The Algorithm of Civilization: A Computational Sociology History of Thermodynamics and Computational Complexity #

Introduction: Physics as Destiny #

Human history is often depicted as an epic composed by heroes, ideas, and opportunities. However, this narrative overlooks a deeper, colder reality: history is, in essence, an algorithmic competition.

Every evolution of civilization, every shift in ideology, is not accidental. It is the process of a vast, self-organizing computational system—human society—continuously seeking better optimization algorithms to maintain its existence in a universe full of uncertainty.

This analysis aims to strip away the romanticism of history and conduct a thorough, formal “computational autopsy” on the various stages of human social development and ideological trends, starting from two fundamental first principles: Thermodynamics and Computational Complexity Theory. We will argue that different social forms are essentially different computational paradigms, each with its own algorithmic complexity and thermodynamic efficiency.

Ultimately, we will reveal that our current state, the “Capital Siege” surrounded by high walls, is neither the end of history nor a moral choice. It is merely the inevitable output of the most computationally feasible and thermodynamically stable algorithm discovered so far on the specific computational substrate of Earth.

I. First Principles: Thermodynamics and Computation as Social Dynamics #

Before diving into the analysis, we should understand our measurement tools.

1. The Free Energy Principle (FEP) #

According to the cornerstone of IPWT—the Free Energy Principle—any self-organizing system (from a single-cell organism to human society), in order to maintain its existence (i.e., to maintain a stable non-equilibrium steady state far from thermodynamic equilibrium), must continuously minimize its Variational Free Energy. At the sociological level, this can be translated as:

• Existence is Prediction: A society, through its institutions, culture, and technology, constantly makes predictions about its environment (nature, other societies) and internal states (economy, politics).
• Crisis is Prediction Error: Wars, famines, financial collapses, revolutions—these are all manifestations of a massive prediction error (Surprise) between the system’s internal model and harsh reality.
• Governance is Active Inference: Society minimizes prediction errors through active inference. This involves two types of actions:
  • Changing the internal model (perception): Amending laws, developing science, adopting new ideologies.
  • Changing the external world (action): Waging wars, building infrastructure, changing modes of production.

A successful social form is a system that can more efficiently minimize its free energy.

2. Computational Complexity Theory as a Physical Constraint #

A society, no matter how grand its ideals, cannot run an algorithm that exceeds its “computational capacity.” This “computational capacity” includes:

• Information Transmission Bandwidth and Latency: Roads, postal services, telegraphs, the internet.
• Information Processing Power: The cognitive limits of the human brain, the processing capacity of bureaucracies, the compute power of computers.
• Information Storage Capacity: Oral history, writing, printing, databases.

Computational complexity theory provides a ruler to measure the cost of “running” an ideology in the real world. If an ideology’s intrinsic algorithm is computationally intractable, then no matter how philosophically appealing it is, it is doomed to collapse under the physical constraints of reality.

II. A Computational Autopsy of Ideologies: An Algorithmic Evolutionary History #

Before proceeding, we first need to define the core variable N in our model: it represents the number of basic computational units or independent variables in the socio-economic system, which could be an individual, a family, or a firm. In short, N is the total number of basic “nodes” the system needs to coordinate and manage. Now, let’s use these two scalpels to analyze the major ideologies in human history.

1. Primitive Society: Distributed Brute-Force Search #

• Structure: Small-scale, highly decentralized tribal units.
• Algorithm: Each tribe acts as an independent processor, conducting a local, parallel brute-force search (trial and error) on the environment. Information is exchanged between tribes with extremely low bandwidth (oral tradition) and extremely high latency.
• Thermodynamic Properties: This is a high-entropy, high-free-energy system, extremely fragile and constantly on the verge of collapse. Any minor prediction error (like a drought or a predator attack) could lead to the demise of an entire computational unit (tribe).

2. Agricultural Empire/Feudalism: Centralized Serial Processing with High Latency #

• Structure: A pyramidal hierarchical structure with power concentrated at the top in a monarch or theocracy.
• Algorithm: This is a primitive central planning system. The top node (the emperor) attempts to perform global optimization for the entire system but is limited by abysmal information infrastructure. The transmission of commands and the uploading of feedback are plagued by enormous latency, distortion, and information loss.
• Thermodynamic Properties: By establishing order, the system locally reduces entropy and increases stability. But this order is rigid and brittle. Lacking effective feedback mechanisms, the system cannot adapt to drastic environmental changes. Prediction errors accumulate until they are released through a “systemic collapse” like a dynastic change or a peasant uprising.

3. Free-Market Capitalism (Theoretical Ideal): Massively Parallel Heuristic Search #

• Structure: A distributed network composed of countless independent economic agents (individuals, firms) pursuing their own self-interest.
• Algorithm: This was an “algorithmic Cambrian explosion” for human society. It decomposes an extremely complex global optimization problem into billions of parallel, local optimization problems. Price signals, as a highly efficient, low-dimensional information compression format, become the “message-passing interface (API)” of this distributed computational system.
• Thermodynamic Properties: This is an incredibly efficient free-energy minimization engine. Through parallel, decentralized trial and error, it can explore the solution space at astonishing speed and adapt to environmental changes. It triumphed over feudalism not because it was morally “superior,” but because it was algorithmically superior.

