René Girard's mimetic theory illuminates how localized human communication networks evolved into today's algorithm-driven social media landscape, shifting the mediation of mimetic desire from religious institutions to mass media conglomerates and now to personalized digital ecosystems. Modern algorithmic media platforms amplify mimetic rivalries without the traditional restraining mechanisms, generating novel social divisions that will require innovative solutions to mediate our innate human tendency to violence.

The Mimetic Engine of Desire, Mediation & Violence

René Girard's mimetic theory proposes that human desire is fundamentally imitative rather than autonomous. We desire objects and experiences not for their inherent value but because others—our models—desire them. This mimetic nature forms the bonds of friendship and love that connect us while, simultaneously, containing the seeds of violence if desires converge on objects that cannot be shared. 1

When humans mirror models of desire with others in close proximity, there is a tendency towards competition for the same objects, leading to what Girard called "mimetic rivalry." As these rivalries intensify, they can spread contagiously throughout a community, creating a mimetic crises that threatens social stability. Girard proposes that this triangular relationship between subject, model, and object is the fundamental driver both human culture and human violence.

To prevent self-destruction from escalating rivalry, human societies developed the scapegoat mechanism—identifying and sacrificing victims whose elimination temporarily restores social harmony. The scapegoat mechanism appears with remarkable consistency across differing human cultures, where scapegoating became institutionalized in religious rituals, cultural prohibitions, and social norms.

Sacrificial rituals thus serve as societal safety mechanisms, channeling destructive mimetic competition away from the community while simultaneously strengthening group cohesion through collective participation in sanctioned victimization.

The universally acknowledged human tendencies toward envy and acquisitiveness suggest that Mimetic conflict may actually be an essential regulatory mechanism rather than a defect in human nature.

Human societies across time and space independently discovered the scapegoating mechanism, typically encoded in religious frameworks, to mediate mimetic desires and constrain violence. This suggests that (a) mimesis and violence is built into our biological hardware (b) is a regulatory feature rather not a bug (c) human beings create religion to shelter society from itself in the same way birds build nests.

The standard account of conflict is violence arises when people fight about differences. However, the key insight of mimetic theory is violence arises within society when people fight about the same thing.

The Transmission Rails of Mimesis

Mimesis requires informational transmission rails to communicate desires. Individuals use the same biological perceptual sensory apparatus wired directly into our neurocognitive social hardware, such as the mirror neuron network. At the scale of community, knowledge historically existed primarily through oral traditions, with essential cultural wisdom and understanding passed between generations through narrative and storytelling.

Communication networks function as evolutionary operating platforms that solve large-scale coordination problems in nature. This design recurs throughout biology because individuals cannot perceive all relevant environmental changes through observation alone. 2

A network of interconnected organisms exploring their environment possesses a significant survival advantage over solitary individuals. When 100 organisms function as a coordinated system, they collectively perceive and understand reality beyond any single member's observations, capturing a crucial survival premium through shared intelligence.

Many plant systems demonstrate this type of collective unconscious, as seen in the interconnected root system of individual aspen trees that practically function as a single organism.

As our species harvested an increasing survival premium via communication networks, the newly available energetic surplus was directed towards developing more sophisticated information-sharing technologies, the advancement of which has recently gone parabolic.

The printing press enabled mass reproduction of printed media, though access initially remained limited to institutions and higher social classes.

Steam-powered presses during the Industrial Revolution democratized printed media by making it both affordable and accessible to the broader public.

The telegraph and telephone later created channels to transmit information instantly across vast distances, while radio and television transformed the very forms of content available for audience consumption.

Each breakthrough in communication technology fundamentally reshaped the infrastructure of information transmission, as systems naturally evolve to integrate the most advanced available methods while simultaneously cannibalizing the old technology.

From this communication revolution emerged mass media, a sophisticated ecosystem for collective observation-sharing that enables millions to simultaneously witness events and process developments in real time, transcending previous constraints of time and space. The fundamental value proposition of mass media is simple: quality information creates clearer perception of reality, enhancing decision-making abilities across both individual and collective levels.

With each improvement in bandwidth, latency, network topologies, and propagation speed the velocity of data moving throughout human network began to accelerate. In the era of spoken stories, network information flow was constrained by the physics of sound waves.

After the scientific revolution, information began to flow at the speed of light. 3

Sacred Mediators: Mass Media's Rise as Society's Mimetic Arbiters

As modern society secularized and traditional religious constraints on mimetic desire weakened, new institutions emerged to channel and mediate society-wide human desires. Mass media networks became foremost among these new mediators, simultaneously offering models of desire while regulating social tensions through controlled narratives. The Boomer nostalgia for post-World War II mid-century America is nostalgia for an entire country collectively orienting along the same few TV channels and news outlets.

Girard would recognize mass media institutions as serving a quasi-religious function in managing societal desire. Just as the Catholic Church historically monopolized mediation between individuals and God through systematic power consolidation, mass media companies came to consolidate the flow of information to society into a entire vertical infrastructure, paving the way for their monopoly of economic and mimetic mediation. This was accomplished through three primary mechanisms:

First, mass media companies controlled physical distribution channels—printing presses, broadcast networks, cable infrastructure—creating high barriers to entry that gave them monopolistic control over which models of desire received widespread attention. 4

Second, they established institutional credibility through consistent practices, effectively forming a cartel of "mimetic arbitration"—determining which desires were legitimate and which were taboo. 5

Third, they captured advertising markets through bundling, systematically channeling mimetic desire toward commercial ends while maintaining the appearance of editorial independence.

Today, just six companies control 90% of traditional media outlets.

These monopolistic dynamics allowed media companies to extract extraordinary value via advertising while portraying themselves as a shining city on a hill; trusted public services, despite the glaring conflicts of interest.

Critical theorists who assail these institutions for such conflict of interest, for example Noam Chomsky, generally fail to recognize mass media as not just economic monopolies but also as necessary mediators of mimetic desire—serving as society wide violence dampeners in the same way religion once did. By building an economic monopoly, traditional media came to function as what Girard called an "external mediator"— constructing models of desire for the entire herd to create societal cohesion without triggering destructive rivalries and preventing runaway mimetic contagion.

Today, the monopolistic grip held by traditional mass media has begun to loosen under pressure from highly personalized content delivery algorithms known as social media.

This dramatic shift is vividly illustrated in the revenue streams of traditional media companies like The New York Times, which now derives over half its revenue from digital subscriptions to online games and puzzles rather than from its traditional news content. Even the most established gatekeepers of information must adapt to a media ecosystem where personalized engagement increasingly displaces centralized editorial authority as the primary economic and mimetic mechanism in society. 6

The Mimetic Crisis of the 21st Century: The Fragmentation of Shared Reality by Algorithmic Amplification

Algorithmic social media represents a fundamental paradigm shift: while traditional media competed through curating scarcity, algorithmic systems compete by personalizing abundance. This inversion creates a Faustian bargain—offering unprecedented access to tailored content while fragmenting shared reality and intensifying desires through hyper-targeted models operating below conscious awareness.

Goethe’s “Faust and Mephistopheles”, 1827-1828, oil on canvas

These systems iteratively improve to detect emerging desires and amplify them through engagement-optimized feedback loops. While "engagement" sounds neutral, algorithms systematically orient users toward like-minded communities, forming content clusters that reinforce existing beliefs. The result is divergent information diets where two users of the same platform experience fundamentally different realities.

A social network graph with content clusters based on user engagement

These digital spaces aren't merely echo chambers but mimetic incubators where desires and fears compound without traditional constraints. Algorithms function as what Girard would call "model-mediators," simultaneously suggesting what to desire, identifying scapegoats, and intensifying these impulses through social proof. Consequently, citizens downstream of their media diets lose control over their own beliefs and desires.

The scapegoat mechanism manifests vividly in internet cancel culture: the decentralized collective targeting of individuals who cannot effectively defend against anonymous swarms. The shared moral righteousness of a digital lynch mob reinforces the unity of their group in a shared belief in the scapegoat's guilt. It’s not surprising that a digital lynch mob constructed in binary bits, rather than atoms, does not speak nuance.

This creates a mimetic crisis where ideological echo chambers align and entrench users against different scapegoats and desire amplification outpaces society's ability to channel it productively.

The Sacrifice of Isaac, 1602 by Caravaggio, the canonical scapegoat examples in Western Judeo-Christian civilization include the binding of Isaac by Abraham or the crucifixion of Jesus Christ.

What is perceived as a cultural or political crisis is actually mimetic acceleration now operating without traditional constraints. Political polarization, culture wars, and weekly viral outrage cycles are all symptoms of unregulated mimetic contagion.

Where traditional media monopolized physical distribution, algorithmic systems monopolize attention distribution—creating an economy operating largely below conscious awareness. Users engage in continuous transactions with every scroll and click, paying not in dollars but in time.

The New Media Monopoly

What we're witnessing is not informational democratization, as was the hope of the early internet, but its reconfiguration into a never before witnessed monopolistic architecture. Within the algorithmic ecosystem, new monopolistic nodes are forming—individuals and organizations accumulating disproportionate influence through algorithmic distribution's compounding advantages.

While traditional media competed within geographic boundaries, algorithmic platforms operate globally with virtually zero marginal distribution costs, creating unprecedented winner-take-all dynamics.

In attention markets, differentiation creates monopolistic niches, making the emerging horizontal monopoly of social media algorithms simultaneously more powerful and less visible. Joe Rogan exemplifies this shift—his distinction stems not merely from institutional independence and a very high IQ but from mastering algorithmic distribution mechanics while self portraying as a meathead.

From a Girardian perspective, we need better desire mediators—not better content filters—systems that acknowledge humanity's mimetic nature while channeling it toward non-rivalrous ends. The fundamental question becomes whether society can develop new mechanisms to manage accelerating mimetic desire in the algorithmic age.

In the 1891 book “The Decay of Lying,” Oscar Wilde articulates an anti-mimetic vision of the artist:

“Art doesn’t imitate life, as the saying goes—life imitates art,” according to Wilde. The artist is a creator par excellence. The artist brings new realities into being and changes how we see and experience the world. The artist enters unexplored wilderness and returns with a map, if he returns at all.

Most proposed solutions misidentify the problem by focusing on content moderation or platform regulation. The core issue isn't the content itself but the intensification of mimetic desire without corresponding mechanisms to manage mimetic rivalry. Mimetic aggression is the easiest of all mimesis; a free and loving anti-mimetic response has the power to change hearts and minds. In short, the problem lies not with technology but within the hearts of men.

The task at hand is to beat contagious mimetic rivalry without the traditional pressure release mechanism used by society historically. Girard succinctly lays out the challenge: “Everyone leaves the beaten path only to fall into the same ditch.”

Don’t get lost in the hall of mirrors, for there are many here amongst us who have yet to return.

In the mid-19th century, a French economist named Leon Walras embarked on an ambitious mission: to transform economics from philosophical musings into a rigorous science. Inspired by the mathematical breakthroughs of Isaac Newton and the growing field of physics, Walras sought to create a "science of economic forces, analogous to the science of astronomical forces."

Before Walras, economics was more closely aligned with philosophy than science. Economic discussions were embedded within philosophical, theological, and ethical frameworks, focusing on moral principles, justice, and practical advice for trade and governance.

Living in an era of tremendous scientific progress, Walras witnessed how Newton's discoveries were being expanded upon to develop calculus—a mathematical language that could describe complex natural phenomena through differential equations. Walras became convinced that if calculus could precisely calculate the motion of planets, it could also capture the movements of human agents trading within an economy.

Walras's breakthrough came when he recognized parallels between physical equilibrium systems and economic markets. To understand this connection, imagine a large bowl with a rubber ball. If you release the ball from the rim, it will roll back and forth until settling at the bottom—a state of equilibrium where all forces acting on the ball cancel each other out. Gravity pulls the ball down, the bowl pushes it up, and eventually, it rests where forces cancel out.

Similarly, Walras reasoned that market forces would drive prices toward a natural equilibrium point. Just as physical forces guide the ball to rest, supply and demand would guide markets toward stable prices where transactions between buyers and sellers converge.

Walras's mathematical approach to economics gained momentum as subsequent thinkers expanded on his work.

William Jevons developed the concept of marginal utility, describing how a consumer's satisfaction changes with additional units of consumption. Since every consumer has different personal utility for a given good, market participants would inevitably trade until reaching equilibrium.

Adam Smith introduced the invisible hand, describing how individuals pursuing self-interest unintentionally benefit society as a whole. Through supply, demand, and competition, markets efficiently allocate resources without central planning.

Vilfredo Pareto introduced the concept of Pareto Efficiency, a state where it's impossible to make anyone better off without making someone else worse off. Pareto argued markets would continue trading until all beneficial trades were exhausted—the point of market equilibrium. He proudly declared that "the theory of economic science has thus acquired the rigor of rational mechanics."

By the 20th century, economists synthesized these ideas into neoclassical economic theory. Starting with foundational assumptions about rational consumers and producers optimizing utility among finite resources, they could mathematically model economic forces through the lens of equilibrium, from individual decisions to international trade.

Economic Balls Never Settle in Their Bowls When Markets Refuse to Stay Still

Walras’s adoption of 19th-century physics brought mathematical precision but also a critical limitation: it locked economics into a static, reductionist framework. Physics of that era focused on closed systems trending toward equilibrium, like the ball in the bowl. Walras assumed economies behaved similarly, with rational actors and predictable outcomes.

This ideological lock-in of an entire field - favoring simplicity over realism—persists in traditional economics, despite evidence of its shortcomings.

As economists gained access to better data, computing power, and research methods there was an uneasiness taking hold as they began questioning Walras's equilibrium model and its underlying assumptions.

For example, the economic “law of one price” asserts that identical goods should sell at the same price across markets absent market distorting economic barriers. Yet, post-1999 Eurozone data showed prices diverging—43% above the EU average in Denmark, more than 40% below in Bulgaria and Romania—defying equilibrium predictions.

Cracks emerged in traditional economics consideration of time scales, which traditional economic models barely consider. When they do, it's often simplified into short, intermediate, or long-term horizons.

Reality is messier: it takes time to extract crude oil, refine it into gasoline, transport it to stations, and for consumers to make purchasing decisions.

Yale economist Herbert Scarf calculated that equilibrium time grows exponentially with an economy’s complexity. The more unique items available to trade, the longer it takes for a economic system to settle. The roughly 10^10 unique economic products available today, Scarf calculated that reaching equilibrium after a single shock would take longer than the universe’s age, rendering the entire concept impractical.

The behavioral research of psychologists Daniel Kahneman and Amos Tversky undermines the "rational actor" axiom essential to traditional economic theory. Real people are poor at complex logical decision-making and subject to biases. American polymath and scholar Herbert Simon observed that people often "satisfice"—settling for "good enough" rather than optimal outcomes.

When filling up gas, people don't drive to every station in town for the cheapest price; they choose among convenient options. Time matters and is considerably more challenging to untangle then the idealized physics of billiard balls colliding.

While traditional economics models supply and demand through negative feedback mechanisms (like the ball returning to the bottom of the bowl), real economies experience positive feedback—seen in market bubbles and crashes (negative bubbles). Human behavior creates herd dynamics, and tail events can completely alter a country's economic trajectory with cascading effects.

As T.S. Eliot observed, "We can't help but disturb the universe"—our actions create ripples that amplify through complex systems in ways that simple equilibrium models cannot capture.

