrality measures the fraction of shortest paths between all node pairs passing through a given node. Removing a node with high betweenness centrality forces the entire network to find costlier alternative paths — or splits it entirely. Burt's structural holes theory demonstrated that individuals who bridge disparate networks receive disproportionate returns in salary, promotions, and influence.

A person who hoards resources but connects to few other nodes is a peripheral storage device. The system loses nothing by routing around them. A person who bridges industries, cultures, or disciplines has high centrality. Removing them is catastrophically expensive.

In control theory, a feedback loop with excessive gain becomes unstable — oscillating with increasing amplitude until the system saturates or destroys itself. When a system dedicates increasing processing capacity to monitoring a single variable, it reduces the bandwidth available for processing all other variables. The environmental signals that would actually lead to the desired outcome are missed because the channel is saturated with self-referential monitoring noise.

This is why people often achieve goals after ceasing to pursue them obsessively. It is not mystical — it is informational. The practical prescription: set the direction, then redirect processing resources to the environment rather than to the internal state of wanting.

Tainter's archaeological analysis across seventeen civilisations showed that complexity is initially adaptive but eventually becomes maladaptive. Olson's institutional sclerosis theory formalised how stable democracies accumulate rent-seeking coalitions that increase regulatory complexity while reducing adaptive capacity. Klimek, Hanel & Thurner identified the mathematical phase-transition boundary where bureaucratic growth becomes self-sustaining and exponential.

As a system adds rules, its internal state space grows combinatorially. Each new rule can interact with every existing rule. Beyond the critical threshold, the system spends more energy on self-coherence than on its ostensible purpose.

Sexual reproduction exists despite being energetically expensive because it generates genetic novelty. Schumpeter's creative destruction formalised how innovation generates disproportionate returns. Bunzeck & Düzel (2006) demonstrated the brain allocates preferential encoding resources to novel stimuli. From the system's perspective, agents generating novel information are the only ones expanding its state space — the only ones making it capable of new responses.

If your work can be described by someone who has not seen it, its information content is zero. A consulting report that says what every consulting report says, a CV that lists what every CV lists — these are high-entropy, low-information outputs. The system does not reward them because they do not teach it anything new.

Dehaene's Global Neuronal Workspace theory established that conscious awareness requires coordinated activation across prefrontal, parietal, and sensory cortices — an energetically expensive state the brain cannot maintain continuously. Kahneman's System 1/System 2 framework distinguished between automatic and deliberate processing. The danger in modern environments: either demanding conscious attention for mundane tasks (burnout) or rendering the environment so predictable that consciousness is rarely triggered (cognitive dormancy).

Google Cloud's 2026 AI Agent Trends Report surveyed 3,466 global executives and found the shift from "instruction-based" to "intent-based" computing: employees define outcomes, agents determine steps. Telus reported 57,000 team members saving 40 minutes per AI interaction. This isn't mere efficiency — it is the conservation of humanity's scarcest resource.

Galton's regression to the mean is one of the most robust empirical findings in statistics, observed across genetics, sports, economics, and clinical outcomes. Kahneman identified it as the phenomenon most consistently confused with causal explanation — people attribute reversion to skill or karma when it is purely mathematical. Extreme states are low-entropy configurations: statistically improbable given the system's state space.

This law dissolves the false dichotomy between optimism and pessimism. Suffering is temporary because extreme negative states are as unstable as extreme positive ones. The wise response to both extremes is the same: invest the energy that would be spent on emotional response into structural work that moves the baseline itself.