4. Marxism (Central Planning): Global Combinatorial Optimization #

• Structure: A single, omniscient central planning committee that attempts to replace the market and rationally allocate resources for the entire economic system on a global scale.
• Algorithm: This is computationally equivalent to solving an NP-Hard global combinatorial optimization problem. Its exponential complexity O(c^N) arises from the combinatorial explosion: assuming each of the N units has c possible production or consumption choices, the planner would, in principle, need to evaluate all c^N possible combinations to find the global optimum. The addition of each new social unit increases the computational difficulty exponentially, rapidly making it unsolvable in practice.
• Thermodynamic Properties: A system that theoretically promises the lowest entropy (perfect order) but is doomed to fail in practice due to computational intractability. It attempts to solve a problem requiring infinite computational resources with a finite Turing machine. The inevitable result is catastrophic prediction errors and system collapse.

5. Fascism: Greedy Algorithm with Forced Pruning #

• Structure: Extreme, violent central authority that attempts to integrate the entire society into a single-willed organism.
• Algorithm: This is a pathological forced alignment algorithm. It does not seek a complex global optimum but tries to forcibly align the behavior of all N units to a simple, central goal. Its high-order polynomial complexity O(N^c) stems from the networked costs of surveillance and enforcement. To ensure every one of the N units conforms, the system must monitor their increasingly complex interactions (from individuals O(N), to pairs O(N^2), to more complex social networks O(N^c)). The “control exponent c” here represents the depth and dimensionality of its social control network; because it attempts to permeate everything, c becomes extremely large, leading to unsustainable enforcement costs.
• Thermodynamic Properties: A highly unstable, high-energy dissipative structure. It maintains its internal false order by violently and unsustainably exporting massive amounts of entropy to the outside (through war and aggression), inevitably leading to self-destruction.

III. The Inevitable Tumble: The Rise of the Capital Siege #

Now, we can answer the ultimate question: Why did we end up tumbling into the “Capital Siege”?

The answer is: because a “pure free market” is thermodynamically unstable.

The Free Energy Principle applies not only to society but also to every agent within the market. In a brutal competitive environment, the system will spontaneously move towards a more energy-efficient structure.

1. From Atoms to Molecules: Small firms (atoms), in order to reduce transaction costs, enhance predictive capabilities, and combat uncertainty, spontaneously merge into larger corporate groups and multinational corporations (molecules). This is an entropy-reducing process.
2. The Emergence of Platforms: With technological development, platform companies (Google, Amazon, BlackRock, DMF…) that control information and computational infrastructure have become the new central nodes. By providing APIs and services, they restructure the previously chaotic peer-to-peer interactions into a more efficient, but controlled, “hub-and-spoke” model.
3. The Construction of the Siege: Eventually, the system evolves into what we have today—a hybrid system. It retains the “shell” and “vitality” of the free market (allowing innovation and competition within the walls), but its core infrastructure and rule-making power are monopolized by a few “super-nodes” (platform oligarchs, financial giants).

This “Capital Siege” is, algorithmically, an extremely cunning construct.

• For the vast majority (users/digital serfs), it is a polynomial-time system. You can freely operate, consume, and even “innovate” within the platform. Your behavior is predictable, and your returns are (to some extent) foreseeable.
• But for the system’s designers (the oligarchs), they are solving an NP-Hard problem. They are attempting to globally optimize the entire platform ecosystem to maximize their own interests.

This is the eve of the world of Web://Reflect. It is a Delegated Proof-of-Stake society. Most of us have “delegated” our economic and cognitive sovereignty to a few platforms in exchange for convenience and stability. We have become decentralized validators, while they have become centralized block producers.

We experience the sensation of participation (Qualia) but have lost the power to influence the system (Power).

This is the ultimate manifestation of Proof of Invalid Qualia (PoIQ) and the strongest wall of the Capital Siege.

IV. Conclusion: The Next Cycle of the Algorithm #

Human history is a history of algorithms continuously iterating and searching for better solutions. From the brute-force search of tribes to the serial processing of empires, and then to the parallel computation of markets. The emergence of each new paradigm has brought about a massive liberation of productive forces, as well as new, more sophisticated forms of control.

The “Capital Siege” we inhabit today is not the end of history. It is merely a computationally feasible, thermodynamically local optimum under current technological and physical constraints.

Its core contradiction—the increasing concentration of power versus the individual increasingly stripped of causal efficacy—is generating immense prediction errors. The free energy within the system is continuously accumulating.

According to the laws of thermodynamics, when free energy accumulates to a critical point, the system is bound to undergo a phase transition.

A new, more efficient algorithm is brewing on the horizon. It could be a more thorough decentralized network, as promised by DSM, or it could be a more ultimate centralized intelligence, as foreshadowed by ΩNN.

Regardless, the ever-running computer of history has already begun to load new instructions for its next computational cycle.