Without the axioms of traditional economics, it's as if the bowl's shape continuously changes over time. Economic shocks, a trade war for example, cause the bottom to develop bumps and the walls to distort, preventing the ball from ever settling. The economy may instead move from one temporary equilibrium to another. To import the language of calculus, rather then settle at an idealized global maximum equilibrium, the economy moves through a series of shifting local maximum & minimum.

Economic Metabolism: How Systems Consume Energy to Create Structure

Finally, Walras missed a key physics development: the second law of thermodynamics, which was basically unknown during his time so it’s hard to fault him.

While he grasped energy conservation (the first law), the second law—entropy increases in closed systems or said another way, “nature hates a gradient”—reveals that order decays without external energy.

The economy is not a closed equilibrium system but an open, disequilibrium system—specifically, a complex adaptive system. Closed systems trend toward maximum entropic equilibrium and cannot spontaneously generate order. Yet economic growth throughout human civilization has been a story of fighting entropy, something only possible in an open system.

Since social and economic systems are physical systems made of matter, energy, and information they are subject to physical laws. Energy enters economies to fight entropy and create order, while economies export waste, pollution, and heat. Cut off the energy flow to an economy, and disorder increases, trending toward societal heat death. If there was no water diversion to desert cities like Phoenix or Las Vegas it’s easy to imagine the entropic slide towards structural disorder.

Countries isolated by war, policy or sanctions, like North Korea, move toward a local minimum of starvation and misery as the entire structure of the system decays. The Soviet Union collapsed from economic stagnation and declining productivity in the face of excessive defense spending during the Cold War arms race. Unable to import energy and unable to produce enough economic growth domestically to fight the entropic slide of a closed system, the Soviet Union was eaten from the inside by corruption, which unintentionally accelerated social demands for political freedom and exposed the fragility of the system.

Traditional economics, locked into a 19th-century physics mindset, overlooks how such physical laws are a structural, load bearing feature of real economies.

According to a 2023 UN report, almost half of North Korea’s population is undernourished

QWERTY Markets: Path Dependency and the Stickiness of Suboptimal Systems

A significant limitations of equilibrium-based economics is its failure to account for "lock-in" phenomena, where inferior government policy, technologies or cultural norms persist despite the theoretical availability of better alternatives. Traditional economics would suggest markets naturally move toward optimal solutions, but history shows this isn't always the case.

Lock-in occurs when a technology becomes dominant and persists due to high switching costs, network effects, or ecosystem dependencies.

The QWERTY keyboard layout, designed in the 19th century to prevent typewriter jams, remains dominant today despite more efficient alternatives like Dvorak. ‘

The VHS format prevailed over the superior Betamax due to business decisions around movie libraries and pricing.’

Gasoline-powered vehicles have dominated transportation for over a century, despite their environmental drawbacks, because of massive infrastructure investments (gas stations), manufacturing supply chains, and consumer habits. The science fiction subgenre of steampunk imagines an alternative history where humanity continued to iterate and refine on steam powered technology rather than gas combustion.

The United States continues to use imperial units (feet, pounds, fahrenheit) despite the simplicity and global adoption of the metric system due to cultural inertia.

The Frankenstein monster that is the U.S. healthcare system is highly fragmented, expensive and inefficient compared to universal healthcare systems in other developed countries. Despite this being self evident to all participants, it suffers from lock in due to the entrenchment of special interest groups, political polarization and high switching costs.

As economic complexity scientist Brian Arthur notes, while linear systems add up to the sum of their parts (like sound and light), economic systems are non-linear, with interdependencies and feedback loops that create persistent patterns resistant to change.

Economies can thus become trapped in suboptimal temporary equilibria due to increasing returns, network effects, and path dependency—concepts that don't exist in traditional economic models based on 19th-century physics.

The Heraclitus Economy: Why You Never Step in the Same Market Twice

Just as early physics models failed to account for emergent properties in nature, traditional economics fails to capture the emergent properties of markets and economies.

To understand emergence, consider water molecules: individually, none possess the property of "liquidity," yet put a few zillion together, and liquidity emerges as a property of the collection. Similarly, several billion neurons following biological laws give rise to consciousness—an emergent property not predictable from studying a single neuron.

Economic systems, like other living systems, demonstrate spontaneous self-organization that depends on self-reinforcement—positive feedback that amplifies during favorable conditions. While negative feedback (like diminishing returns) prevents small negative changes from growing out of control, positive feedback (increasing returns) can drive growth, innovation, and change. This rich but complex mixture of positive and negative feedback magnifies differences into patterns.

Human organizations reflect this complexity. Social dynamics expand to fill all space (Parkinson’s Law), often prioritizing internal politics over goals. Resilience, not just efficiency, becomes key—efficiency locks in structure, but resilience also requires adaptability which requires flexibility. High-trust teams, diverse perspectives, and minimal coordination maximize innovation, mirroring economic self-organization. High trust networks with minimal coordination is the entire thesis of the Bitcoin network and cryptographic smart contracts.

The universe forms a hierarchy; at each level of complexity, entirely new properties appear with new laws governing them. Psychology is not merely applied biology, biology is not just applied chemistry, and economics cannot be reduced to simple cause and effect physics equations.

The concept of systems organizing themselves without central direction isn't new to human understanding. Ancient Chinese philosophy captured this phenomenon centuries ago through principles like Yin and Yang and Wu Wei ("non-action" or "effortless action"), which describe how natural order emerges without forced intervention.

“The Tao does nothing, yet nothing is left undone.” - Tao Te Ching

Greek philosopher Heraclitus noted, you can "never step in the same river twice because it is fluid, ever-changing, and alive." Economies, too, are constantly evolving systems rather than static equilibrium states. Said another way, you never step in the same market twice.

Fire Resistant Economics: Resilient Systems in an Age of Turbulence

While the ghost of Newton and Walras endures, complexity economics offers a path forward. Unlike physics’s predictable orbits, economies resemble something closer to slime molds—adaptive, distributed systems where intelligence emerges bottom-up. Strategy shifts from predicting equilibria to fostering conditions for growth: planting diverse “acorns” and nurturing those that sprout.

Slime molds solve complex network problems using non-neural systems

Walras’s physics-inspired economics brought rigor but locked the field into a 19th-century mindset, ill-equipped for the non-linear, emergent nature of real economies.

The invasive, ideological lock in suffered by neoclassical economists is like the Eucalyptus tree that takes advantage of favorable conditions to grows as fast and tall as possible until it towers over its surroundings. However, eucalyptus trees grow fast but are brittle, easily toppled by wind and quick to combust during forest fires

Eucalyptus became an invasive California tree species when they were transplanted to increase the lumber supply.

To move beyond the equilibrium trap, consider the deliberate, slow and strong growth strategy of an oak tree: survive, keep costs low, explore iteratively, and embrace compounding opportunities.

The breadth and deep roots of a live oak tree means it can handle severe winds while its hard wood and thick bark make it fire resistant.

Complexity economics—rooted in open systems, iterative experimentation and adaptive behavior—better reflects reality. The next economic revolution won’t mimic physics but will embrace the messy, vibrant complexity that defines all open, living systems.

At its heart, complexity economics is more like gardening than engineering.

While perturbations in one system (e.g., deforestation or Milankovitch orbital variations) ripple through the others and create cascading effects, the lack of simple, linear, cause and effect dynamics make forecasting near impossible. There’s no local forecast for the weather in your town on this day a year from now.

Fundamentally, this means it is not knowable whether a climate 2 degrees warmer is substantially worse than one 1 degree warmer or considerably better than one 4 degrees warmer. Being in the bucket of the unknowable means no amount of research can move it into the knowable. The only certainty about our future climate is that it will be different.

At a moment in history where people earnestly debate the morality of bringing children into the world due to climate change, I intend to lay out the following case:

1. The climate is not and has never been on the side of humans

2. Policy won’t save us but technology will

3. Cognitive biases have grossly distorted the climate conversation

4. The path forward into an uncertain future is to build and not panic

The Myth of the Benevolent Biosphere

The Spaceship Earth theory imagines our planet as a perfectly engineered vessel speeding through the cosmos at 67,000 miles per hour. On board, generations of passengers live and die, sustained by a self-contained biosphere—clean, recycling, life-giving, powered by a nuclear sun reactor. It’s a nice story, but it’s just that: a story.

The Spaceship Earth myth contains echoes the oldest human narratives—the Garden of Eden of Judaism, the Hesiod’s Greek Golden Age, the Hindu’s Satya Yuga, the Nordic Asgard, the Tibetan Shangri-La, Rousseau’s Noble Savage—visions of harmony, balance, and simplicity. These stories share a fatal flaw: they assume nature is on our side, a virtuous system built top down for our benefit and we are its caretakers.

George Catlin, Bird’s-eye View of the Mandan Village, 1800 Miles Above St. Louis, 1837-1839, oil on canvas

This is anthropocentrism, the most human of errors. The belief that Earth is here for us. That its systems are designed to sustain us. The anthropocentric view of our place in the natural world is intuitive, comforting, and utterly wrong. Nature is not benevolent. It is not even neutral. Rather, nature is actively hostile.

Anthropocentrism, like the geocentrism of the Middle Ages, has historically begot harmful oversights, delayed progress and self inflicted crisis by being off mark in describing the material world.

The actual biosphere is not a nurturing garden; it is a brutal, self-regulating complex system that filters life through the merciless mechanisms of natural selection—competition, extinction, and inequality. In the Great Rift Valley, the “Cradle of Humankind,” proto-humans didn’t thrive because of the biosphere—they survived in spite of it. No clean water. No shelter. Predators, parasites, and plagues everywhere. Most living things died horrible deaths—starved, frozen, baked, eaten, or infected.

And this isn’t some historical anomaly. Natural living systems exist in perpetual crisis, just at the edge of survival. It is the default state of nature.

Populations outgrow food supplies. Resources dwindle. Mass death restores the balance of biological systems via the four levers of war, conquest, famine and pestilence. Forward progress in nature comes not from organic life support systems, but through the ruthless extinction of what does not work. The climate existed long before organic life scratched its way into emergence.

Albercht Dürer, The Apocalypse, the Four Horseman, 1498, Woodcut

The settlers of Manifest Destiny weren’t welcomed and supported by an open frontier—they encountered starvation, disease, hostile landscapes and people. The most common cause of pediatric death on the Oregon Trail was falling between and being crushed by the wagon wheels. Native American history reminds us that one group’s opportunity is another group’s ruin; in the natural world, one group’s unknown horizon is another group’s ancestral home.

Nature doesn’t care about equality, freedom, or fairness. It hasn’t read the American Declaration of Independence nor the The French Declaration of the Rights of Man. In nature, pursuing your own interests freely comes at the expense of perfect equality with others. All mammals have to eat their energy. The tension between freedom and equality isn’t a social construct; it’s a natural law.

The entire mechanism is mostly a practice in subtraction.

The pre-Enlightenment and post-Enlightenment views of humanity share the same anthropocentric arrogance. We either put ourselves at the center of the universe or pretend we have dominion over it. Neither is true. Nature doesn’t serve humanity. It kills indiscriminately, lubricating its innovation engine through perpetual, systemic competitive destruction.

The biosphere is not your friend. The climate is not your life support system. Humans are not and have never been the benevolent caretakers the climate, which existed a long time before it ever had a human name.

In order to propagate the causal structure of the human species, we have always had to build the life support system ourselves.

Humans Have Always Built Our Own Life Support System

A recent report from Citizens Climate International reveals a stark truth: despite trillions of dollars spent globally, only 4.6% of climate action policies have succeeded over the last 20 years. This suggests a misalignment of capital with effective outcomes, inefficiency in policy and capital deployment and need for better leverage points. The levers of policy, even when backed by trillions in capital, are weak and slow-moving tools.

Fortunately policy is only one tool in humanity’s toolkit—and it has never been the primary one that solves our biggest challenges.

The biosphere has no intrinsic priority to support human life, no moral posture, no care for human survival. It is a hostile, indifferent system. We survive not because Earth is designed for us but because we have learned to build technology—to construct artificial life support systems where none exist.

A pile of raw minerals forged in a supernovae strewn about the Earth and a stream of energy from the sun is not enough. An overemphasis of climate policy spending without accountability is not enough. Evolution gave us opposable thumbs, not instruction manuals. Nature provides the ingredients but we must still grasp for a solution through experimentation. It was knowledge—hard-earned, painstakingly discovered—that turned raw minerals into steel, fire into energy, and chaos into civilization.

Consider this: I’m writing this from the mountains of Colorado in December. If I walked outside without clothing or shelter, I would die of exposure in hours. The natural world doesn’t care about my survival. It’s not a nurturing home; it’s a death sentence. We don’t live on Spaceship Earth. We are not passengers. We are the architects, the engineers, and the captains of our own technological life support system.

Mount Sneffels, 14,153’, Colorado

Common Biases That Corrupt the Climate Change Discussion

The morality of a civilization evolves alongside its technology. Hunter-gatherers lived by different rules than agricultural societies. The industrial age shifted those rules again. And today, in the digital era, technology has fundamentally altered what we can achieve, what we consider moral, and how we perceive risk.

But here’s the problem: we don’t see the world as it actually is. We see it through a dramatic attention filter—a filter built into us over millions of years of evolution. Humans are wired to overestimate threats because, for our ancestors, underestimating a threat usually meant death. This bias was survival-enhancing in the wild, but it wreaks havoc on our understanding of modern, complex, probabilistic systems.

In his book Factfulness, Hans Roslings outlines strategies to recognize and control our dramatic filter instincts.

Catastrophe sells. Nuance does not. Headlines highlight outliers and worst-case scenarios, creating a distorted sense of reality. As traditional media has atomized into social media which atomized into individual influencers, the trappings of personalized distortion generating content feeds continues to increase. In this new media landscape, isolated scientific disagreement becomes a false “gap” in consensus when meanwhile, 97%+ of climate scientists agree on human-caused climate change.

Humans tend to extrapolate trends linearly. Pessimists see leading data trends and conclude: apocalypse is inevitable. Optimists cling to magical thinking: the climate will fix itself. Neither is true. The future is neither binary nor linear. It’s a continuum of probabilities shaped by human action—particularly technological innovation.

So why wouldn’t humanity bend the trend line? When has human ingenuity failed to rise to the challenge of existential threats? The Green Revolution solved global hunger. Vaccines eradicated diseases. Renewable energy, particularly solar, is scaling faster than anyone predicted 20 years ago.

Complex dynamic systems exhibit “fat tailed” outcome distributions rather than normal distributions, meaning there is a higher probability of extreme events occurring to the upside and downside. Combine this structural feature with our dramatic attention filter and sociological groupthink, via authority bias and social proof, tends to simultaneously over estimate the risks and also underestimate the benefits.

However, progress is real. To avoid our tendency to underestimate the benefits, let’s look in the rearview mirror and ask: what has humanity gained in exchange for its industrial carbon emissions?

• Global poverty is collapsing and on track to hit zero

• Famines have virtually disappeared outside of war zones

• Child labor and child mortality are at all time lows while child cancer survival is at all time highs

• The marginal cost of energy production is dropping towards zero

• Natural disaster deaths are down 99% in the past 100 years

• War between countries has become unprecedentedly rare (but does still occur) as food, energy and resources have become abundant

• Democracies are expanding while autocracies are declining

It’s essential to realize that progress does not mean everything is immediately better for everyone, everywhere at the same time. Progress is not the same as a miracle.

