Kurtis Kemple

Information Physics: How Human Systems Exhibit Physics-Like Patterns

July 16th, 2025

Human societies consistently create systems that exhibit remarkably physics-like patterns. This phenomenon appears across all civilizations, time periods, and scales - from ancient calendar systems to modern organizational structures. These patterns emerge because humans naturally organize information systems using optimization principles they understand from physics—concepts like entropy, energy flow, and structural stability.

Information physics is the principle that humans organize information systems using patterns they understand from physics, leading to consistent optimization approaches across cultures and time periods.

Historical Information Systems

The convergent evolution of human systems across isolated civilizations reveals consistent optimization patterns in information organization. Every society, regardless of location or era, developed remarkably similar solutions to information challenges - suggesting underlying principles that transcend culture.

Calendar systems

Every civilization independently developed calendar systems tracking the same celestial phenomena. Despite no communication between ancient Egypt, Maya, and China, all created ~365-day solar years and lunar month divisions. These weren’t arbitrary choices but optimization toward efficient information structures for encoding temporal cycles within human memory constraints.

The universal convergence on hierarchical calendar structures reveals a deeper pattern, calendars are literally information pyramids:

  • 1 year cycle: sits at the apex, maximum compression containing all temporal information in a single unit
  • 4 seasons: forms the middle layer, medium compression providing cognitively manageable chunks for agricultural planning
  • ~365 days: creates the base, minimal compression offering maximum granularity for daily activities

This pyramid topology isn’t coincidental, it mirrors the exact same information density distribution found in modern organizational structures. Ancient brains, with far less cognitive processing power than modern ones, needed optimal compression algorithms for temporal data. The calendars that survived were those achieving maximum compression while remaining usable by pre-literate humans.

The constraints were severe: encode a year’s worth of temporal patterns into memorable chunks without writing systems to offload memory, while maintaining agricultural accuracy. Too complex and people couldn’t track it. Too simple and it wouldn’t capture essential seasonal information. The hierarchical structure (Year → Seasons → Days) emerged as the optimal solution across all civilizations - not through cultural exchange, but by hitting the same cognitive optimization limits.

Architectural information

Pyramid structures appeared independently in Egypt, Mesopotamia, Mesoamerica, and Asia. Far beyond mere physical stability, these monumental structures represent an astonishingly sophisticated form of information compression and durable storage, serving as the ancient world’s premier “hard drives” for critical societal data. Given the available technology and resources of the time, they were the optimal solution for encoding and transmitting high-value information across vast distances and millennia.

The sheer scale and deliberate design of pyramids allowed them to:

  • Compress multi-layered information: They simultaneously encoded complex data about power structures (pharaohs, gods), cosmological beliefs, advanced engineering knowledge, and the organized capacity of the state into their very form. This allowed for the long-term persistence of vital societal “data.”

  • Act as location anchors (information compression for navigation): Their immense visibility, especially when originally clad in gleaming materials, transformed them into unambiguous navigational beacons. The complex information of “how to get here” was compressed into a simple, universal instruction: “Go to the bright, monumental light.” This drastically reduced friction for orientation and travel across large, undifferentiated landscapes.

  • Combat information entropy: In an era without widespread literacy or digital replication, the physical durability of stone was the most effective means to resist the natural decay and loss of information over time. They were built to endure, ensuring their embedded messages persisted across countless generations.

Thus, the pyramid’s form, arising convergently across disconnected civilizations, highlights a consistent optimization in information systems: the urgent need for durable, broadcastable, and highly compressed information solutions when technological constraints limit other options.

Writing evolution

All writing systems evolved from pictographic to abstract linear forms following consistent optimization principles. Constraints of hand movement combined with cognitive processing limits drove universal simplification patterns. Each civilization independently discovered that linear sequences achieve efficient information encoding.

Language as information optimization

Human languages demonstrate consistent optimization patterns across all cultures and time periods. Every language independently evolves toward approximately 40 phonemes - reflecting optimization for human vocal and auditory channels. Most frequent words become shortest following Zipf’s Law of information compression. All languages develop subject-verb-object patterns that create efficient information hierarchies. Modern languages show accelerating optimization:

  • Text abbreviations maximize information per character
  • Emojis provide parallel emotional information channels
  • Code-switching matches information topology to social networks
  • Programming languages achieve zero-ambiguity information transfer

The universal speech rate of ~39 bits per second across all human languages reveals consistent constraints of information processing in biological systems.

Currency as information

Money evolution follows consistent optimization patterns - from commodity items (shells, grain) → precious metals → abstract tokens → digital representations. Each transition reduced information friction while maintaining value fidelity. The progression represents systematic optimization in value transfer systems.

