The Unseen Thread Connecting Life, Technology, and Information
What if Darwin's theory of evolution was just one piece of a much larger puzzle? What if the same principles that explain how finches adapted their beaks on the Galapagos Islands also govern how artificial intelligence improves itself and how cultural trends spread virally?
This isn't science fiction—it's the groundbreaking perspective of Panevolutionary Theory (or 'Pan-Evo'), a revolutionary framework proposing that biological and non-biological information undergo similar evolutionary processes.
Recent developments in artificial intelligence have forced scientists to confront fundamental questions: Will AI help or harm humanity? Is biology separate from information? Pan-Evo suggests these are the wrong questions because biology and information are not truly distinct2 .
Life itself is an ordered form that reproduces with variation, and any ordered arrangement—biological or not—potentially contains information. This theory proposes that biological and non-biological information are components of a unified process that has been operating since before biology existed2 .
As one researcher puts it, "Integrated thinking about technological and biological evolution might lead to better developments"2 —possibly minimizing harm from both human error and failed AI systems. This article explores how Panevolutionary Theory is reshaping our understanding of everything from the origin of life to our technological future.
Panevolutionary Theory proposes that all information systems—whether biological, cultural, or technological—share four fundamental operations2 :
The introduction of new variations in information systems, analogous to genetic mutations in biological evolution.
The copying or spreading of information across systems, similar to genetic inheritance or cultural transmission.
Selection and refinement based on environmental fit, where better-adapted information persists and spreads.
Physical or conceptual spread across domains, enabling information to reach new environments and systems.
These processes operate simultaneously across multiple levels, from molecules to individuals, populations, species, and even ecosystems2 . The theory dramatically expands what qualifies as an "evolutionary system," suggesting that the same principles describe both the evolution of biological species and the development of human culture and technology.
Some versions of Panevolutionary Theory identify distinct evolutionary epochs that have emerged throughout cosmic history4 :
| Epoch | Medium | Description | Examples |
|---|---|---|---|
| Phusitic Evolution | Inorganic compounds | Emergence of life through dynamics of inorganic compounds | Prebiotic chemistry, self-organizing matter |
| Zoetic Evolution | Genetic & molecular biological processes | Propagation of life through genetic and epigenetic processes | DNA-based life, biological speciation |
| Noetic Evolution | Knowledge systems | Systems where knowledge itself directs processes required for existence | Artificial intelligence, human culture, technology |
The foundational epoch where inorganic compounds self-organized into increasingly complex structures, setting the stage for life's emergence. This represents the physical basis of all subsequent evolutionary processes.
The biological epoch characterized by DNA-based life forms undergoing Darwinian evolution through genetic variation, inheritance, and natural selection. This epoch dominated Earth's history for billions of years.
The current epoch where knowledge systems themselves evolve and direct change. This includes human culture, technology, and artificial intelligence, where information guides its own replication and transformation.
This framework resolves paradoxes that traditional Neo-Darwinian evolution struggles to explain, particularly human behaviors that defy standard evolutionary precepts of survival and propagation4 . Why would humans make decisions that reduce reproductive success? Why do we develop technologies that could potentially destroy us? Pan-Evo suggests these make sense when understood as examples of Noetic evolution, where knowledge systems follow their own evolutionary pathways.
At the heart of Panevolutionary Theory lies a radical blurring of the distinction between information and life. The theory builds on a simple but profound definition: life is "the ability to use energy and materials to create and maintain some ordered form that can reproduce itself with variation"2 .
The revolutionary insight is that many non-living systems also fit this description. Autocatalytic chemicals (which speed up their own production), viruses, and self-replicating software all exhibit life-like properties according to this definition2 . This challenges our fundamental categories of what qualifies as "living."