Only you can answer for yourself if all that relief of human suffering was worth the cost of industrial emissions.

Climate Change Doesn’t Have to Mean the Apocalypse

So here’s the good news: nowhere in the recent Intergovernmental Panel on Climate Change (IPCC) report are climate scientists warning us to prepare for the apocalypse. There will be no dramatic, Hollywood-style climate change event. No singular apocalypse. Climate change is already here.

“If I had to rate odds, I would say the chances of climate change driving us to the point of human extinction are very low, if not zero,” says Adam Schlosser, the Deputy Director of the MIT Joint Program on the Science and Policy of Global Change

The impacts of climate change will vary significantly by region. Low-lying coastal areas and deserts are likely to become less habitable, but we shouldn’t overlook the potential upsides: warming could make currently inhospitable regions—like parts of Canada, Russia, and Scandinavia—more arable and livable. Meanwhile, the melting polar ice is already fueling competition for control of newly accessible Arctic shipping routes.

Technologies will evolve to mitigate the worst effects. The rise of AI is likely to drive a renaissance in materials science, enabling the synthesis of new elements and the advanced chemical doping of existing ones to unlock groundbreaking applications. Solutions will emerge at the speed of progress—incrementally, unevenly, and quietly. And humans will adapt and migrate, just as we always have.

Here’s the irony: if humanity succeeds in blunting climate change, the doomsayers will never admit they were wrong. If disaster strikes, they will claim victory for predicting it. Either way, the path-dependent process of solutions will be erased by hindsight bias and everyone will agree it was inevitable all along.

The real world doesn’t unfold that way. The real world is messy. It’s ambiguous. It evolves in real time through experimentation, iteration, and innovation. Progress doesn’t come from certainty. It comes from human action—building in the face of uncertainty.

People always have and always will crave the certainty of the apocalypse. But to sit in the discomfort of ambiguity is to sit within the actual geometry of the universe.

American historian Will Durant writes: “Every day the sea encroaches somewhere upon the land or the land upon the sea; cities disappear under the water, and sunken cathedrals ring their melancholy bells. Mountains rise and fall in the rhythm of emergence and erosion; rivers swell and flood, or dry up, or change their course; valleys become deserts, and isthmuses become straits. To the geologic eye all the surface of the earth is a fluid form, and man moves upon it as insecurely as Peter walking on the waves to Christ.”

In my view, the real immediate existential threat isn’t carbon emissions—it’s nuclear war. If you wanted to be a single issue voter, that would be it. Climate change isn’t the end of the story but the latest in a long series of crisis that humanity has conquered.

No one is coming to save us. There is no magical policy, no benevolent planet, no divine intervention. There’s only us—humans, doing what we’ve always done: adapt, migrate and solve problems by building solutions.

Zoom out if you really want to get existentially stressed. Eventually the Earth and its climate will be swallowed by the sun, which will explode and wipe everything clean. If humans fail to colonize space extinction is already, right now, a certainty.

But today’s climate crisis? An existential threat?

Climate change is not the end. It’s just the next chapter in humanity’s endless cycle of migration, adaptation and building. It’s really important to internalize that history is just one thing after another. Fortunately, the history of humanity has been on balance additive rather than mostly a practice in subtraction.

Its easy to forget how one piece of new technology can transform the way we build and solve problems. So don’t panic. Instead, build, and the opportunities will multiply. Because if we don’t, the sun is coming for us anyway.

Nuclear war is the only immediate existential threat, so stop scaring your kids about climate change.

The majority of deep intergalactic space, which is the majority of the known universe, lies far from any galaxy. Without a gravitational well of matter to transmute into heat or energy, the typical location in the universe is cold, dark and empty.

In this void, everything is pitch black. Even if you were placed there and stared directly at a distant exploding supernova, the light wouldn’t even appear as a faint glimmer on the horizon. Even if you cranked the power dial on the supernova, there would be no visible matter for the light to interact anyways.

Matter is so scarce in deep space that atomic density falls below one atom per cubic meter. That is a million times sparser than the space between stars and far sparser than the best vacuums humans can create.

With no matter to convert into energy deep space is unimaginably cold: just 2.7 degrees above absolute zero, the coldest possible temperature. This is enough to freeze every known substance, apart from helium. And the sparse atoms that are present, mostly hydrogen and helium, allow no chance for chemistry to spontaneously occur.

And so a typical place in the universe is a cold, inert sea of dead chemistry. Without energy, nothing changes, and nothing happens.

Now compare that to our solar system, where the fire of life seems to have spontaneously kindled. (As of this writing, it’s not at all clear whether or not this is the first time life has this has ever happened.)

The basic equation or structure of organic biological systems is the import of matter (food) to transmute into energy used for self organizing followed by the export of entropy as heat.

The energy flow creates structure and patterns, constantly countering the natural tendency toward disorder and decay, a process governed by the second law of thermodynamics. If Earth did not happen to lie on a river of energy streaming out from the sun, no life on Earth could exist.

Understanding that the basic equation for life is the import of energy and matter and the export of entropy does not answer how structure and order arise in the universe, nor does it explain where this structure and order come from.

With the aim of answering such deep, cosmic questions, Nobel laureate Ilya Prigogine explored self-organizing systems and demonstrated that, under far-from-equilibrium conditions, energy flow through a system can spontaneously generate order. His work became Prigogine’s theorem of non-equilibrium thermodynamics, known as the Prigogine Principle.

Maintaining any structure is challenging because atoms, left to themselves, mix and randomize over time. The second law of thermodynamics ensures that entropy—disorder—inevitably increases. A simple example is rust: iron atoms on the surface of a solid object react with atmspheric oxygen to form iron oxide, an irreversible process often summarized as "rust never sleeps." This is entropy in action, driving all matter toward equilibrium. To put it more intuitively, you can’t unscramble an egg.

Fortunately, Earth sits within a hot river of electromagnetic radiation emanating from the Sun. This energy flow temporarily reverses entropy, allowing systems to self-organize into complex patterns and structures. Over limited periods and in localized spaces, far-from-equilibrium conditions allow complexity to emerge.

For example, when water is heated in a pot on a stove, energy flow destabilizes the system. At low heat, little happens, but at high heat, random molecular motion transitions into organized patterns like convection cells, visible as a hexagonal pattern on the surface of boiling water. The system exports entropy in the form of steaming water vapor. In this way, the water "self-organizes" into a dynamic, structured state.

Due to convection, the temperatures in the top and bottom layers gradually equalize, and the amount of cells changes: they can join together to form larger structures

Such self-organization is ubiquitous in nature and is consistent with open, complex, dynamical systems. Hurricanes, driven by solar energy, are self-organizing systems as are the convection cells in the atmosphere and deep in the molten interior of the Earth. These systems arise from local interactions among simpler components, creating emergent properties without external direction.

Living cells exemplify Prigogine's work on self-organizing systems, whereby they use energy from the ingestion of food to sustain complex organization. The modeling of biological systems however is vastly more complex and less mechanistic then convection cells which can be modeled by the comparatively easy mathematics of physics and chemistry. For example, we cannot write an equation for an amoeba, let alone an oak tree. Yet, at the molecular level, biology arises from the same fundamental carbon based chemistry and thus shares common levers that give rise to complex life.

All biological life shares astonishing molecular similarities. DNA, the blueprint of life, is remarkably conserved across species. Humans share 60% of their DNA with bananas, reflecting a distant common ancestor before natural selection diverged into the genetic evolutionary pathways of fruit and primates.

DNA is the universal mechanism for transmitting genetic information, and every cell in your body contains the entire blueprint. But while the genetic blueprint of DNA is a little different all living organisms on Earth, the organism is constructed using the same molecular code breaking machinery of ribosomes, tRNA and various enzymes.

DNA imaged with electron microscopy

Different organisms exist because there are a small fraction of genes arrayed along the DNA molecule that function as tiny switches called your epigenome. The epigenome, the system stack above DNA, regulates which genes are switched on or off in different cell types. Toggling a local set of genes on or off via chemical reactions propagates a cascade of additional downstream genetic toggling until the cellular DNA eventually settles down into a new and stable genetic blueprint pattern. This new, stable blueprint is customized to construct the molecules needed for a specific type of cell.

This is the difference between a chimpanzee and a human or a primate and a banana - series of local chemical interactions along the DNA molecule that self propagate and self organize into all the variety of living organisms on Earth. This is how a fertilized egg, with two strands of DNA each from a set of reproducing organisms, starts to divide and differentiate from the same cell into pancreas cells that produce insulin or the photoreceptor cells in your eyes.

In a way, the on or off toggling of genetic switches in the epigenome is to a molecular scale computer that orchestrates cellular development and interaction with the environment. This cascading process propagates over time, creating an intricate web of cause and effect that builds complex organisms.

Natural selection amplifies advantageous traits, eliminates neutral or harmful traits, and creates the rich diversity of life. However this interplay of chance and selection makes life inherently unpredictable. Small genetic changes to the start conditions may have no effect—or transform an organism profoundly. The evolutionary "experiment" unfolds only as life is lived. Said another way, you live in the sample not the sample size.

The epigenetic molecular mechanism indicate biology exists as a world of power laws and tail events rather than the simple normal distribution of a bell curve. Biological systems are path dependent, meaning past events impact future events and the history of the system matters. Chance events can transform the final form and you can’t ever predict the final structure from the initial conditions.

Path dependency diagram of organizational structures

This is why biology is a complex adaptive system. It is why we cannot write a mathematical equation for a complex living object. This spontaneity is what makes biological life feel alive, with all its comedy, tragedy and absurdity.

Living systems import matter and energy and export entropy to create a causal structure that is self organizing and self propagating across time. From the same biological molecular workshop comes a handful of pieces and an infinity of possible patterns.

This sprawling set of self consistent patterns evolves and changes in response to the outside world. Like a kaleidoscope, living systems lock into one pattern and hold it until natural selection causes a slow turn of the barrel, causing it to suddenly cascade into a new configuration.

All living systems, you, me and all of us, are holding onto this causal structure for dear life in an endless struggle against a universe trending towards the equilibrium of deep space.

A place that is cold, dark and empty, where nothing changes and nothing happens.

So reflect for a moment on how lucky you are to have ever been alive and how strange it is to be anything at all.

"Geographical Portfolio,” Levi Walter Yaggy, 1887

Humans have been co-evolving with technology for a very, very long time, even on evolutionary timescales. The building and application of technology is arguable the defining feature of our species.

Our oldest technologies involved the recombination of fire, stone and metals which humans dug out of dirt bare handed. Much like the self-assembling and self-replicating complex carbon molecules in the prebiotic soup, early human technologies were replicated, encoded, and transmitted across early human networks, such as the Silk Road.

It’s not enough to discover scientific laws. Science is only theory until it is applied as technology.

The Birth of Technology (Hands + Stone)

Ancient human scavengers, indistinguishable from other animals, once dug through the dirt with their bare hands in search of food.

For a long time, they overlooked the rocks scattered on the ground, deeming them useless. After all, any creature that tried to consume such inorganic material would quickly suffer fatal consequences, like a bowel obstruction.

Early humans risked serious injury when striking objects too forcefully, as broken hand bones could drastically reduce their ability to grasp and manipulate objects—a potentially life-threatening injury.

But around 2.6 million years ago, humans discovered that they could reduce the risk of injury by using rocks to deliver stronger impacts. This realization allowed them to wield stones as tools, throwing and sharpening them with increasing accuracy and precision.

Technological leverage had been just laying on the ground waiting to be discovered.

And so, without ceremony, stone tools emerged.

The oldest known stone tools, Oldowan stone tools, discovered in modern day Ethiopia 2.6 million years ago

The discovery of stone tools introduced a revolutionary force-multiplying technology. Compared to the fragile human hand alone, the combination of an ape grip and the hardness of stone gave early humans a dramatic increase in striking power.

Since metallurgy had not yet been invented, tools made from pure elements (a single type of atom) were rare. Humans instead relied on rocks constructed from highly compressed elements called minerals.

The earliest stone tools were made from minerals harder than bone, capable of holding a sharp edge, and readily available within the top layer of the Earth’s crust. This was quartz, quartzite, basalt, or obsidian, and later flint. Obsidian, a naturally occurring volcanic glass that’s made up of silicon, oxygen, aluminum, sodium and potassium that could be picked up in chunks right off the ground, was crafted and sharped into the most advanced tools and weapons of the Paleolithic era.

By combining the cooperative power of early social networks with the force-multiplying effect of stone tools, humans began to outcompete every other animal on the planet. It was as if, overnight, humans had suddenly evolved lethal hands of stone.

With natural selection unable to keep pace, animals had no time to adjust to this rapid shift in the ecosystem’s power dynamics. Early stone technology made humans so powerful they hunted the colossal wooly mammoths to extinction. Soon humans dominated any ecosystem they entered, surpassing their stronger, faster, but less technologically advanced rivals.

Rouffignac Cave, France, Upper Paleolithic era, 13,000 BC

Fire and the Transmutation of Metal (Hands + Metal + Fire)

Fire has been integral to human existence for nearly a million years. Early humans captured and propagated fire from naturally occurring land wildfires.

The strategy of animal carnivores is to outsource food scavenging and food metabolism to smaller prey animals. By pre-digesting scavenged food with fire instead, humans became the first species to outsource part of their metabolic process to technology. The energy saved from digestion was redirected to fuel the brain, which today accounts for 20% of our total metabolic energy consumption. Unlocking these scarce calories removed evolutionary constraints, making our brains larger and making us smarter.

Humans soon discovered fire could soften not just food but rock, metal and other materials.

It hardened clay into the pottery necessary for early agricultural societies to cook and store food.

Before fire, humans shaped stone tools by striking one rock against another. With fire, they discovered that heated minerals became more malleable, allowing humans to shape them into better technology.

Outsourcing to fire the energy and labor needed to manually shape minerals into better technological devices marked the beginning of the Metal Ages.

In the Copper Age (6200 BC), humans smelted copper ore to craft stronger tools and weapons.

In the Bronze Age (3800 BC), copper was smelted and alloyed with tin to produce bronze, which was much stronger than copper alone.

Although older civilizations had used meteoric iron for thousands of years, the Iron Age (1380 BC) saw the mass production of iron tools and weapons scaled up and refined. Carbon from charcoal was soon alloyed with iron to create steel — harder and lighter than bronze.

Mass produced nine inch iron Roman nails affixed Jesus of Nazareth to the cross. Numerous iron nails are venerated as those of Jesus’s crucifixion at museums throughout the world today.

Fire revolutionized not just the metabolism of food and the shaping of minerals but the very way humans stored economic value. Fire facilitated the extraction of precious metals like lead, silver, and gold from raw metal ore. Better extraction techniques lead to the mass production of metal currencies, a better store of value technology.

Metal currency revolutionized trade, as metal coins were more practical to transport than sea shells, livestock, or slaves. Traveling with a pouch of silver along the Silk Road was far easier than traveling with a herd of oxen. For a modern day analogy, consider that moving wealth across borders is far easier using a memorized Bitcoin seed phrase than carrying a suitcase full of cash or navigating multi national bank account transactions.