These historical patterns suggest that humans consistently organize information systems using similar optimization principles they understand from physics - a pattern too consistent to be mere coincidence.

Modern Information Flow Dynamics

Contemporary organizations exhibit similar optimization patterns to historical systems, now accelerated by digital communication and global connectivity. Modern systems make these patterns more visible and measurable.

Organizational topology

Hierarchies universally emerge as efficient information structures - decisions concentrate where information density is highest, execution distributes where bandwidth is greatest. Information moves through hierarchical structures following predictable paths that resemble water flowing downhill, pooling at decision points, and cascading through implementation layers—though unlike water, information lacks mass and follows gradients of bandwidth and attention rather than gravity.

Network crystallization

Social networks grow following percolation-like patterns - nodes connect when information value exceeds connection cost, forming clusters at critical thresholds. LinkedIn, Facebook, and professional networks demonstrate phase transitions from isolated nodes to giant connected components at predictable densities.

Market information dynamics

Financial markets exhibit patterns reminiscent of physical systems:

  • Bubbles form when information feedback loops create runaway cycles
  • Crashes cascade like avalanches when information symmetry suddenly breaks
  • “Liquidity” describes information flow between value containers
  • Equilibrium represents stable information configuration

These patterns suggest that markets aren’t just economic systems but information processing networks that naturally optimize toward efficient price discovery and resource allocation.

Innovation diffusion

Ideas propagate through organizations following predictable patterns - high-energy early adopters transfer information along paths of least resistance. “Viral” spread occurs when information packets achieve optimal size and structure for network transmission.

Modern organizations appear to succeed or fail based on how well they align with these optimization patterns - suggesting these represent consistent approaches to organizing information systems rather than just useful metaphors.

Digital Systems and Information Optimization

Contemporary technology strips away physical constraints to reveal pure information dynamics. Digital systems demonstrate consistent optimization patterns without material limitations.

Artificial intelligence architecture

Neural networks represent information processing topologies that optimize through training. Training optimizes information pathways, memory stores information states, attention mechanisms manage information bandwidth. AI development follows information theory principles because intelligence itself involves information processing optimization.

Distributed computing

Terms like data lakes, pipelines, and flows are helpful metaphors reflecting measurable properties (bandwidth, throughput), but should not be mistaken as literal fluid dynamics. Information, though measurable, remains fundamentally different from physical fluids.

System resilience patterns

Modern systems implement optimization-based safeguards that mirror biological and physical resilience mechanisms. These aren’t arbitrary design choices but reflect deeper patterns of how stable systems maintain function under stress:

  • Circuit breakers prevent information cascade failures
  • Load balancers distribute information processing
  • Redundancy maintains information integrity
  • Caching reduces information retrieval overhead

Digital systems reveal what might be information optimization in its purest form - patterns so consistent they suggest underlying principles we’re only beginning to understand.

Working With vs Against Information Patterns

Civilizational progress comes from working with deeper optimization principles, while civilizational failures come from attempting to ignore fundamental constraints. This distinction separates sustainable innovation from inevitable collapse.

Successful Pattern Application

These innovations succeed by applying sophisticated principles to transcend surface constraints:

  • Compression algorithms: Reduce information size without losing content
  • Encryption: Increase information entropy deliberately for security
  • Parallel processing: Multiply information throughput via topology
  • Quantum computing: Exploit superposition for information density

Each breakthrough applies deeper principles rather than ignoring existing constraints.

Failed Pattern Violations

These systems fail by attempting to ignore information constraints entirely:

  • Infinite growth economics: Ignores conservation of information/energy
  • Perpetual engagement platforms: Ignores attention processing limits
  • Centralized everything: Fights natural information distribution patterns
  • 24/7 availability: Ignores that all systems need maintenance to clear accumulated overhead

The pattern seems clear: systems can transcend immediate constraints through clever application of deeper principles, but apparently cannot ignore fundamental constraints without eventual collapse.

Digital Native Information Topologies

A fundamental shift emerges between minds shaped by hierarchical information structures and those native to graph-based information networks. This isn’t generational preference but adaptation to different information physics environments.

Traditional hierarchical thinkers process information in tree structures - linear paths, clear dependencies, sequential processing. Digital natives process information in graph structures - multiple simultaneous paths, web dependencies, parallel processing. Neither is superior; they’re optimized for different information topologies.

What organizations pathologize as “attention deficit” often indicates minds optimized for high-connectivity information environments. These individuals track multiple information streams simultaneously, maintaining awareness of edge relationships that hierarchical processing might miss. They struggle in linear systems not from deficiency but from topology mismatch.

This divergence will intensify as information environments become increasingly graph-structured while many organizations maintain hierarchical topologies.

