The evolution of human knowledge can be intriguingly compared to the distinct phases of a chess game, a powerful metaphor that brings clarity to the grand arc of discovery across time.
In this view, the early game represents the momentous period of domain creation, when the fundamental building blocks of human understanding were first established. This phase was dynamic and expansive, akin to the opening moves in chess where new pieces enter the board, setting the stage for everything that follows.
During this time, humanity forged critical domains such as physics, mathematics, language, and agriculture, intellectual territories that would guide subsequent innovation, all without knowing it. The discovery of fire, for example, is the domain creation of physics.
Following this foundational period is the middle game, the era of established fields of study. Much like the intricate maneuvering and strategy of the middlegame in chess, this phase saw the domains interact, hybridize, and evolve into specialized disciplines such as medicine, law, and economics.
Here, discovery became more complex and nuanced, shifting from the creation of entirely new domains to the elaboration and deepening of knowledge within and between established fields.
While surprises and breakthroughs continued to emerge, the scope for radical new domains had largely diminished, and innovation unfolded within the constraints of the foundational structures laid down in the early game.
Finally, we arrive at the endgame, the post-slowdown phase that humanity currently inhabits. This stage is marked by a striking narrowing of possibilities, a slowing pace of discovery where remaining advances are harder fought, more subtle, and increasingly incremental.
Like the chess endgame, where each remaining move carries enormous weight but the options are few, this phase reflects a plateau in the accumulation of new knowledge. Most of the expansive combinatorial space of discovery has been explored, and the remaining 3 percent. According to the Discovery Plateau Hypothesis, the fraction of accessible knowledge is still within reach. However, as we try to make gains in that 3%, the discoveries we make become smaller and smaller, and slower and slower. That slowdown continues to get slower into infinity. And, there are always events that occur to knock us backward. For example, the burning of the Library of Alexandria would represent a setback to the accumulated knowledge of all of humanity if such an event took place today.
Central to this model is the concept of the Human Shannon Number, a theoretical ceiling that quantifies the universe of all possible collective mental states humanity could realize. This number defines the ultimate limit of human knowledge in information-theoretic terms.
However, most of this theoretical space remains inaccessible due to the immutable laws of physics and limitations of cognition. The practical consequences are profound: the vast majority of conceivable knowledge configurations lie beyond our reach, leaving only a fraction, represented by the remaining 3 percent, to be explored and understood.
This analogy elegantly synthesizes elements of game theory, information theory, and intellectual history into a cohesive narrative that explains both the historical trajectory and current challenges of human discovery. By framing our position as an “endgame,” it acknowledges the deceleration in innovation while grounding it in the realities of physical and cognitive constraints.
At the same time, it opens a door to the meaningful pursuit of the remaining knowledge accessible within these bounds, emphasizing the importance of synergy, applied domains, and the potential for synthetic or emergent fields to unlock new avenues of progress.
Ultimately, this perspective illuminates the grand chessboard on which humanity navigates discovery, offering both a realistic assessment of limits and a hopeful vision for continued intellectual advancement.
In trying to quantify novelty, I've decided to try to map knowledge domains throughout the time scale of human history (300,000 BCE to 2,025 CE).
All mega events would have to start in prehistoric times, going from 300,000 BCE, and the mega events era would need to end at the era where the first fields of study began.
From there, those mega-events would be extinct, because all discoveries leading up to the creation of domains would have been discovered.
These are the domains that formed the basis of the Proto-Origin, Paradigm Shift, and Post-Slowdown analysis.
