INTRODUCTION
Change is the driving force behind everything—from the expansion of the universe to the evolution of life and the rise and fall of civilizations. It fuels both entropy, which pushes systems toward disorder, and evolution, which shapes complexity and adaptation. But is change simply a consequence of these forces, or is it the deeper, underlying principle guiding all transformation?
Understanding the dynamic interplay between change, entropy, and evolution reveals the hidden patterns that shape our world from biology and technology to law and society. Entropy (disorder) and complexity (organized structure) may seem like opposites, but they often coexist in dynamic systems. Complexity emerges from change, but without constant energy or adaptation, entropy eventually dominates. In this posting we explore these relationships across living systems, artificial intelligence, quantum computing, business, legal systems, and libraries.
A WORKING DEFINITION FOR FUNDAMENTAL CHANGE
For years I have been searching for a definition which encapsulates the universal, and, as it turns out a deeply fundamental, phenomenon we commonly refer to as change. Finally, I think I may have found it, thanks to a lecture I listened to recently by the physicist and philosopher Sean Carroll. In the lecture Professor Carroll discussed various concepts including entropy and evolution as they evolved after the big bang but I realized the subtext of his message was change.
What then is a working definition of change when viewed from this perspective? After reviewing a variety of related sources and consulting with others, I have arrived at the following which I have been told accurately represents change as discussed in this posting.
Change is the fundamental driving force behind all transformation, supported by energy, that has shaped entropy and evolution from the beginning to the present day. It governs the continuous alteration of systems—whether physical, biological, or social—leading to shifts in structure, function, and complexity over time.
Change occurs when energy facilitates interactions or transformations within or between elements of nature. Since the beginning, energy-driven change has influenced both entropy, which increases disorder, and biological evolution, which shapes complexity through adaptation and selection. Because of this linkage, change often involves an element of risk, as its outcomes can be unpredictable or disruptive. While not a universal or absolute rule, many natural and social systems exhibit a general tendency for complexity to increase over time as a result of change, though this process is neither linear nor inevitable
What are Entropy and Evolution?
- Entropy (Thermodynamics): Entropy, a measure of disorder in a system, naturally increases over time according to the Second Law of Thermodynamics. Change is inherent to this process, as systems evolve toward greater entropy unless energy is introduced to maintain order.
- Evolution (Biology): Biological evolution is driven by change—genetic mutations, environmental shifts, and natural selection all contribute to the adaptation and diversification of species. Evolution depends on variation and change in organisms over generations.
In both cases, change supported by energy is a fundamental force. However, while entropy leads to disorder, evolution often produces complex and ordered structures in living systems. Life counteracts entropy locally by using energy, though the overall entropy of the universe still increases.
Thus, while change drives both entropy and evolution, they operate under different principles—one tending toward disorder (entropy), the other toward adaptation and complexity (evolution).
CHANGE AS A DRIVER OF ENTROPY
Entropy is a measure of disorder or randomness in a system, and change is what drives entropy forward. The Second Law of Thermodynamics states that in a closed system, entropy always increases over time, meaning things naturally move from order to disorder unless energy is added to maintain structure.
To understand how change drives entropy, let’s break it down into key principles with examples.
1. Entropy and Change, The Fundamental Relationship
- Entropy increases when things change from an organized state to a more disordered state.
- The more possible ways a system can be arranged, the higher its entropy.
- Change, whether spontaneous or forced, leads to more possible arrangements, which means more entropy.
Example: Ice Melting
- Initial State: Ice cube (solid, structured, low entropy).
- Change: Heat energy is added.
- Final State: Water (liquid, molecules move freely, higher entropy).
- The system moves toward greater disorder because molecules have more freedom to spread out.
Example: A Sandcastle Eroding
- Initial State: A carefully built sandcastle (structured, low entropy).
- Change: Wind and waves break it down.
- Final State: A random pile of sand (disordered, high entropy).
- The external force (wind, water) increases entropy by disrupting the organized structure.
2. Time and Irreversibility: Why Entropy Increases
- The Arrow of Time: Time moves forward because entropy increases.
- Once a system undergoes a change that increases disorder, it does not spontaneously return to order.
- You can’t unmix coffee and milk once they blend together—this is entropy-driven change.
Example: Breaking an Egg
- Before breaking: The egg is structured (low entropy).
- After breaking: The yolk and white spread out (higher entropy).
- Why it’s irreversible: The molecules have more possible arrangements and don’t naturally go back to the original order.
3. Energy and Entropy: How Change Propels Disorder
- Change occurs when energy is added or removed from a system.
- Higher energy states allow particles to move more freely, leading to more possible arrangements (higher entropy).
Example: Burning a Piece of Paper
- Before burning: The paper is intact (low entropy).