Measuring Information Patterns

The true power of recognizing these patterns lies in applying established scientific measurements to human systems. These aren’t just analogies but actual information theory principles we can measure and use for prediction in real-world systems:

  • Shannon entropy in organizations: Every Slack workspace, email system, and communication platform exhibits measurable information entropy. High-performing teams maintain low entropy through clear channels, consistent terminology, and structured workflows. When entropy rises - mixed messages, unclear responsibilities, communication breakdown - teams fail predictably. Communication platform success correlates with tools that reduce information entropy for specific organizational needs.

  • Percolation thresholds in markets: Social networks undergo phase transitions at critical connection densities, exactly like percolation in physics. LinkedIn demonstrated this when it hit critical mass - suddenly everyone needed to be there because everyone was there. The same threshold dynamics explain why some products explode virally while others grow linearly. WhatsApp reached 1 billion users by hitting percolation threshold after percolation threshold in local markets.

  • Metcalfe’s Law in platform economics: Network value increases with n² connections, explaining why winner-take-all dynamics dominate digital platforms. Facebook’s $1 trillion valuation isn’t from features but from 3 billion users creating n² possible connections. This same law explains why enterprise software companies desperately add collaboration features - they’re trying to create network effects where none naturally exist.

  • Dunbar’s number in organizational design: Human cognitive limits create hard constraints on information processing - we can only maintain ~150 stable social connections. Companies that structure around this limit (like Gore-Tex’s 150-person factory rule) show higher innovation and lower coordination costs. When organizations exceed these natural information processing limits without proper structure, communication breaks down predictably.

  • Power laws in everything: City sizes, company valuations, wealth distribution, and social media engagement all follow power law distributions because information accumulation creates preferential attachment. The biggest cities get bigger, the richest get richer, the most viral content gets more viral - not through conspiracy but through information physics. Amazon’s dominance isn’t strategy alone; it’s information physics creating inevitable concentration.

  • Information velocity in competitive advantage: Organizations that increase information velocity - faster decision loops, quicker customer feedback, rapid deployment cycles - consistently outcompete slower rivals. Amazon’s two-pizza teams, Spotify’s squads, and startup success rates all correlate with measured information velocity. The US military’s OODA loop concept (Observe, Orient, Decide, Act) is literally information velocity optimization for warfare.

These measurements appear to work because they tap into consistent optimization patterns, not just helpful metaphors. When organizations measure Shannon entropy in communication systems or track percolation dynamics in markets, they seem to be applying the same principles that govern efficient information systems.

Implications for Human Systems

Understanding these information optimization patterns offers powerful insights for designing, managing, and predicting human systems. Several compelling observations emerge from this framework.

First, convergent evolution across cultures likely occurs because optimal information structures appear to be determined by consistent constraints, not culture. Similar problems seem to require similar information topologies regardless of who solves them.

Second, system failures become more predictable when viewing them through constraint violations. Just as engineers can calculate when a bridge might collapse under load, organizations might be able to anticipate when systems will collapse under information strain.

Third, sustainable systems appear to respect natural cycles - processing and rest, gathering and distribution, growth and consolidation. Systems claiming exemption from these cycles tend to exhaust their information processing capacity.

Finally, the future may belong to those who engineer systems aligned with these apparent optimization patterns rather than fighting them.

Conclusion: Information Patterns as Natural Principles

The most compelling validation of these information optimization patterns comes from examining system failures across all scales. Just as perpetual motion machines fail because they violate thermodynamics, human systems consistently fail when they violate what appear to be fundamental information constraints.

When companies promise infinite growth, they seem to be claiming information can expand without energy input. When platforms demand constant engagement, they appear to deny information processing fatigue. When economies assume eternal acceleration, they’re essentially proposing perpetual motion for information systems. Each violation tends to meet the same inevitable end: system collapse when capacity depletes.

This pattern goes beyond mere metaphor - it appears measurably consistent. Organizational burnout follows predictable information overload curves. Market crashes exhibit information cascade dynamics that can be modeled and often anticipated. The same optimization patterns that shaped ancient calendar design and modern AI architecture may be expressions of consistent underlying principles.

Whether calculating moon phases or training neural networks, the patterns remain strikingly similar. Humans consistently organize information systems using familiar optimization principles - patterns that transcend individual intentions or organizational charts because they reflect how we naturally think about efficient systems.

In building systems, perhaps the wisest approach is recognizing these patterns exist. Information physics may not be literal physics, but it represents consistent human approaches to organizing information systems using principles we understand from the physical world. Organizations can work with these patterns to build resilient, sustainable, innovative systems. Or they can ignore how humans naturally organize information and risk watching their systems consume themselves trying to achieve impossible optimization.

The choice exists, but the patterns persist regardless.