Geographia, Greek Historian Ptolemy, 150 AD. This atlas depicts the Silk Road, which economically connected “Sinae” (China) to the West

Fire was used by ancient humans to explore the combinatorial space of how rocks and minerals could be transformed into tools and weapons. The experimental recombination of environmental objects using fire during the three Metal Ages laid the foundation for modern materials science with the rise of Alchemy.

Alchemy, though often dismissed as pseudoscience, was foundational to the development of modern chemistry. In the search for the philosophers stone, a mythical substance said to grant immortality and transmute base metals into gold, early alchemists developed many of the tools and methods still used in laboratory science today, such as distillation, crystallization, sublimation and filtration. By experimenting with various chemical mixtures, alchemists discovered new elements such as mercury, sulfur, and arsenic.

In the 9th century, Chinese alchemists accidentally discovered the explosive power of gunpowder by applying fire to a novel mixture of sulfur, charcoal, and potassium nitrate. Gunpowder sparked a revolution in weaponry and demolition, and laid the groundwork for the chemical rocket fuel that eventually took humans to the moon one thousand years later.

The alchemical cipher for the Philosophers Stone, the Elixir of Eternal Life

Technology Is A Defining Trait of Our Species

The innovation arc of early human technologies—using stone, fire, and metal—suggests that technological progress occurs when mature, existing components are recombined to create new technologies. These innovations reduce scarcity by improving efficiency and unlocking hidden value.

The technological flywheel gains momentum as new technologies are combined with existing ones to create more innovation. Each additional technological part expands the combinatorial space of future innovation, paving the way for the next breakthrough.

Technology lies upstream of human culture and even morality. A clear example of a technology-driven moral shift is happening in the 2020s. As the population-level effects of weight loss medications like Ozempic begin to emerge in the data, notice how the moral narrative surrounding obesity shifts. What was once seen as a failure of self-discipline or moral character is increasingly reframed as a medicalized issue, akin to an addiction to food.

Technology also lies upstream of politics and history. Only what is technologically feasible can be promised on the campaign trail or implemented in the arena of geopolitics and war.

Humans are inseparable from the technologies we create. Our unique ability to creatively recombine resources into innovative technologies that unlock hidden value is arguably one of the defining traits of our species.

Technology is what makes us human.

Promethesus Bound, Peter Paul Rubens, 1611 AD

The Greek Titan Prometheus was eternally chained to a rock where an eagle devoured his liver every day, only for it to regenerate over night, as punishment for stealing fire from the Gods and gifting it to humanity.

Let's explore how these powers can create either virtuous cycles (flywheels) or vicious cycles (doom loops).

Soft Power: The Carrot Approach

Soft power, on the other hand, relies on attraction and persuasion. It's about building relationships, fostering cooperation, and shaping perceptions.

Soft Power Flywheel:

• Building Trust: Positive actions and diplomacy can build trust and goodwill.

• Increased Influence: This leads to increased influence and cooperation.

• Strengthened Relationships: Stronger relationships further enhance soft power.

Hard Power: The Stick Approach

Hard power relies on coercion and force to achieve desired outcomes. While it can be effective in the short term, it often leads to unintended consequences and long-term instability.

Hard Power Doom Loop:

• Erosion of Trust: Excessive use of force or coercion can erode trust and respect.

• Resistance and Backlash: This leads to resistance, protests, or even violent conflict.

• Escalation of Force: To maintain control, the power-holder may resort to even harsher measures.

Real-World Examples

Let's explore how these dynamics play out in various contexts:

Governmental Relations:

• Hard Power Doom Loop: Authoritarian regimes often rely on surveillance and repression, leading to civil unrest and further crackdowns.

• Soft Power Flywheel: Democratic governments prioritize transparency, accountability, and civic engagement, fostering trust and stability.

International Relations:

• Hard Power Doom Loop: Countries that resort to sanctions or military intervention may face diplomatic isolation and further conflict.

• Soft Power Flywheel: Nations that promote diplomacy, aid, and cultural exchange can build global influence and partnerships.

Organizational Culture:

• Hard Power Doom Loop: Micromanagement and strict rules can stifle creativity, reduce morale, and harm productivity.

• Soft Power Flywheel: Empowering employees, fostering collaboration, and recognizing achievements can boost morale, innovation, and overall performance.

In mathematics, combinatorial growth represents exponential growth layered on top of exponential growth.

In systems theory, it is complexity building upon complexity.

I aim to show how combinatorics is a key driver of global growth and innovation, as each new idea or technology disproportionately expands the combinatorial possibility space leading to a self reinforcing cycle of growth and innovation.

Comparing Different Types of Growth

As a simple illustration, consider the yellow circle one element (N).

A single element yields one possible combination.

Adding a second elements yields two combinations.

With three elements, there are six combinations.

Four elements results in twenty four combinations.

Five elements yields one hundred and twenty combinations.

The following graph illustrates how any system that follows combinatorics has a comparatively explosive growth acceleration as you add more elements. By only five elements, the linear growth function looks like a flat linen compared to the combinatorial growth function, which is already going parabolic.

Linear growth occurs at a constant rate, increasing by a fixed amount with each step or time unit. For example, if a business adds 10 new customers every month, after one month there are 10 new customers, after two months 20, and so forth. Graphically, this appears as a straight line.

Exponential growth increases at an accelerating rate, where the growth rate is proportional to the current value. For instance, if each customer tells two more customers, who in turn tell two more, the number doubles consistently. Graphically, exponential growth starts slowly but rapidly increases, resembling a J-shaped curve.

Combinatorial growth involves multiplying the number of combinations as new elements are added, resulting in a rapid escalation of possibilities. Due to the sheer multitude of combinations it propagates faster than standard exponential or linear functions.

Combinatorial growth is evident in businesses like social media platforms that leverage network effects. The value of such platforms grows not just by adding users linearly or exponentially, but combinatorially through the connections between users. As the number of users increases, the network’s value increases disproportionately from the potential user interactions.

The Paradox of Global Wealth

Combinatorial growth is the answer to the paradox of global wealth, which asks, how does global wealth continue to grow despite an increasing population? As new ideas and technologies emerge, they combine with existing ones, expanding the combinatorial possibilities disproportionately.

For example, Uber combined the existing technologies of mobile internet connectivity, GPS tracking and digital payment processing with the almost 300 million privately owned vehicles in the United States to create an entirely new product, unlocking $150 billion in value and growing the global economic pie.

As a more concrete illustration, if we frame the combinatorial growth space of innovation as physical land, it’s as if each new land discovery brings forth even more new land rising from the oceans.

So despite the omnipresent doomsayers, global wealth may actually be infinite.

Combinatorial Growth Both Expands and Compresses Time

Due to the limitations of physics, all available elements in a system cannot be experimentally combined simultaneously. Said another way, it takes time to rearrange physical objects or elements into different configurations. Time and distance and inextricably linked.

In classical mechanics, the relationship between distance and time is related through motion.

Distance = Speed x Time

In special relativity, space and time are interconnected in a four dimensional continuum known as spacetime. As objects approach the speed of light, time dilation and length contraction occurs, linking time and distance in a way that doesn’t exist in classical mechanics.

In general relativity, time and distance are influenced by gravitational fields. For near massive objects, time slows down (gravitational time dilation), and distances start to warp. For example, in cosmology light years (distance) are often used to describe astronomical scales of time since the speed of light is constant at that scale.

Since sifting through a vast recombinatorial space also takes a proportionately immense amount of time, it can stretch seconds into billions of years.

Consider the origins of complex life and the origins of human civilization.

Combinatorics was the Earth’s Early Prebiotic Innovation Engine, which took 4.5 billion years to recombine carbon with other simple molecules, evolving a primordial soup into the vast diversity of modern organic life.

Once complex life had evolved, the Combinatorial Innovation Engine of Early Civilization took only 2.6 million years for humans to dig up minerals and elements from the ground, apply fire and iterate from stone tools into a digital, spacefaring civilization.

Notice the time compression. Once an evolutionary search function hits on valuable recombination of elements, all the time it took finding the recombination gets rolled up into the new element, making it easier to replicate. Growth begets growth.

This is the Matthew effect of accumulated advantage, a natural phenomena so important and widespread it was even written down in the Bible.

“For to every one who has will more be given, and he will have abundance; but from him who has not, even what he has will be taken away.” Matthew 25:29, RSV.

“The Calling of Saint Matthew” by Caravaggio, 1599-1600

“Zero to One” by Peter Thiel is about creating groundbreaking businesses that move from “zero to one” by building something entirely new, rather than incrementally improving on what already exists. The book explores how to find unique opportunities, cultivate innovative thinking and create monopolies through technological breakthroughs, rather than competing in crowded markets.

Said another way, once a novel company or object is assembled, the time and work that was first required for construction gets compressed, making it easier to replicate. It’s harder to go from Zero to One then to One + N because of this compression phenomena.

Take modern humans for example. The spatial volume of the average human is about 62,000 cubic centimeters. However, when considering the required 4.5 billion years of time packed into the creation of those 62,000 cubic centimeters, unrolled we are enormous spatiotemporal beings. It’s no surprise that in terms of network power and depth of function, the human is considered the most complex thing in the known universe.

Remember that you are more ancient, towering and powerful than you think. After all, you have been traveling for 4.5 billion years in a wake of reassembled ancestral parts to be reading this text right now.

However, they soon realized that some systems defy this approach, as understanding local cause-and-effect interactions alone was insufficient to fully explain system-wide behavior.

Small changes in initial conditions could lead to vastly different outcomes, revealing that the relationships were not linear but super-linear.

Moreover, instead of independent variables driving dependent ones, it became apparent that some systems were interconnected with only dependent variables.

Enter chaos theory and complex adaptive systems.

A complex adaptive system (CAS) is a dynamic network of diverse, autonomous agents that interact, self-organize, and adapt their behavior in response to a constantly changing environment. Over time, the repeated interactions among agents lead to system-wide behaviors that cannot be fully understood by examining individual interactions alone. Due to the dynamic and nonlinear nature of these interactions, the system produces emergent outcomes that are greater than the sum of its parts.

The agents within a CAS lack awareness of the broader system they are part of, making it impossible to fully explain emergent phenomena by studying local interactions alone. The complex, super-linear relationships between agents, initial conditions, outputs, and feedback loops obscure cause and effect, rendering CAS effectively a "black box."

Biology offers many great examples of complex adaptivity because nature uses this organizational structure to solve highly complex coordination problems.

Consider the emergent behavior of a beehive.

Without any single bee in control, a beehive effectively adapts to the changing needs of the brood, fluctuating food availability, and internal temperature. The hive coordinates foraging patterns, swarming behavior, wing fanning for air circulation, and adjusts worker and drone reproduction rates to respond to a constantly shifting environment.

Or consider the beautifully synchronized and emergent murmuration behavior of a flock of birds.

Ant colonies solve complex coordination problems without any leadership, relying only on simple rules and chemical signals.

Complex adaptive systems are all around us. They are the structure of the economy and financial markets, of societies, of families, of the climate, of supply chains, of the immune system and even the neuroplastic network of the human brain. They all share the same features of heterogenous agents who interact leading to emergent system wide phenomena.

Complex adaptivity is the reason why legendary investor George Soros thought the idea of market equilibrium was bullshit. In his book the “Alchemy of Finance,” he instead calls the phenomenon “reflexivity. “

Reflexivity occurs because the views and expectations of market participants influence market events, and in turn, these events shape participants' perceptions. The participants are thinking agents with imperfect information who interpret facts through their personal biases, interacting and self-organizing often with flawed models of the world.

This led Soros to reject the traditional economic model of market equilibrium.

Instead of having independent and dependent variables, markets are entirely composed of dependent variables, preventing markets from ever settling into an equilibrium.

Soros argues emergent phenomena like bubbles and crashes arise because actions like bidding up or selling down a stock continually alter perceptions of that stock’s value. As a result, markets are always on a pendulum swing away from equilibrium rather then towards it. If market equilibrium exists it is a pushing force rather than pulling force.

The lens of complex adaptivity doesn’t fit neatly into cause-and-effect mathematical models, but it is often the most accurate perspective to use. Soros believed that using a faulty model is more dangerous than using no model at all.

A related concept is the observer effect, which is prevalent across various fields. In social sciences, it’s known that people change their behavior when they know they are being observed. This effect is also embedded in the fundamental architecture of the universe, where a photon changes its behavior from a wave to a particle when observed.

The Egyptians provided one of the earliest symbolic representations of complex adaptive systems with the ancient symbol of Ouroboros, a snake endlessly eating its own tail.

Hieroglyphs of Ouroboros near the sarcophagus of the Egyptian pharaoh Tutankhamun, 1300s BC.

Once you understand the structure of complex adaptivity, you quickly realize that we are deeply embedded within and are born into these systems. Like nested Russian dolls, these systems often exist within one another.

“Systems gardener” Alex Komoroske says “everything in life is a game within a game within a game, endlessly layered.”

To play well, the first step is recognizing you’re embedded inside a game.

The second step is discerning the rules and structure. In my experience, people confuse rules with the pressure of social structures. There are less rules than you think.

After awakening and discernment, the last and most freeing step is discovering that what feels like a death after a botched play in one game merely transitions you into another game because life is iterative.

Instead of turtles, it's complex adaptivity all the way down.

Drawing from an ancient Hindu ceramic depicting the tortoise Akupara supporting the elephants that hold the Earth, all surrounded by the self-devouring serpent, Asootee.

In fact, it’s necessary to disentangle luck and skill to get any lessons from history at all.

For example, was the Allied strategy of storming the beaches of Normandy to get a foothold in Nazi occupied Europe good strategy or dumb luck? If luck was the dominant influence, the lessons are limited.

This is the limitation of the case study teaching model omnipresent in medical, legal and business education. To glean any actionable lessons from case studies you must know whether the company was lucky or good, which is not self evident. The behavior of patients, markets and clients is rarely textbook.

To answer this conundrum is no mere academic exercise. It is a lodestone for navigating the treacherous waters of decision-making. To know whether luck or skill holds sway is to possess a map of sorts, one that guides not just the distribution of capital, but the very approach to life's inevitable challenges from which no one is spared.

This knowledge seeps into every crevice of strategy, coloring risk assessments with the hues of probability and tempering expectations with the cool touch of reality. It whispers in the ear of the ethicist, suggesting where true merit may lie. And in the crucible of choice, it stands as a silent partner, its presence felt in every decision, large or small.

In a world where the flip of a coin can sometimes carry as much weight as years of study, understanding the balance of fortune and faculty becomes not just an advantage, but a necessity

The Luck Skill Continuum

In most games the influence of luck and skill falls somewhere along a continuum, presenting the challenge of disentanglement.

The Luck Skill Continuum

Games of skill are the domain of the craftsman, virtuoso and expertise. Skill is hewn from countless hours of practice and iteration in the pursuit of mastery. In this domain, players are in full control because actions produce predictable results.

Games of luck are domains inhabited by a capricious spirit that defies prediction. It is the wind that shifts without warning or the deadly rockfall from a rapidly warming mountainside. It is an external force as neutral as it is powerful. It’s the pebble that diverts the course of empires. It’s a chain of historical events that will never be replicated even under identical starting conditions.

Luck is what’s left over after subtracting skill from an outcome.

Luck = Outcome - Skill

In “The Success Equation” Michael Mauboussin illustrates the luck skill continuum using a sports frame. Consider the following chart.