- Change: Fire adds energy.
- After burning: The paper turns into ash, smoke, and heat (higher entropy).
- The system has transformed into many smaller, more randomly distributed components.
4. Entropy in the Universe: Change as the Ultimate Driver
- The universe started in a low-entropy, highly ordered state (the Big Bang).
- Over time, stars form, burn fuel, explode, and distribute matter, increasing entropy.
- The expansion of the universe itself is an entropic process—galaxies spread apart, increasing disorder.
Example: A Star’s Life Cycle
- A star forms (low entropy).
- It burns fuel, creating heat and radiation (change increases entropy).
- It explodes as a supernova, scattering elements into space (high entropy).
- New stars and planets form from this dust—temporarily lowering entropy in local regions, but the overall entropy of the universe still rises.
5. Can Entropy Decrease? Yes, But It Requires Work
- Entropy naturally increases, but external energy input can reverse local entropy.
- Life itself is an example—organisms use energy (from the Sun or food) to maintain order.
- However, this requires continuous energy input—without it, entropy takes over.
Example: Cleaning a Messy Room
- If you don’t clean your room, entropy increases (it naturally becomes messier).
- You can reverse the entropy by putting things back in place, but that requires energy (your effort).
- Over time, without maintenance, disorder will return.
COMPLEXITY IN RELATION TO CHANGE OVER TIME
Complexity in relation to change over time is a fascinating topic because it intersects with both entropy (thermodynamics) and evolution (biology), but in different ways.
- Entropy and Complexity: The Paradox
- The Second Law of Thermodynamics states that entropy (disorder) tends to increase in a closed system.
- However, complexity can emerge in open systems where energy flows in from an external source (e.g., the Sun for Earth, or food for living organisms).
- This is why, despite the universe tending toward disorder, localized complexity can increase—for example, in living organisms, ecosystems, and even human societies.
- Evolution and Increasing Complexity
- Over evolutionary time, biological systems have become more complex, not because evolution has a goal, but because complex adaptations can provide survival advantages in certain environments.
- Early life forms were relatively simple, but natural selection has driven the emergence of multicellular life, specialized organs, intelligence, and social structures.
- However, evolution does not always favor complexity—sometimes, simpler forms are more efficient (e.g., bacteria are highly successful despite their simplicity).
- Complexity in Human Systems and Technology
- In human societies, change over time has generally led to increasing complexity in technology, governance, and knowledge systems.
- The evolution of language, laws, economies, and artificial intelligence are examples of increasing complexity.
- But complexity can also lead to fragility—highly complex systems (e.g., financial markets, ecosystems) can collapse if their interdependencies become too rigid or unstable.
Conclusion: Change as a Driver of Complexity
- Change is a fundamental force behind both entropy (which increases disorder overall) and evolution (which can increase complexity locally).
- Complexity emerges when energy flows sustain order, and evolution or self-organization refines structures over time.
- However, complexity is not inevitable—it can grow, stagnate, or collapse depending on the system’s conditions.
ENTROPY AND COMPLEXITY AS RELATED TO CHANGE: A MULTI-DOMAIN EXPLORATION.
Entropy (disorder) and complexity (organized structure) may seem like opposites, but they often coexist in dynamic systems. Complexity emerges from change, but without constant energy or adaptation, entropy eventually dominates. Below, I’ll explore this relationship across living systems, artificial intelligence, quantum computing, business, legal systems, and libraries.
- Living Systems: Entropy vs. Complexity in Biology
How Life Fights Entropy
- Living organisms constantly use energy to maintain complexity.
- Without energy (food, sunlight), biological systems break down into entropy (death, decay).
Example: Human Body and Aging
- Your body is an ordered system, but entropy increases over time.
- Cellular aging (entropy) occurs due to DNA damage, inefficient repair, and metabolic waste.
- Complexity in life (evolution, adaptation) emerges as life uses energy to counteract entropy.
Example: Ecosystems as Self-Organizing Complexity
- An ecosystem is a complex adaptive system where species interact dynamically.
- Change (e.g., climate shifts, species extinction) can increase entropy (ecosystem collapse) or lead to new complexity (new species dominance).
- Human impact often accelerates entropy, reducing biodiversity and increasing ecological disorder.
- Artificial Intelligence: Complexity from Information, Entropy in Errors
How AI Systems Build Complexity
- AI learns patterns from data, increasing structured knowledge (complexity).
- Neural networks evolve, reducing entropy by turning random data into predictions.
Example: Machine Learning Models
- A well-trained AI model reduces informational entropy—it makes sense of chaotic data.
- However, without proper training, AI models suffer from noise, bias, and overfitting, increasing entropy (errors, unpredictability).
Entropy in AI Failures
- AI models degrade over time if they don’t adapt to new data (concept drift).