Physical Domains:
Physics (fire, tools, mechanics)
Chemistry (plant medicine, fermentation, material transformation)
Astronomy (navigation, seasonal cycles, celestial patterns)
Life Domains:
4. Biology (agriculture, breeding, life cycles)
5. Medicine (healing, anatomy, pathology)
6. Psychology (understanding minds, emotions, behavior)
Abstract/Symbolic Domains:
7. Mathematics (quantity, space, pattern)
8. Language (symbolic communication, meaning)
9. Logic (reasoning, causation, inference)
Social Domains:
10. Politics (group organization, leadership, power)
11. Economics (trade, value, resource allocation)
12. Law (justice, rules, social order)
13. War/Strategy (conflict, tactics, competition)
Meaning-Making Domains:
14. Religion/Spirituality (transcendence, purpose, sacred)
15. Art/Aesthetics (beauty, expression, representation)
16. Ethics (right/wrong, moral reasoning)
Craft/Technical Domains:
17. Engineering (construction, mechanical advantage)
18. Agriculture (cultivation, domestication)
19. Architecture (buildings, design, infrastructure)
20. Textiles (fabric, weaving, clothing technology)
21. Metallurgy (metal extraction, shaping, tools)
22. Maritime/Naval Knowledge (navigation, shipbuilding)
23. Geology/Earth Science (landforms, resources, mining)
24. Meteorology/Climate Science (weather, climate observation)
25. Mythology & Storytelling (narratives, cultural memory, tradition)
The chart below showcases when proto-origins of domains began, what paradigm shifts these proto-origins led to, and the subsequent novelty slowdowns we end up with.
To quantify novelty and model the progression of human knowledge, I created a hierarchical scoring system for each domain and listed the logic below:
1. Developed Scoring System
Assigned Proto-Origin Score – marks the initial emergence of a domain.
Assigned First Paradigm Shift Score – measures early revolutionary breakthroughs.
Assigned Lineage Score – measures a domain’s influence on subsequent advancement.
Applied Synergy Multiplier to account for cross-domain interactions.
Calculated the Synergy-Adjusted Index, which feeds into the discovery model.
a. Proto-Origin Score
Represents the earliest emergence of a domain in human history.
Focuses on the foundational contributions that allowed further discoveries to occur.
Examples:
Physics: mastering fire and basic mechanics.
Mathematics: counting and intuitive spatial reasoning used in hunting.
Biology: early agriculture and domestication of animals.
Scored on a scale from 0–100, with higher scores indicating domains that appeared earlier and enabled multiple subsequent developments.
b. First Paradigm Shift Score
Captures the initial transformative breakthroughs within each domain that reshaped human society.
These are revolutionary leaps, not incremental improvements.
Examples:
Medicine: an organized understanding of anatomy, disease, and healing.
Engineering: creation of permanent infrastructure, irrigation, and monumental construction.
Metallurgy: extraction and shaping of metals for tools and weapons.
Scored 0–100 based on the magnitude of societal and cross-domain impact of the first paradigm shift.
c. Lineage Score
Measures a domain’s influence on subsequent discoveries and its historical longevity.
Accounts for how many other domains a discovery enabled or accelerated.
Examples:
Mathematics’ influence on physics, engineering, and economics.
Agriculture’s influence on medicine, social organization, and trade.
Higher scores indicate domains that have left a substantial chain of impact across multiple areas.
d. Synergy Multiplier
Recognizes that cross-domain interactions amplify discovery potential.
Adjusts each domain’s impact by considering its synergy with other domains.
Example: Engineering breakthroughs may be more impactful when combined with advances in Mathematics or Physics.
Multiplier typically ranges from 1.0–1.15, with 1.0 meaning minimal synergy and 1.15 representing strong cross-domain amplification.
e. Synergy-Adjusted Index
Integrates all previous scores into a single metric that reflects both intrinsic and relational novelty potential:
This index serves as α (intrinsic discovery capability) in Varney’s Law, directly feeding into the simulation of knowledge growth over time.
It allows the model to quantify both the starting potential of a domain and the amplification effects from interactions with other domains, producing a more realistic trajectory of cumulative human knowledge.
2. Integrated Varney’s Law
Mapped the Synergy-Adjusted Index and other scores to Varney’s Law:
α derived from Synergy-Adjusted Index.
S(t) and E(t) represent domain-specific search effort and exposure drag.