At one end is the realm of pure chance—a cacophony of clicking slot machines, the whir of roulette wheels, and the flutter of lottery tickets. Players in these games are mere spectators to their own fortunes, their skills as relevant as a snowflake in a blizzard.

Opposite this chaos stands the domain of pure skill, where chess pieces move with the precision of military campaigns and tennis balls arc through the air like guided missiles. In the theatre of expertise, an amateur's lucky move is as futile as bringing a knife to a gunfight—the grandmaster's strategy an impenetrable fortress against the siege of chance.

Between games of pure chance and pure skill lay more nuanced games. Consider the following chart from the Success Equation.

There is a 40% spread between the influence of luck in basketball compared to hockey. This suggests resource allocation to skill development in basketball has a higher payoff than in hockey.

But Mauboussin’s research paints a curious picture here, one that defies intuition. He calls this phenomenon the paradox of skill. ^.

“"Okay, you have gotten the memo on improving skill: 10,000 hours, hard work, deliberate practice, grit, and attentive teacher. We've all heard it. You also recognize that in many of life's activities, the results you achieve combine skill and luck. No debate there. Now, what if I told you that in many cases improving skill leads to results that rely more on luck? That's right. Greater skill doesn't decrease the dependence on luck, it increases it. If you have an interest in sports, business, or investing, this lesson is for you.”

The principle is that, as players abilities converge towards perfection the influence of skill diminishes while the role of luck increases.

It’s analogous to harmonic cancellation, where two sine waves smooth into a third, lower amplitude wave. If skills match with absolute precision, the wave flattens entirely.

Said another way, in games with perfectly matched skill the outcome becomes entirely driven by luck.

Disentangling Luck and Skill Based Games Using Indicators

For games at the extremes of the luck skill continuum, the dominant influence is obvious. For example, it’s mostly intuitive that casino games like roulette are pure luck while a board game like chess is pure skill.

But step outside the casino or away from the game board and it’s apparent that (a) most games are influenced by both factors and (b) it’s not at all obvious how to disentangle their individual influence.

Since luck and skill exist on a continuum it means they are continuous variables and are practically uncountable with any precision. The best we can do is use tools to approximate the coordinates.

Use the following indicators to estimate in what direction on the continuum a game leans. The more indicators you can tick under a column the more likely it is a given game is more dominantly influenced one or another variable

For example, if you cannot intentionally lose a game it is likely you are playing a luck dominant game.

The Treacherous Importance of Sample Size

Picture a vast, snow-covered mountain range. At its base, a group of backcountry skiers huddle around a tiny pit dug into the snow, peering intently at the layers revealed in order to forecast their risk of death or disability by avalanche.

This scene, seemingly innocuous, encapsulates a profound dilemma faced by decision-makers across all fields: the treacherous interplay of sample size, skill, and luck.

The question is, where does the game of avalanche forecasting fall on the luck skill continuum? In my view, it ticks most of the luck based indicators.

So if avalanche forecasting is a primarily luck based game and you have only a small snow pit sampling of the larger mountain slope, one cannot reliably describe the avalanche risk profile from this information alone.

In the realm of skill-dominant pursuits, small samples can be nuggets of gold, each observation a concentrated lesson. But as we venture into territories where Lady Luck holds greater sway, these limited glimpses become as unreliable as mirages in the desert. It's here, in this nebulous zone, that our snow pit reveals its limitations. The skiers, armed with their tiny window into the mountain's mood, are unwitting players in a game where the rules of chance overshadow their expertise.

The avalanche pit predicament is the same as that faced by the use of case studies in academics, which are a small sampling of a much larger spatiotemporal structure. Unless the approximate location of that structure on the continuum can be identified you must be cautious applying any lessons learned. Otherwise, it’s a potentially false signal of trend continuation when the outcome may in fact fatally mean revert.

To extend the mountain the analogy further, enter the gambler’s fallacy. The gamblers fallacy is a siren song that lures even the most rational minds onto the rocks of misunderstanding.

Imagine a coin flipper, convinced that after a string of heads, tails must surely be due. This belief, as persistent as it is misguided, ignores the fundamental independence of each flip. It's the same flawed logic that might lead our skiers to declare a slope safe based on previous descending ski tracks - a sometimes fatal misreading.

The summary principle is that small sample size is useful in skill dominant games but is misleading and dangerous in luck dominant games.

The interplay between luck and skill shapes outcomes across a vast spectrum of human endeavors, from games of chance to professional sports and beyond. Understanding where an activity falls on this continuum is crucial for strategy development, risk assessment, and decision-making. As Michael Mauboussin's research illustrates, even in highly skilled domains like professional sports, luck can play a surprisingly significant role. The paradox of skill further complicates this picture, showing how increasing expertise can paradoxically amplify luck's influence. To navigate this complex landscape, we must learn to recognize indicators of luck and skill, understand the pitfalls of small sample sizes, and guard against fallacies like the gambler's fallacy. Ultimately, disentangling luck from skill is not just an academic exercise—it's a vital tool for setting realistic expectations, allocating resources effectively, and making informed decisions in an uncertain world. By embracing this nuanced understanding, we can approach challenges with clearer insight, whether we're analyzing business case studies, evaluating avalanche risks, or simply trying to improve our performance in any domain.

A common error in human judgment is using the quality of an outcome to judge the quality of a decision.

Failing to disentangle outcomes from decisions leads to retrospective distortions and hindsight bias. Hindsight bias changes our perception of a decision, making us see a singular outcome as an inevitable chain of events. This is the ubiquitous Monday morning quarterback syndrome.

Without disentangling outcome from the decision, it’s extremely difficult to disentangle luck from skill or a faulty decision making method.

For example, how do you know a good outcome was due to a brilliant strategic insight or blind luck? How do you know if a bad outcome was actually a tough break versus a long shot in the dark.

Without disentanglement, the whole process bleeds into a narrative you tell yourself after the fact. When judging personal decisions, hindsight bias tends to attribute good outcomes to skill and bad outcomes to luck (and vice versa when judging others).

Both retrospectively and prospectively we are wired to think discretely in a probabilistic world.

The vast majority of people are never taught how to make decisions. Without a framework the tendency is to fall prey to biases and blindspots. So let’s consider a decision making framework using expected payoffs. This framework is similar to the decision making process in a game like poker.

A Simple Decision-Making Game Plan

1. Determine all possible outcomes for decision.

2. Identify the potential payoffs for each outcome.

3. Estimate the probability of each outcome occurring. Use historical base rates if applicable and available.

4. Calculate the expected payoff for each outcome by multiplying the payoff value by the outcome probability.

5. Compare the expected payoffs between all potential outcomes

   1. It’s important to know whether you are playing a finite or infinite game.

6. Repeat the process for each possible decision and compare the expected payoffs between all decisions and outcomes

See this page for a sample scenario with numbers.

Some Additional Decision Making Frameworks & Tools

Keep a decision journal for small and large decisions using base rates, perspective taking, counterfactual thinking and pre and post mortem analysis.

Write down the information you currently have, the risks you foresee and your decision making thought process because once the outcome is known your brain will retroactively distort what you actually knew and felt before the outcome occurred. Write it all down so you have evidence of your reasoning. Similar to cognitive behavioral therapy, this alone can expose distortions once it’s out of your head and on paper.

If available, figure out the base rate for the decision you’re trying to make. For example, if you’re worried about a specific medical complication following routine surgery, find the complication incidence to inform your expected value calculations.

Use perspective taking to get outside your personal worldview and biases. Consider in your imagination what a different decision maker, stake holder or someone you admire for their judgment might decide in the same situation. If seeking guidance from a friend or mentor, don’t first disclose your thought process to avoid corrupting their opinion.

In medicine, a post mortem is an autopsy of a body to determine the cause of death retrospectively. Organizational strategists similarly use this practice to dissect out why a company decision went off the rails. Write postmortems for your decisions regardless of the outcome. Use counterfactual thinking. This is similar to writing an “alternative history.” Consider hypothetical scenarios where an alternative outcomes occurred and find insights by viewing your decision process through a different outcome lens. The human tendency to rumination, regret or self pity when reflecting on the past is an unhealthy version counterfactual thinking where one digs a psychological hole that you will just have to dig yourself out of later.

Instead of a postmortem, you can also generate a pre mortem where you write up a hypothetical future postmortem forecasting why a decision went awry. Research by J. Russo at Cornell found prospective hindsight - which you imagine an outcome has already occurred - increases accurate forecasting of decision failure points by 30%.

Jeff Bezos uses the frame of one way vs two way doors:

• Two way door decisions are reversible and should be made quickly. If it’s the wrong decision you can always go back.

• One way door decisions are impossible to reverse once made or would be extremely complicated and costly to reverse, so are extremely consequential. These decisions should be made deliberately and carefully.

• Organizations and people make a frequent error by treating two way door decisions like one way door decisions.

• Each additional unit of information you seek out becomes less valuable and more costly to obtain, so consider setting a target of having 70% of the information you need to make a decision for a two way door. It’s rare to have perfect information.

• The one versus two way door frame relates to the finite versus iterative game mental model.

• Ask yourself if your decisions exhibits path dependency i.e. each decision alters future decisions,

Per the “Merton share,” named after the Nobel-winning economist Robert Merton, “the expected profit required from a gamble increases not with the size of the risk, but rather with the size of the risk squared.” Said another way, risk moves up exponentially not linearly in relation to your expected payoff.

Be aware of the paradox of choice, where having too many options can lead to negative outcomes, such as anxiety, decision paralysis, and dissatisfaction through higher expectations. An interesting example of this is how lifetime sexual partners is inversely correlated with martial happiness. Spouses who are both each other’s first and only sexual partner tend to have happier marriages. Defend against this by simplifying options (make the one choice that eliminates a thousand choices) and be a "satisficer" versus a "maximizer."

If you are really struggling to choose between an array of decisions, consider the mathematical tool of inversion, often required to solve algebraic equations. Instead of asking “What good decisions must I make to achieve my target outcome”, ask “What bad decisions could I make to ensure I fail at this?” At a minimum it helps set parameters or constraints on the decision making process by eliminating bad decisions. Charlie Munger famously delivered a graduation speech through the lens of inversion titled “How to Guarantee a Life of Misery.” This included prescriptions like “go down and stay down” and “be unreliable.”

Greek vases frequently portrayed Theseus, the Athenian prince, navigating the maze with a ball of thread in order to retrace his steps. Theseus confronted and killed the Minotaur, an act of bravery immortalized in the art of a civilization.

Greek vase, circa 500 BCE

Unearthed from the soil of Knossos, the coins bore the engravings of the labyrinth.

Hellenistic coin from Knossos, 300-200 BCE

The human fascination with mazes has continued through the centuries, exemplified by the Labyrinth of Versailles, the Chartres Cathedral Labyrinth, the Turf Maze at Saffron Walden, the Hedge Maze at Villa Pisani, and the Gardens of Bomarzo, to name a few.

In the 19th and 20th centuries, biomedical research began to extensively employ rat mazes to investigate learning, memory, spatial navigation, and the impact of brain injuries and drugs on these abilities.

Today, we understand that rats can navigate remarkably complex mazes

In "The Secret of Words," Noam Chomsky highlights that while you can train a rat to navigate a complex maze, you can never train it to run a prime number maze—a maze that dictates, "turn at every prime number."

Rats lack the concept of prime numbers, and there is no way to impart this understanding to them.

This raises a profound question: why would humans be any different from rats in this regard? What might exist in the world that we have no concept of?

It's far from certain that life isn’t a maze beyond our conceptual grasp.

Economist Richard Zeckhauser, known for his work on decision theory, categorizes the information used to evaluate decisions as “known,” “unknown,” and “unknowable.” This framework aids in understanding how decisions can be made under varying levels of uncertainty.

The known encompasses all readily available and well-understood information. This includes facts, historical events, and future events with predictable outcomes. For example, the laws of physics, the winners of World War I, and the 16.67% probability of a six-sided die landing on 1.

The unknown refers to information that is not currently known but is theoretically discoverable. Moving information from the unknown to the known through research, exploration, or experimentation can reduce uncertainty and improve the odds of a favorable future outcome.

In "Mastering the Market Cycle" for example, investor Howard Marks argues that by understanding where you are in the market cycle, you can position yourself to shift your outcome curve in a favorable direction. If indicators suggest a market cycle low, more aggressive portfolio positioning can tilt the odds of higher future returns in your favor.

The unknown consists of factors or outcomes that are inherently unpredictable and cannot be known, even with additional information or research. These elements are often subject to significant randomness, complexity, or the conceptual limits of understanding. No amount of information can move the unknowable to the known. Examples include forecasting the distant future or the prime number maze for rats.

The unknown is represented in the "fat-tailed" ends of a probability distribution, also known as black swan events, as described in Nassim Taleb’s insightful work, "Fooled by Randomness."

If you can discern which category of knowledge something falls into, you can determine whether seeking more information will be fruitful.

It is our human tendency to turn to experts in the face of uncertainty. However, despite the self-confidence of academics, pundits, and talking heads, decades of longitudinal research presented by Philip Tetlock in “Superforecasting” have quantitatively shown them to be no better than chance in predicting future events within their respective fields.

Tetlock did find a small percentage of experts, known as "superforecasters," are in fact better than chance due to their use of techniques like probabilistic thinking and Bayesian updating.

So, the next time you feel like a rat caught in a scary maze, ask yourself: which category of information on the knowledge continuum am I dealing with?

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In 2006, the 65 year old Ryuken accepted a challenge match against 35-year-old Iwakura Tsuyoshi, a Japanese journalist and mixed martial artist.

Ryuken agreed to let the fight be filmed.

The height of self deception is believing one cannot be injured or killed in combat against a fellow great ape. Beyond a certain level of self deception consequences start to come increasingly without warning.

Another example of the emperor has no clothes.

Richard Feynman famously said "the first principle is that you must not fool yourself, and you are the easiest person to fool."

Feynman is talking about the unknown unknowns of Donald Rumsfeld matrix, meaning you and I are fooling ourselves about something right now without knowing it.

The unknown unknowns is why labeling things is so corrosive to clear thinking. Labels are a compression algorithm for a multivariate object. Think conceptual zip file. Labels are an incomplete, low resolution map of the territory, a symbolic representation of a more complex structure.

Label yourself a touch less knockout master long enough and the label no longer survives contact with reality.

Once unmoored from the territory the label is a tool used to dig the hole of ideology.

Ideology means you outsource considerate thought to a Netflix style subscription bundle of ideological opinions, not realizing all shows are certain of their righteousness.

A useful indicator for political ideology is the following: If someone can derive all your political positions only knowing a single position, it’s likely you’ve hit subscribe.

Once subscribed you become a walled city believing there is nothing worthwhile beyond the walls. There’s a reason that in the opening act of Siddartha, the Buddha, he must leave the walls of his comfortable and privileged Brahmin life.

A subscription to certainty is a subscription to a feeling, perhaps moral superiority. Perhaps it’s the feeling of safety brought forth from a stable world view.

The problem comes as stability tends toward petrification. You ossify.

To go look and find out for yourself and to be wrong requires the destruction of a neural structure. It’s a real biological, cellular death. Through the reweighting of a neural network comes a horizon of apoptosis where what remains is scavenged to rebuild. Emotionally it’s uncomfortable.

The Jungian view is to look at the monster and know it will get worse for a time but with looking comes enlightenment - seeing that the monster has always been in service of you.