- Example: Spam filters—if not updated, they become less effective as scammers evolve, increasing entropy in security.
- Quantum Computing: Harnessing Entropy for Complexity
How Quantum Systems Relate to Entropy
- Classical computing follows strict rules, but quantum computing works with probabilities and uncertainty (higher entropy).
- Quantum mechanics allows superposition (a bit being both 0 and 1), which increases computational complexity.
Example: Quantum Entanglement Reducing Entropy
- When two particles become entangled, knowing one instantly reveals the state of the other—reducing uncertainty (entropy).
- This allows quantum computers to process complex calculations efficiently compared to traditional systems.
Entropy as a Challenge in Quantum Systems
- Quantum systems are highly unstable—tiny environmental changes (heat, vibrations) increase entropy, causing decoherence (loss of quantum information).
- Researchers develop error correction methods to fight entropy and maintain quantum complexity.
- Business: Managing Complexity While Avoiding Entropic Collapse
How Companies Grow Complexity
- Businesses start simple, then scale by adding products, divisions, and global operations.
- Change (market shifts, innovation) forces businesses to adapt, increasing complexity.
Example: Amazon’s Expansion
- Amazon grew from an online bookstore to a highly complex AI-driven logistics empire.
- Complexity led to efficiency and innovation, but also fragility—small disruptions (supply chain issues) cause cascading failures (entropy).
Entropy in Business Failure
- Corporate bureaucracy and inefficiency are forms of increasing entropy.
- Kodak’s collapse—failure to adapt to digital photography increased entropy, leading to decline.
- Legal Systems: Balancing Order and Entropy Through Change
How Legal Systems Manage Complexity
- Legal systems evolve to create order (reduce entropy) in society’s interactions.
- More laws = more complexity, but also a higher risk of legal entropy (uncertainty, loopholes).
Example: U.S. Constitution’s Adaptability
- The U.S. Constitution is a complex but flexible system—amendments allow adaptation.
- However, legal complexity can lead to entropy (gridlock, conflicting rulings).
Entropy in Legal Challenges
- Too many regulations can create contradictions and inefficiencies, increasing entropy.
- Example: Tax laws—so complex that even experts struggle, creating legal entropy (uncertainty in compliance).Libraries: Fighting Informational Entropy While Enabling Complexity
How Libraries Organize Complexity
- Libraries store vast amounts of knowledge, making complex information manageable.
- Cataloging systems (Dewey Decimal, Library of Congress) reduce informational entropy.
Example: Digital vs. Physical Libraries
- Physical libraries require maintenance; books decay (entropy).
- Digital libraries store vast knowledge but face entropy in the form of outdated links, lost data, or misinformation.
Entropy in the Digital Age
- The internet is a high-entropy system—billions of pages, but much is misinformation.
- Libraries act as entropy reducers, curating reliable information in a chaotic digital world.
FINAL SYNTHESIS: ENTROPY AND COMPLEXITY IN A CHANGING WORLD.
- Living systems fight entropy with energy, but age and decay are inevitable.
- AI builds complexity, but without adaptation it becomes entropic (outdated, biased).
- Quantum computing thrives on entropy but must control it to function.
- Businesses expand complexity but risk entropy through inefficiency and disruption.
- Legal systems aim to create order but can become entropic due to excessive complexity.
- Libraries manage complexity by structuring knowledge, but digital entropy remains a challenge.
CONCLUDING STATEMENT: ENTROPY, COMPLEXITY AND THE DYNAMICS OF CHANGE.
Change is the fundamental driver of both entropy and complexity, shaping the evolution of systems across nature, technology, business, law, and knowledge. In living systems, change fosters adaptation and growth, yet entropy inevitably leads to aging and decay. In artificial intelligence, change allows systems to learn and evolve, but without continuous refinement, entropy manifests as errors and obsolescence. Quantum computing thrives on uncertainty and probability, leveraging entropy while struggling to contain its disruptive effects. Businesses and economies grow in complexity through innovation and expansion, but unchecked entropy—whether through inefficiency, market disruption, or bureaucratic stagnation—can lead to collapse. Legal systems strive to impose order and structure on society, yet excessive complexity can introduce contradictions and entropy in governance. Meanwhile, libraries and information systems function as vital organizers of human knowledge, counteracting digital entropy by curating reliable information in an ever-expanding sea of data.
Ultimately, change fuels the constant tension between order and disorder, innovation and decay, adaptation and collapse. Systems that endure are those that not only embrace complexity but also develop mechanisms to mitigate entropy—whether through learning, adaptation, resilience, or external energy input. In an era of accelerating technological and societal transformation, the ability to balance complexity with stability and harness change rather than succumb to entropy will define the future of intelligence, governance, and human progress.