K_max represents the domain’s theoretical ceiling.
3. Simulated Knowledge Growth
Ran a numerical integration from 300,000 BCE to 3000 CE for each domain.
Generated Global_K (cumulative knowledge) over time.
Identified phases of discovery: proto-origin growth, paradigm shifts, and post-novelty slowdown.
Normalized K(t) for visualization and analysis.
4. Analyzed Results
Determined which domains drove early acceleration (Physics, Mathematics, Agriculture).
Highlighted domains responsible for paradigm shifts (Engineering, Medicine, Metallurgy).
Identified plateauing domains in the post-slowdown phase (Physics, Chemistry, Astronomy).
Predicted future discovery potential based on synergy and applied domains.
Scoring Human Knowledge Domains
Each domain was evaluated with three foundational scores:
Proto-Origin Score – Marks the earliest emergence of the domain. Example: Physics began with fire and basic mechanics; Mathematics emerged from intuitive counting in hunting and gathering.
First Paradigm Shift Score – Measures the magnitude of the domain’s early revolutionary breakthroughs. Example: Agriculture shifted humanity from a hunter-gatherer to an agrarian society.
Lineage Score – Captures the domain’s influence on subsequent human advancement. Example: Engineering and metallurgy facilitated complex construction, navigation, and technological systems.
These scores were then adjusted using synergy multipliers, producing a Synergy-Adjusted Index for each domain, reflecting both intrinsic discovery potential and cross-domain effects.
Scoring Highlights (Top Domains)
Varney’s Law and Discovery Dynamics
Using Varney’s Law:
K(t) is cumulative knowledge
α derived from Synergy-Adjusted Varney Index
S(t) and E(t) reflect domain-specific effort and exposure drag
K_max is the theoretical ceiling per domain
Each domain’s growth curve was computed, and Global_K is the sum across all domains.
Simulation: 300,000 BCE – 3000 CE
By integrating the scored domains over time:
Prehistoric Acceleration (-300,000 to -10,000 BCE): Early discoveries in Physics, Mathematics, Agriculture, and Biology drove rapid novelty. High Proto-Origin and Paradigm Shift scores pushed initial growth.
First Paradigm Shifts (-10,000 BCE to 0 CE): Domains like Engineering, Metallurgy, Architecture, Maritime Knowledge, Language, Religion/Spirituality became significant, reflecting strong lineage contributions.
Classical/Medieval (0–1500 CE): Growth decelerated; social, artistic, and ethical domains were more prominent, consistent with their synergy-adjusted scores.
Scientific Acceleration (1500–1950 CE): High Synergy-Adjusted Varney Index domains (Physics, Chemistry, Biology, Medicine) drove rapid novelty.
Post-Novelty Slowdown (1950–2025 CE): Most fundamental domains plateaued near K_max, but applied and synergistic domains sustained minor growth.
Humanity’s Discovery Plateau Position (2025 CE)
Global_K (sum of all domains) ≈ 24.3 / 25 → 97.2% of cumulative ceiling
Domains like Physics and Chemistry, despite high Proto-Origin scores, contribute little new discovery due to nearing their K_max.
Growth potential now relies on applied domains, cross-domain synergy, and new emergent fields.
Predictive Insights (2025–3000 CE)
The global knowledge curve plateaus; most Kuhnian-level paradigm shifts are complete.
Future novelty is driven by synergy and applied domains (Engineering, Medicine, Technology).
Radical domain emergence or synthetic knowledge creation is required to produce new paradigm-shift-level novelty.
Conclusion
Integrating domain scoring with Varney’s Law provides a quantitative framework for understanding the human discovery trajectory:
Proto-Origin scores explain early, rapid growth.
Paradigm Shift scores highlight transformative periods.
Lineage and synergy adjustments capture ongoing impact and cross-domain influence.
I still have to incorporate the Human Shannon Number if I’m going to run a more comprehensive simulation, but the multi-layered scoring system represents a significant leap forward in quantifying novelty.
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