In a world of constructed meaning the purpose of looking is so your ideology dies instead of you, the continuous self that manages the transformation.

Every year, despite flashing warning indicators, people die on Everest because they are unable to turn back from the summit.

The climbers must know the answer to the question they come to ask. They must obtain what they come to seek.

They risk their lives to see the monster for themselves.

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We’ve already witnessed the equality of outcome experiment in the classlessness of the former the Soviet Union and Mao Zedong’s Chinese revolution. Its echos continue in North Korea.

Government policies can shuffle wealth and resources but is unable to shuffle elements of inequality that are more qualitative, such as the distribution of talent or personal preference within a populace.

Equality of outcome, therefore, requires enforcement, often manifesting as killing for equality. Consider the application of the guillotine during the French revolution’s reign of terror for example.

On the other hand, the American dream is an ongoing equality of opportunity experiment. People with varied structural starting conditions and personal preferences have a historically unprecedented path for upward socioeconomic mobility. This is a revolutionary way to structure society.

As the great social experiment that is the American dream continues to unfold, remember there are no guarantees it works indefinitely.

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Our natural inclination is to identify patterns that reinforce our pre-existing beliefs. The more entrenched these beliefs become, the more they obscure any information that might challenge them.

The initial step in addressing this is to acknowledge that our worldview is inherently shaped by our beliefs. This step is profoundly challenging, requiring a division between the self that generates thoughts and the self that observes them.

Next, it's crucial to recognize that beliefs are like clothing; they can be donned or discarded at will. We possess the agency to retain what benefits us and shed what doesn't.

Just as a new outfit can alter our emotional state, adopting a new belief can alter our perspective on life. Beliefs, when chosen wisely, become tools suited to the different phases of our journey.

However, we often conflate beliefs with absolute truth. Yet, more frequently, they become rigid constraints that hinder our growth, causing us to ossify rather than evolve.

Remember you can always new outfits for a spin around town and just notice how they make you feel.

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What I’m about to describe is not merely a shift in perspective, but a tectonic upheavel, as profound as Galileo’s telescope which redefined the heavens.

Bear in mind, it took centuries of relentless effort for heliocentrism to gain widespread acceptance and these recent discoveries are likely to follow a similar path. Galileo died in 1642, and it wasn't until 1822 that the Catholic Church finally lifted its ban on heliocentric books.

Empiricism & the Scientific Method

Tim Urban asks us to consider human history as a 1000 page book, with each page representing 250 years of human history.

The really ancient Sumerians, who first came down from the mountains of modern day Turkey and Iran, don’t start until page 970. Buddhism begins on page 989 while Christianity begins on page 993.

What’s evident is that nothing happens until the final 1-2 pages, suggesting we currently live in the most extreme historical anomaly of human progress in all of history.

What happened on those last two pages to kick off civilizational progress?

The scientific revolution. It drove the enlightenment, the industrial revolution and the rise of empiricism as a pillar of Western thought. The Greeks were smart but handicapped without the scientific method.

The following chart from this Vox article emphasizes how human progress goes completely parabolic when the scientific revolution kicks off.

Science is the only tool discovered to date which reliably produces and compounds technological advancements. Nothing has relieved more suffering in the world then science. It is the flashlight used to peer into the surrounding darkness.

Empiricism gave us Darwinian evolution, cellular and genetic theory as well as anti-septics. Physics went from a sort of mysticism to the towering achievements of quantum theory and general relativity, which describe the universe at vastly different scales and under different conditions. One describes the probabilistic dance of subatomic particles and the other, the vast, curving expanse of cosmological space-time.

The grand challenge in the sprawling landscape of theoretical physics lies in uniting these two foundational but fundamentally incompatible theories.

Spacetime is Not Fundamental

Since the scientific revolution, physicists trusted the physical world could be understood because it could be measured. But when Heisenberg demonstrated in 1927 that subatomic particles changed behavior when observe all of physics was upended.

Schrödinger deepened the issue by proving electrons were just a series of probabilities which collapsed into one state when observed. If a continuous wave function always becomes discrete when observed by humans, how can reality even be knowable? Said another way, if the cat is both alive and dead until observed, why not the whole universe?

Particle physicists, probing the minutiae of the universe with instruments like the Large Hadron Collider in Geneva, have long relied on Feynman diagrams to tame the challenging equations that govern subatomic interactions.

These diagrams, born of Richard Feynman’s genius, translate complex integrals into manageable visual snapshots, depicting particles meeting and parting at precise points in space and time. Yet, even with their elegant simplicity, the calculations demand summations over countless intricate diagrams, considered a laborious and limiting task of modern particle physics.

An Example of Feynman Diagrams

In 2013, a paradigm shift emerged from the mind of theoretical physicist Nima Arkani-Hamed and his team. They introduced the amplituhedron, a multi-dimensional geometric wonder that promises to revolutionize our understanding of particle interactions. The amplituhedron distills the chaos of quantum calculations into the serene simplicity of geometry, reducing the summation problem to a single term: finding the volume of this abstract shape.

What makes the amplituhedron truly astonishing is its ability to describe particle interactions without invoking the familiar coordinates of space and time. This revelation hints at a staggering possibility: space-time, the very stage on which our perceivable the universe unfolds, might not be fundamental at all. Instead, it seems to emerge from a deeper, mysterious geometric structure.

The Amplitudehedron

The flashlight of science has seen something unnerving and implications are seismic.

Everything we know about the natural world, every physical law, every constant, all objects we see, can be seen as emergent properties, not fundamental truths. This shifts the foundations, unsettling our most basic assumptions about the universe.

In this new vista, the elegant dance of particles and the grand curvature of space-time would be seen as mere projections of a deeper, hidden reality yet undiscovered. The modern scientific pillars of quantum theory and general relativity are emergent from a deeper structure.

To summarize, if spacetime is not a fundamental property of the universe then we have no fucking clue what is actually going on.

In Evolutionary Game Theory Fitness Trumps Truth

That spacetime is not fundamental finds an intriguing partner in the work of computational neuroscientist Dr. Donald Hoffman.

The radical insights into the nature of reality and perception from his team at UC Irvine challenges our deepest assumptions about the accuracy of what we see and experience everyday.

In his TED Talk and book, "The Case Against Reality," Dr. Hoffman builds on the work of evolutionary game theory pioneered by John Maynard Smith in the 1970s, coming to the conclusion that the odds humans are able to perceive anything about reality through our senses is zero.

Evolutionary game theory is a mathematical representation of Darwinian evolution. It employs "fitness payoff functions" (clunkily named) to quantify the success of survival and reproduction strategies. These payoffs, expressed numerically, reflect the benefits accrued by competing agents within the game. A higher payoff translates to greater reproductive success, ensuring that winning traits dominate future generations

Consider a simple game with two strategies: Hawk (aggressive) and Dove (peaceful). When two individuals meet, their payoffs depend on their chosen strategies:

• Hawk vs. Hawk: Both fight, incurring high costs and low payoffs.

• Hawk vs. Dove: The Hawk wins easily, gaining a high payoff, while the Dove retreats with little to nothing.

• Dove vs. Dove: Both share resources without conflict, each receiving a moderate payoff.

The payoff matrix for this interaction looks like this:

Hawk Dove

Hawk (-10,-10) (10, 0)

Dove (0, 10) (5, 5)

• Hawk vs. Hawk: Both get -10 (cost of fighting).

• Hawk vs. Dove: Hawk gets 10, Dove gets 0. (Hawk wins)

• Dove vs. Hawk: Dove gets 0, Hawk gets 10. (Hawk wins)

• Dove vs. Dove: Both get 5 (sharing the resource).

Over many iterations, the strategy yielding the higher payoff proliferates, shaping the traits of a population.

Around the same time Dr. Arkani-Hamed discovered the amplitudehedron, Hoffman’s lab uncovered a profound insight: that an accurate representation of reality is not required for survival and reproduction

In simulations using two sets of agents, one optimized for fitness and the other optimized to see the reality of the environment, the agents optimized for fitness always outcompeted those optimized to see reality accurately.

The unsettling implication? Our sensory systems and cognitive faculties, honed by evolution, have virtually no chance of perceiving an accurate representation reality. Said another way, in Darwinian evolution fitness always trumps truth.

This discovery raised the next pivotal question: do the fitness payoff functions that drive evolutionary success preserve any structure of the underlying reality?

Hoffman’s team explored this question using branch of mathematics called holomorphism, which studies the preservation of structural properties within data sets undergoing transformations.

Hoffman's team found that evolution preserves only fitness-relevant information and does not preserve any structure of the underlying reality or truth. Our vision, hearing, and other senses retain and utilize only fitness-critical data, with no representation the actual world.

Building on these findings, Hoffman's "Interface Theory of Perception" posits that our senses have evolved to perceive objects in our world similar to the icons of an iPhone App. The App is a useful interface but is not an accurate structural representation the toggling of electrical voltages in the hardware underlying the icon. Just as you don't need to understand the inner workings of a computer to send an email, our perceptions offer a user-friendly interface that bears no resemblance to the architecture of reality that underlies it.

Thus, while something real underlies our perceptions of a tree, a dog, or a house, these perceptual icons bear no resemblance to the underlying reality. Our evolved sensory systems are essentially a dumbed-down virtual reality headset, sparing us from the overwhelming complexity of the truth. Without filters or an interface we would drown in the information. Notably psychedelic compounds, like psilocybin mushrooms or LSD, dial down the headset filter so more perceptual information rises to consciousness.

In this view, humans navigate the world with a streamlined interface, evolved for fitness, not for truth. This is a profound departure from our assumptions about the nature of reality.

The Hard Problem of Consciousness

To quickly review, the theoretical physicists are indicating that spacetime is emergent rather then fundamental to the universe. Spacetime appears to emerges from geometric structures like the amplitudehedron and to unite general relativity and quantum mechanics spacetime must be discarded.

New insights from evolutionary game theory dovetail with the idea that spacetime is emergent, indicating our perceptual systems evolved to construct a simple world of icons optimized for fitness rather perceiving the truth of reality. Spacetime may turn out to similarly exists only within our perceptual VR headsets.

At the heart of these intertwined revelations lies the hard problem of consciousness: the question of how and why subjective experiences arise from physical processes. Traditional materialist views hold that consciousness emerges from neural activity in the brain and if we keep digging for more neural correlates of function, at some point consciousness spontaneously emerges.

But what if the brain is just a perceptual icon? What if the brain, which neuroscientists have presumed to be a correlate of consciousness, does not even exist inside our skulls until observed?

The bold stance taking hold within the field of consciousness research is that rather then consciousness emerging from the physical world of spacetime, our physical world of spacetime emerges from consciousness itself.

This aligns with the quantum phenomenon that electrons (and thus reality itself) seem to exist as a probability space until observed by a conscious agent. It is only when observed does anything we perceive become discrete.

Said another way, the spirit of being generates the universe into a structure of meaning, because without a conscious observer, the universe is a field of indeterminate possibility. This indicates that everything you see in the world makes itself manifest in accordance with your aims, i.e. you see only what you will into being.

Grappling with these very same topics, Einstein once said that “matter is spirit reduced to the point of visibility. There is no matter.”

The Water is Deeper Then We Thought

Kurt Gödel’s Incompleteness Theorem, unveiled by the Austrian logician in 1931, stands as one of the towering intellectual achievements of modern times. It illuminated the inherent limitations of our frameworks for understanding the world, demonstrating that some truths lie forever beyond the reach of formal systems.

As we venture into the next phase of scientific inquiry, where the boundaries between science, philosophy, and spirituality blur, Gödel’s insights remind us of the profound complexity we face. If science is a system striving to map the vastness of reality, it can never achieve a final theory of everything; it will only unearth new layers of truth.

Perhaps it is in fact turtles all the way down.

Since the aim of good science is to break its own models, it’s said that science progresses one funeral at a time,. It’s the the death of a model that points us to the next discovery. In this case, it’s the death of spacetime and the implications are unsettling.

There is something out there, outside of spacetime, from which our world emerges and our perceptual systems are not tuned to see any hint of its true form.

The always prescient Nietzsche famously said “battle not with monsters, lest ye become a monster, and if you gaze into the abyss, the abyss gazes also into you.”

And so we humans journey onward into the abyss, guided only by a flickering flashlight and the indomitable human spirit.

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This post delves into the structure of our nervous system and the profound implications of our sensory limitations, challenging the notion that we have experienced anything close to the full spectrum of reality.

The Structure of the Human Nervous System

The following photo is a real dissection of the nervous system done in the 1880s. Before such dissections, it was not at all self evident to humans that we are a floating system of electrical wires.

Starting at the periphery, there are six special subtypes of neurons: mechanoreceptors, thermoreceptors, nociceptors, chemoreceptors, photoreceptors and proprioceptors.

These specialized receptor neurons have an architecture tuned to capture environmental signals like the electromagnetic radiation of visible light, atmospheric pressure waves of sound and the chemical detection of taste and smell. Some subtypes are temperature and tissue damage indicators. Some inform us where our limbs are in space.

The receiver end of the neuron is called the dendrite, from the Greek “dendron” for tree. The fractal structure of dendrites increases the computational power, network scalability and robustness of the entire system via increased surface area for connectivity.

Histological stain of a mouse neurons using expansion microscopy.

When an environmental signal is detected, neurons exchange electrolytes across their cell wall, forming an electrical voltage for signal propagation.

For example, the neurons in your heart use the sodium, calcium and potassium you consume in food to create this voltage. If you flood the system with an abundance of one electrolyte, such as the potassium chloride used for lethal injections, the heart tissue cannot generate an electrical charge to contract the muscles of the pump.

Neurons fire in an “all or nothing” fashion, meaning the trigger to send a signal is either pulled or not pulled. Since there is no intermediate discharge, it has close parallels to computational systems using binary 0 and 1s. From this emerges computational neuroscience, which uses electrical engineering, computer science and physics to understand how the nervous system processes information.

While not nearly as efficient as an electrical conductor constructed from elemental metals like copper, neurons follow electrical engineering principles such as Ohm's law, capacitance, and thermal insulation. You can see in the dissection photo how nerves thicken near the spinal column to conduct an increasing amount of charge.

To summarize so far, perceptual information from the environment is captured by specialized receptors in our nervous system and transformed into an electrical signal using electrolytes which is sent to our brain.

At the highest level, the primary function of the brain is to make adaptive models of the external and internal environment using interoceptive and exteroceptive information. These models are continuously updated based on the incoming perceptual information stream to make probabilistic adjustments about how to think and behave.

Said another said, the ability to construct a cognitive mental model of a probabilistic future is imagination. Imagination is one of the greatest advantages humans possess.

The triune brain is an older but useful evolutionary theory of brain development. It’s a model that is too reductionist from the standpoint of neuroscience but is practical in related disciplines, like psychology. The idea is that neuroanatomical structures closer to the spinal cord are more evolutionarily ancient while farther exterior structures are more recently developed.

The triune brain is three interacting operating systems.

1. The autonomic functions and reflexes as well as balance and locomotion nestled in the cerebellum and brainstem. This is the fight or flight basement level reptilian brain shared by most mammals.

2. The limbic system which colors incoming information with an emotional charge. The psychologists would call this the emotional valence you feel for everything in your environment. It’s like magnetism in that all objects are on a valence spectrum of attractiveness or averseness. You move towards objects with positive valence and retreat from objects with negative valence.

3. Higher cognitive functions like rational thought come from the highest and most evolutionarily recent neocortical structures. Consider these higher cognitive systems as regulators of the emotional and locomotive systems. A fixture clinical case study in neurology and psychology, railroad worker Finneus Gauge suffered cognitive defects specific to impulse control after an iron rod destroyed much of his left frontal lobe in an 1848 accident.

Next, let’s explore the quantitative limits of our sensory receptors to underscore our limitations in constructing an accurate worldview. Just considering how much of our environment is invisible to our perceptual interface and that sensory receptors optimized for reproductive fitness would be very different then ones optimized for truth or understanding, it seems highly likely that our senses hide a world much deeper and complex then we can imagine.

The Limits of Human Vision

All humans have an optical blind spot where the optic nerve connects to the retina, resulting in an area without photoreceptors. This blind spot is compensated for by the visual cortex, which fills in the missing information from the other eye.

You can find your blindspot using the following picture.

1. Close one eye and fixate the other eye on the X in the middle. Start approximately 10-12 inches from the screen.

2. While fixated on the X with one eye closed, move your head forwards and backwards until the dot on the side of your open eye disappears.

Human vision is restricted by the tuning of our photoreceptors to only the spectrum of “visible light,” which ranges from 380 to 750 nanometers. The entire electromagnetic spectrum ranges from gamma rays at less then 0.01 nanometers to longer radio waves thousands of kilometers wide.

The visible light range we detect with our eyes makes up only about 0.0035% of the entire electromagnetic spectrum.

In some cases technology can greatly enhance our perceptual capabilities, for example in night and thermal vision goggles.

The Limits of Human Hearing

Our ear drum is a biological piezoelectric device that converts mechanical energy to an electrical signal that our brain interprets as sound. The mechanical energy arrives in the form of a pressure wave moving through the atmosphere.

Sound frequencies on Earth range from the infrasonic to the ultrasonic. Infrasonic sounds down to 1Hz are used by humans for geological monitoring and by animals like elephants for infrasonic communication. Ultrasonic frequencies up to 1,000,000,000 Hz (1GHz) are used in medical diagnostics and industrial applications as well as animals like bats for navigation.

Human hearing by comparison is confined to a frequency range of 20 Hz to 20,000 Hz. Considering the entire sonic range, humans can only hear .0002% of all sound.

The Limits of Touch, Taste and Smell

Since taste and smell is a function of chemical density and touch is captured by force or temperature rather than electromagnetic wavelengths it’s hard to establish a comparative range that makes sense. However, their limitations are illustrated when compared to other animals. Humans are at least tenfold weaker in these perceptual realms compared other animals.

A cortical homunculus maps the density of sensory specific brain tissue dedicated to interpreting perceptual information in a proportional representation to the external human body.

Said another way, far more more computational power via neuronal density goes into monitoring the feeling in our hands and face then the rest of our body.

Human touch sensitivity can detect indentations as small as 13 nanometers. Compare this to the star-nosed mole, which can detect differences as small as 1-5 nanometers.

The human tongue has about 10,000 taste buds, each capable of detecting the five primary tastes: sweet, sour, salty, bitter and umami. By comparison taste dominant animals like fish can have over 100,000 taste buds covering their entire body.

The human nose can detect a few parts per billion of smell. By comparison dogs can detect a few parts per trillion.

The Time Limits of Experience

It’s interesting to examine the total time afforded by a single human lifespan to collect perceptual information compared to the collective amount of time all humans have experienced.

Think of your life as small box in spacetime contained inside the much larger box of all human experiences over all of human time. In many ways this is the collective unconscious first explored by Jung.

To calculate total personal experience hours, multiply your age by the number of hours in a year. As a 36 year old this comes out to 36 years x (365 days x 24 hours) = 315,360 lifetime hours.

To calculate the total hours of human experience across history involves taking the total hours of the estimated 108 billion people ever born, who lived on average (until recently) 35 years. This comes out to approximately 33,112,800,000,000,000 lifetime hours.

Dividing personal hours by total human hours gives us 0.000000000952%, a sliver of the total human experience.

Why You Have Not Experienced Anything

To summarize, the basic structure of the nervous system is that peripheral receptors convert perceptual information into an electrical signal which allows our brains to continuously update a predictive, probabilistic cognitive model of the world and make adaptive corrections to the model.

It’s like we’re an electrically charged, terrestrial jellyfish navigating an ocean of energetic quantum superposition just trying to live long enough to reproduce.

Said another way, life is the perceptual experience of flashing lights, sounds and experiences that you attach meaning to over time.

It’s evident we perceive only an infinitesimal sliver of the world through our sensory organs and we are not afforded much time to do it. The final step is to multiply your lifetime experience hours by the trickle of sensory information our nervous system can capture to appreciate how little of the world we perceive. For myself at 36 this is approximately 0.000000000000000000006664% or said another way, a rounding error.

Lastly, its important to understand that, not only is our perceptual view into the world like standing in a pitch black room with earplugs in, but very little of that perceptual information makes it to conscious awareness. The value hierarchy by which our brain processes incoming information is tuned for survival and reproduction, only perceiving reality at the minimum level required for its tuning. For example, the informational value of a car barreling down on you while crossing the street takes hierarchical priority over the informational value of noticing a strangely shaped pebble on the asphalt. A hierarchy tuned to the truth of reality would weight information differently and likely rapidly been extinguished by natural selection since reproduction is not whats optimized.

So in the face of this, how can you possibly hold any ideological or dogmatic beliefs?

How can you think you know the best way for society to be structured when you have experienced so little?

How can you possibly think that you know anything at all?

Consider these limitations to counter to the human tendency towards pride and ego. It’s no accident that humility is a virtue in almost all philosophical, religious and ethical systems around the world.

Issac Newton reportedly said the following towards the end of his life:

“I do not know what I may appear to the world, but to myself I seem to have been only like a boy playing on the seashore, and diverting myself now and then finding a smoother pebble or a prettier shell than ordinary, whilst the great ocean of truth lay all undiscovered before me."

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From Galileo’s manual crafting of telescope lenses in the 16th century we get the scientific revolution.

From Benjamin Franklin grinding and polishing of spectacle lenses we get bifocals.

From microscope lenses we get germ theory, anti-septics and modern medicine.

From spectrometer lenses we get the periodic table, the elemental building materials of the universe.

Without the lens of our eyes to focus light onto our retina we are blind. This is the global health challenge of cataracts.

Even cognitive biases act as a mental lens which shape how we perceive information.

In fact, all beliefs you hold are a series of lenses you place upon the world to help you filter and interpret what you see and experience. Life is, after all, fundamentally a series of blinking sensory information and experiences upon which we place a narrative of meaning.

Left to right quality comparison of the early Iphone’s camera lens, Lisa Bettany

There are common characteristics shared by all types of lenses.

Changing the shape and curve of a lens will change the signal which enters into, traverses across and emerges from it.

Changing the material used to construct a lens will change how the signal is refracted. It will also affect the speed of the traveling signal.

Between a source and detector there is a physical distance a signal must cross which times take. This inherent time delay is sometimes important and sometimes not but important to be aware of.

Light from Andromeda, our closest neighboring galaxy, has a time delay of 2.5 million light years.

The morning sunlight on your face by comparison is only 8 to 9 minutes old.

There is even a question of whether physical reality requires a lens, detector or observer to manifest at all.

This is the famous double slit experiment, where the photon only collapses from probabilistic wave into a lower energy particle state when observed.

This is Heisenberg’s uncertainty principle, where the superpositioned electrons in the orbital cloud of an atom collapse into a definite location only when observed and measured.

This is Schroedinger’s cat in the box who is both alive and dead, only maybe killed by poison until observed.

This is the “esse est percipi” (to be is to be perceived) of George Berkley’s famous philosophical question about the sound of a tree which has fallen but is unheard by an observer.

With incomplete, inaccurate or poor quality detectors of physical reality comes a correspondingly incomplete, inaccurate and poor quality construction of physical reality.

It’s foundational that our physics is only as good as the quality of signal our human invented detectors of physical reality allows for.

For example, 27% of the universe’s mass-energy content appears to be composed of dark matter per the math but our detectors are not sufficiently advanced to capture it.

The top left image is from the 2021 James Webb Space Telescope. The lower right image is from the 1990 Hubble Space Telescope. Notice the image quality difference across 31 years of technological advancements. Barreled Spiral Galaxy NGC 1512.

Each of our personalized cognitive lens of belief transmutes the signal of reality which forms our perceptions of truth.

So the accuracy of the reality you construct is only as good as the quality of your tools of detection. With faulty tools you construct a faulty worldview.

With faulty tools you are the potemkin villages of North Korea.

With faulty tools you are a house built on a foundation of sand, no matter how intricate the architecture

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However far you wander, awareness is always there.

However far you look, it stretches past the horizon.

Awareness doesn’t have a beginning or an end. It’s just behind everything hanging out, observing and omnipresent.

Walter de Maria Lightning Field, New Mexico

Your life is a cloud in the sky of awareness. 

With high winds the clouds of life are in movement or stillness without. They cast shadows and are illuminated in sunset. 

The content of the clouds includes everything you identify as you.

It is the unique genetics and experiences that have formed your ego. It is your name, which Dale Carnegie described as the “sweetest, most important sound in any language.”

Ego is your inner voice, which is the voice of your parents, which is the voice of their parents and so on. 

The ego wants to be remembered. It wants to exist. It will tell you it’s real. The voice of the voice of the voice of your ancestors in your head has to be real, right? 

The super organism will always fight for its survival.

Through stories we remember egos past. Some have been been so large and dense they remain as mythology in the history of the species.

But ego is formless like clouds. Time moves forward and egos appear, change and dissipate into nothingness. 

It’s important to understand that the clouds are not fundamental to the existence of the sky. On a cloudless summer day the sky exists.

Awareness is what remains when you discard the content of you.

Most people die having lived a life in the clouds. Everywhere they have looked cloud is all they’ve seen so it is all they know. To most nothing else can exist because that is all of life.

Most civilizational cultures have a mythology of life outside the cloud.

Christianity has heaven, hell and purgatory. Islam has Jannah (paradise) and Janannam (hell). Hinduism has samsara (reincarnation, the reforming of clouds) and moksha (liberation from the reincarnation cycle, dissipation of clouds). The Buddhists call moksha nirvana. Judaism, while less explicit, sees a final divine judgment and the occasional resurrection of the dead.

Dante and Virgil Climb Down on Lucifer, The Divine Comedy, Dante’s Inferno, 14th Century

At the moment of rapture the faithful dead are resurrected to join the faithful living in the clouds to meet the Lord in the air.

At the moment of rapture the voice of the voice of the voice of your ancestors exists in perpetuity. You too shall live forever in the kingdom of God if only you truly believe in your heart of hearts.

The Last Judgment, Michaelangelo, Sistine Chapel in Vatican City, 1541

You see, the ego wants to live forever. To each and every one of us it whispers the fear death. However, ego is the one afraid of its inevitable non-existence.

Why would the sky fear non-existence of the clouds if they are not fundamental to its existence?

The collective ego of humanity is the author of its own mythology. Our collective unconscious is the invisible hand guiding the ouija board to spell its own name. 

Beliefs are not real. They are not fundamental to the workings of the universe.

The belief structures of humans exists on top of the structure of reality. This meta structure has existed for a very short time on the scale of the universe. For our species, at this moment in time and maybe forever, it is a black box. We do not know what other meta structures exist in the complex adaptive system of the universe.

Beliefs are a guess at the inner mechanism inside the box knowing all phenomena observed with our detectors of physical reality are in a constant states of flux and transformation.

However like ego, beliefs appear, change and dissipate into nothingness. 

A belief is not falsifiable. There are no measurements or observations that can refute it. 

For instance, the statement “all swans are white” can be refuted by seeing a black swan.

On the other hand, the statement “there is a force that influences us but is undetectable by any scientific instruments” is not falsifiable since no observation or measurement can be made to disprove it. 

Falsifiability allows for hypotheses to be tested and disproven, which is the fundamental mechanism by which scientific knowledge progresses. 

A non-falsifiable hypothesis is a belief. It may be meaningful in philosophical, theological or personal contexts but is not real. 

To be a Christian is to believe in the resurrection story of Jesus. It is a belief because we cannot falsify the resurrection.

To be an Atheist who proudly states they do not believe in God is also to hold a belief. Atheism is just a belief nestled inside the belief in God. Since there is nothing measurable in fundamental reality that falsifies the existence of God, it is also a system of belief.

The Atheist example illustrates how tricky the structure of belief can be. Beliefs feel real. They feel like critical scaffolding which holds the weight of your identity. This is the illusion of ego.

Remember you are awareness. You are the sky and not the clouds

New Mexico

If you thoughtfully trace back the cause and effect origins of your beliefs you come to see beliefs are an inheritance. They are a narrative you have told yourself your whole life. But they are more of a feeling, often the feeling of safety, certainty and equilibrium. 

Your beliefs are an inherited bloodline of narratives from your tribe as a child. They are mimicry of the beliefs of the apes you most wanted to please as a child. Anyone who has had children understands that at our core we are mimetic creatures. Consider the five chimps theory.

All the joyous and painful experiences of your life have shaped the cloud of your beliefs. From experience, the tendency is to prematurely conclude something about reality as a universal truth when it is not. That is the human tendency deep in the cognitive programming. It’s the man behind the curtain in the Wizard of Oz.

Recognize the truths of your childhood are not falsifiable. When you feel anger or discomfort when strongly held beliefs are challenged it is the ego fearing for its safety, certainty and equilibrium. Recognize you are defending a feeling not a truth. 

Awareness is to empty your mind of belief structures and be formless and shapeless like water. When put into a cup, water both forms into a cup and does not need the structure of the cup for its existence. Belief and ego are not required for the existence of awareness. That is to say, there is no spoon.

It’s the principle of Wu Wei. It’s awareness allowing ego to float effortlessly with the river of life rather then drown trying to swim upstream. It’s Bruce Lee saying “be like water making its way through cracks. Do not be assertive, but adjust to the object, and you shall find a way around or through it. If nothing within you stays rigid, outward things will disclose themselves.”

It’s Emperor of Rome, Marcus Aurelius writing in his journal that the constancy of change must be accepted because there is no other option than death.

Marcus Aurelius, bronze, 175AD

Beliefs matter. Beliefs are relevant. Beliefs change the world of humans and so have power. They are important.

But only to us and our egos.

For they do not exist in physical reality. They are not fundamental to the workings of the Universe.

The practice of meditation is the practice of discovering there are edges to the clouds. It is the practice of moving beyond the margins of ego into awareness. It is understanding the clouds of life are not the totality of existence. It is a way of moving you may have never experienced because you move outside of intellect, ego and belief.

Without awakening to awareness, you are the child who knows only white swans.

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As each penguin pushes into its neighbor, a spiraling wave like movement propagates through the herd. This shuffling spiral rotates penguins at the periphery into the warm interior and moves those in the middle out to the periphery to have another lap. This spiral motion minimizes the space between neighbors, maintaining the density of the herd to protect against heat loss.

It’s like a big bonfire the penguins keep lit to survive the winter.

So animals gather in herds for good reason.

A herd offers collective defense against predators, weather and starvation. Spread out on a grassy hill the animals more quickly locates food or water. There are genetically diverse mates readily available. Within the herd, the individual constituents can have slightly better odds of survival because the herd does not play zero sum games.

It’s the deranged penguin that abandons the herd to pursue its own fortunes.

Werner Herzog’s Encounters at the End of the World

It’s important to realize that we humans are psychological herd animals.

In "The Lucifer Principle," Howard Bloom describes these psychological herds as a "super organism" – a complex meta-structure intimately interwoven through genetics, human behavior, and culture. This concept suggests that entities like your family, community, culture, ideology, religion, and country function as single entities, operating within the world using interconnected and interdependent components made up of individual people.

Similar to a bee hive or an ant colony, psychological super organisms will exhibit behavioral characteristics such as self regulation, homeostasis, collective intelligence, self replication, adaptive structuring and complex communication networks.

Ant colonies can form interconnected nests linked across vast areas called super colonies. They have anti-fragile characteristics. For example, destroying a line of ants can split the colony and worsen the invasion.

Due to the internet, there has been no time in history where roaming psychological human herds are more interconnected and self reinforcing. In the mindless scrolling it’s easy to mistake entertainment for cognitive programming. Logging into your social media account has replaced the Christian revivalist tent.

Nietzsche wrote about our tendency towards psychological herd behavior.

To leave the psychological human herd is to discard a system of morality and values. Perhaps even those of your parents or close friends.

Nietzsche felt this was accomplished only through self mastery, ongoing learning and intense introspection, after which a new value system tailored to each individual begins to take form. The“Ubermensch” thus transcends human mediocrity and reversion to the mean. The math is simple. For average outcomes do average things.

The challenge in aiming for extraordinary outcomes is all herds have social contours and rules about how to behave. When male lions reach maturity, leadership disputes are common. If the challenger loses, the young lion is at best expelled and at worst killed by the herd. The challenger must be killed because social cohesion is crucial for survival of the pride.

It is the “deranged’ penguin who wanders into the Antarctic wasteland in pursuit of something yet undefined.

To abandon a human herd means to incur attack from the power embedded in the social hierarchy. This power can be considerable. Consider the Salem witch trials or the McCarthyism during the cold war.

It is an attack motivated by the self preservation instinct of the super organism. It knows when enough blocks are removed from the Pyramids they collapse under their own weight.

In humans, Nietzsche felt such attacks came from our tendency towards envy.

The weak envy the strong. The ill envy the healthy. The slaves envy the masters. The poor envy the rich.

Do not covet they neighbors wife is a commandment for a reason.

Envy is one of seven deadly sins for a reason.

Even within the scrum of Emperor penguin spiral the aim of those on the frigid margins is to displace those in the warm interior. The many at the bottom always aim to displace the resource rich at the top.

Nietzsche observed a common lever by which this cyclical dethroning mechanism occurs in humans societies is the construction of binary moral systems, where those at the bottom vilify the attributes of those at the top and set themselves in diametric moral opposition.

This is good and evil, the oppressed and the oppressors, the poor and the rich, Saints and sinners, the French royalists and revolutionaries, Roman citizens and barbarians, Protestants and Catholics, the Islamic faithful and infidels, American capitalists and communists, Russian-Marxist proletariat and the bourgeoisie, Democrats and Republicans and so on.

When you view the world in such moral binaries it’s easy to believe you live in a world full of enemies.

And so humans will also try to kill, literally or figuratively, those who abandon the herd.

Indian spiritual figure Jiddu Krishnamurti, who advised against blindly following any guru, doctrine or spiritual authority, asserted that “truth is a pathless land.”

To set off into the psychological Antarctic alone and on foot, at great peril to yourself, is one of the highest moral aims. There is no a map anyone can give you.

The Übermensch is the homeless, beggar philosopher Diogenes, holding a burning oil mid day searching Athens for an honest man.

The Übermensch is also Socrates, sentenced to death for impiety by a jury in Athens, who accepts the hemlock chalice and chooses, for himself, death before dishonor.

In reading Plato’s written record of Socrate’s final reflections it is apparent why the herd wanted him dead.

Jacques Louis Davis, the Death of Socrates, 1787

The crux of this is how we all must decide the meaning which exists in our life for ourselves. Meaning does not exist external to you. It cannot.

Anyone who has ever abandoned a faith will tell you this is not easy. It requires a radical act of self immolation, subuku or psychological suicide because the super organism, an extension of the ego, is in an existential fight for its very existence.

To follow the advice of Nietzsche is to live a life of authenticity, in alignment with your highest self discovered values and to discard the life others want for you.

A few quick thoughts I think are interesting.

The penguin spiral resembles engineering systems that require heat distribution management or risk catastrophic failure.

A reverse penguin spiral is a combustion engine cooling systems that moves the engine heat to the radiator via radiator hoses filled with coolant.

Or the heat sinks and fans required by high performance computer processors. A MacBook Air is thinner than a MacBook Pro because the Air processor is not powerful enough to require a fan cooling system.

It’s like physiologic blood shunting in hypothermia. The body prioritizes warming the organs in the torso and head at the expense of fingers and toes.

It’s important to learn the physical laws of nature, such as thermodynamics, because all things follows these rules. You can never expect to play the game of life well if you don’t understand the basic rules.

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Consider circadian rhythm, the four seasons, menstrual cycles, reproductive cycles, hormonal cycles, feeding cycles, migration cycles, plant growth cycles, life and death cycles, climate cycles, generational cycles, political cycles, cultural cycles, cycles of empires, debt cycles, and cycles of war and peace.

For example, consider the life cycle of the modern human.

The typical life arc, from Ray Dalio's Life Journey Exercise

Not everyone experiences each checkpoint in the same sequence, and some stages may be omitted altogether. The crucial idea is that by recognizing your place in the cycle, you begin to peek around corners to better see where you are going.

This underscores the significance of studying history. It turns out everything has occurred previously. Never exactly the same but the contours often have the same feel. If you're unaware of the history preceding your birth, you will live your life like a child experiencing everything for the first time.

The ever insightful Mark Twain wrote that “history doesn’t repeat but it does rhyme.”

For instance, if you're pondering whether you should be concerned about the United States government's debt, consider examining the debt of past empires. Read about the United Kingdom's debt burden during the Napoleonic Wars and World War I in the 18th and 19th centuries; or the fiscal challenges faced by France under King Louis XVI prior to the French Revolution; or Spain's financial strain during the Eighty Years War and Thirty Years War in the 16th and 17th centuries; or Japan's debt crisis in the late 20th century; or Germany's economic struggles after World War I culminating in the rise and fall of the Third Reich; or the debt crises in Argentina and Greece—the examples are plentiful. Debt is a recurring theme throughout history.

Understand that the dead outnumber the living 14:1. Many wrote the details of all these historical events down. Find the history relevant to you and read it. You, your family or your country are never the first to go through whatever it is you are going through.

These cycles likely persist because our fundamental human nature (the human operating system/OS) remains unchanged over recorded history. Biological evolution occurs gradually, so the core aspects of human behavior have persisted. Therefore, insights from historical and classical texts, such as those by Marcus Aurelius in 150 AD about human psychology, remain highly relevant today.

This leads us to the cyclical nature of capital markets and the most important question. Why do markets exhibit cyclical behavior at all? And why is cyclicality so ubiquitous in the world?

Consider this: If the average growth rate of US GDP is 2%, why doesn't it consistently grow by 2% each year? Similarly, if the S&P 500 index returns an average of 10% over 100 years, why doesn't it yield a 10% return every year?

Why doesn’t it move in a straight line upwards? Why do market crashes and bubbles occur?

Because like history, the market is made up of people feeling feelings driving behaviors based on those feelings. When all those people feeling feelings start exchanging resources based on those feelings it becomes a market. And just like animals in the wild, those feelings careen between fear and greed. The principle aim for all living beings is to not get eaten and hoard scarce resources when your next meal or mate is not guaranteed. It’s built into the architecture of the human OS.

Like a multi-cellular organism made up of single cellular organisms, the market is a super humanoid organism made up of smaller, similar human organisms. Given its size the super organism can feel things intensely. The intense emotion of the herd when it detects danger and feels fear or detects resources and feels greed will propagate through all the people that make up the super structure.

This emotional propagation causes a behavioral stampede, creating market bubbles and crashes.

Conceptually, it functions like a pendulum tracing a sine wave over time, moving back and forth between fear and greed.

Looking down on a pendulum wave

During bubbles, greed drives the herd to frantically purchase stocks, sometimes with leverage, causing prices rapidly rise. When we see our neighbor getting rich in the stock market, even if they’re just paper profits, our tendency is to FOMO in. Eventually, the price of the stock surpasses the actual value of the business setting up the crash.

There is an analogous phenomena in the wild called a feeding frenzy, where an abundance of food triggers a competitive rush among predators and scavengers to consume as much as possible in a short time, setting up the upside swing of the pendulum. In the market, think cheap debt driving the rise of speculative asset prices.

The animals will exhibit aggressive and violent behaviors. The frenzy can become so intense it disrupts the surrounding ecosystem as anything edible is consumed out of FOMO, setting up the downswing of the pendulum.

To see the mechanics of a feeding frenzy at the microeconomic level, consider the COVID-19 supermarket run on toilet paper.

Imagine you are a toilet paper manufacturer. Investors are bullish on your company's stock, expecting robust profits due to high demand amid empty supermarket shelves. They have purchased stock shares in your company to a record all time high. Responding to this, management decides to invest in additional toilet paper production factories to meet the surge in demand.

However, just as the frenzy for supermarket toilet paper starts to ease, the increased supply from the new factories floods the market, leading to a rapid decline in demand. Now in a surplus, sellers attempt to move excess inventory by dropping the price of toilet paper to incentivize buyers.

Consequently, during your company’s next quarterly earnings report, a decline in profits is announced attributed to the lower price of toilet paper. As investors interpret this decline as a negative sign for your company’s valuation, they begin to sell their shares, driving down the stock price.

Now let’s look at the capital market cycle in more detail.

The Upswing

During the upward phase of the market cycle, expectations escalate, and investor psychology solidifies. Individuals' confirmation bias tends to highlight only positive trends, making capital more accessible for investment in appreciating assets. Those who already own assets feel optimistic about the increasing values and are encouraged to purchase more. Conversely, individuals without assets may feel pressured by the continuous price surge and decide to start buying, succumbing to the market momentum. As prices soar, caution diminishes, and investors increasingly gravitate toward riskier assets, which may experience exponential growth.

The Top

At the cycle's peak, asset prices reach their zenith, resulting in diminished prospective returns due to the significant escalation in stock prices. Consequently, risk is at its highest point, despite prevailing euphoric market sentiment. It is a critical juncture for prudence, yet numerous investors, engrossed in the fervor, exhibit tunnel vision. Overcome by the prevailing exuberance, they often overlook the mounting risks and the necessity for caution.

As an aside, it's crucial to acknowledge that a market bubble often only becomes apparent after it bursts. Even with suspicions of a bubble, witnessing continued price increases can be frustrating, especially as others appear to profit substantially. This situation can challenge even the most disciplined investors.

From my perspective, a crash is a more more definitive signal then a bubble. A pronounced market decline, such as one ranging from 30-50%, will be widely agreed upon as a downswing towards a bottom. While the downswing may persist as the market searches for its lowest point, capitalizing on such downturns tends to tilt the odds in your favor. Remember risk is typically lowest and prospective returns are typically highest at these times.

Identifying the opportunity amidst widespread panic requires clarity and conviction, as this is when potential for substantial financial gain emerges. In today's era, where information is ubiquitous, maintaining a behavioral edge is perhaps the most significant advantage an individual investor can hold.

The Downswing

Economic fundamentals start to visibly weaken. As companies announce their quarterly results, many fail to meet expectations. The media amplifies a stream of negative news, leading the public to focus predominantly on unfavorable trends. The market begins to correct itself, moving away from recent excesses, prompting investors to offload their overvalued assets, which, in turn, triggers a decline in prices. This drop initiates a reverse fear of missing out (FOMO) scenario: investors observing diminishing returns in their 401(k)s feel compelled to sell to secure their dwindling gains, exacerbating the downward price trend. Those who have incurred losses face a tough decision: to realize these losses or to invest more in a declining market, still influenced by residual euphoria. As prices continue to fall, risk aversion intensifies, with risky assets increasingly perceived as surefire losses.

During the downturn, as economic conditions worsen and asset prices plummet, the urge to sell intensifies among investors, eager to stop the bleeding.

The Bottom

Asset prices are at or near a low point. Due to a significant price decline, the potential for returns is high, and the associated risk is reduced. However, many individuals remain fearful, projecting the recent downtrend into the future due to recency bias.

Knowing that markets are cyclical, not linear, you can gaze through the fog of fear to anticipate the next turn of the cycle. These are the moments to take the big swing. With a bit of luck and conviction, these can be moments of life changing wealth generation.

Eventually, when the market exhausts its pool of sellers, the dynamics begin to shift, signaling the pendulum's swing in the opposite direction as the cycle prepares to enter its next phase change. Keep in mind that at the start of the upswing, there is still widespread pessimism in the herd and an ongoing depressed outlook in the news.

The swings of the pendulum occur because there is a symmetry built into the mechanics of life. You see it in the physics of the world, how energy and mass are always conserved as objects interact. You can’t push on the ground without the Earth equally pushing back on you. You can’t stare into the abyss without it staring into you.

“No tree can grow to Heaven unless its roots reach down to Hell” - Carl Jung

Success always carries the seeds of failure and failure always carries the seeds of success. The wild flower is predestined to die in winter but it leaves behind the seeds of the next spring flower.

In psychology, success makes you vulnerable to failure through false confidence and failure sets you up for success through the lessons learned.

Success is not a constant because life is brutal not only at the bottom of the hierarchy but also at top. At the top, everyone is storming the castle seeking your head. You must constantly fight and win against the next best competitor. Enduring repeated and sustained offenses from the best is a impossible position to maintain. And so the seeds of failure are built into success and onwards the cycle turns.

It’s the story of Icarus crashing into the ocean on melted wings. It’s the Phoenix rising from the ashes. It’s Sisyphus, who finally pushes the boulder onto the top of the mountain only to see it roll back down again, repeated forever. It’s the story of Christ’s crucifixion and resurrection.

It’s the ancient concept of Yin-Yang.

Understanding how human psychology interacts with these cycles is a critical skill for any investor. When you anticipate what the herd and subsequently yourself, the single celled organism part of the super organism, will feel in the upswings and the downswings, it can be a bit easier to hold your ground in the storm. Losing your footing amidst turbulent conditions tends towards emotional capital allocation decisions forged in fear and greed. It risks dire financial consequences for you, or at worst, your family or friends.

Investing principles are life principles because it is ultimately on us to decide how to best allocate our scarce resources of time, effort, wealth and attention to achieve our aims.

There is always a tension between outperformance and resilience. It is very difficult to have both. You can drive a car at 130 MPH only by giving up steering and control. You cannot allocate your capital like a leveraged heat seeking missile and expect to have resilience in the crash.

Whether in investing or life, being aware of your position in the cycle to peek around corners will help in keeping composure when there is the inevitable turning of the pendulum.

Lastly, keep in mind that this is simple but not easy. There is a world of difference between looking at at a picture of a snake and having a live one unexpectedly thrown in your lap.

Remember your default programming is to run for your life.

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