Panevolutionary Theory draws heavily on information theory, particularly concepts of entropy and order. Any ordered arrangement—whether biological or not—can potentially contain information2 . Consider these four sequences of letters, each with different entropy (disorder) measurements2 :
Entropy = zero
Entropy = 0.69
Entropy = 2.11
Entropy = 2.11
The first sequence has minimal potential for information, while the last actually conveys meaning to English speakers—but only because there's a recipient (a person who understands English) capable of interpreting it2 . This illustrates a core principle: informativeness depends on both the ordered arrangement and the availability of a system that can interpret it. In Panevolutionary terms, both biological and non-biological information require appropriate "recipients" to have meaning or evolutionary impact.
To understand how Panevolutionary principles operate in practice, let's examine a revealing experiment that bridges biological and information processing systems. Researchers investigating the "Frog-in-the-Pan" (FIP) phenomenon—where people notice abrupt changes but miss gradual ones—developed a cognitive-evolutionary model based on surprise emotion5 .
The researchers recruited 109 participants to complete a prediction task under different conditions5 . The experiment was designed as follows:
The reinforcement learning (RL) model was used to calculate learning rates, which quantify how much weight people give to new information when updating their beliefs5 .
The findings demonstrated that surprise functions as an evolutionary adaptation for efficient information processing:
| Condition | Average Learning Rate | Surprise Elicitation | Belief Updating |
|---|---|---|---|
| Gradual Change | Low | Minimal | Slow, incremental adjustments |
| Abrupt Change | High | Significant | Rapid, significant belief revision |
Visual representation of surprise response in gradual vs. abrupt change conditions
When changes were gradual, participants made small prediction errors that failed to trigger surprise, resulting in low learning rates and minimal belief updating. However, when changes were abrupt, the significant prediction errors triggered surprise emotion, causing learning rates to soar and driving substantial belief revision5 .
This experiment provides a microcosm of evolutionary principles operating in information processing systems. Surprise functions as a selection mechanism that determines which environmental changes warrant cognitive resources and adaptation—paralleling how natural selection operates on biological traits.
One of the most provocative applications of Panevolutionary Theory is the concept of "Panspeciation"—the extension of biological speciation to non-biological information systems2 . The theory suggests that as artificial intelligence develops, humans and AI might undergo a speciation-like event, diverging into vastly different environments that suit their respective strengths2 .
Digital environments, data processing tasks, computational problem-solving, and automated systems management.
Creative endeavors, emotional intelligence, physical interaction, ethical decision-making, and cultural development.
This wouldn't necessarily be the hostile takeover scenario often depicted in science fiction. If both humans and AI behave intelligently, they might naturally occupy different niches, much like how similar species partition resources in ecological systems2 . This could represent the first major speciation event involving humans in thousands of years.
| Concept/Tool | Function | Application in Pan-Evo |
|---|---|---|
| Assembly Theory | Measures complexity via assembly index | Quantifies evolutionary development across biological and non-biological entities2 |
| Reinforcement Learning Models | Algorithms that quantify learning from new information | Measures adaptation processes in biological and artificial systems5 |
| Shannon Entropy | Measures information potential in ordered systems | Quantifies information content across different media2 |
| Cognitive-Evolutionary Framework | Models surprise and belief updating | Explains adaptation mechanisms across living and informational systems5 |
| Neutral Theory | Null hypothesis of non-adaptive evolution | Counterbalances pan-adaptationist assumptions |
Panevolutionary Theory represents more than an academic curiosity—it provides crucial insights for navigating our rapidly changing technological landscape. By recognizing that AI systems undergo evolutionary processes similar to biological systems, we might better anticipate their development and potential impacts2 .
Explains human behaviors that contradict standard Darwinian logic, such as reduced reproduction and self-harming technological development4 .
Demonstrated that cultural and socioeconomic factors often outweigh biological ones in determining survival during COVID-193 .
Suggests harm from AI might be minimal if humans and machines occupy different environmental niches2 .
The theory also helps resolve longstanding conflicts in evolutionary biology. For decades, scientists have noted that human behavior often contradicts Darwinian logic4 . Why do humans choose to have fewer children despite reproductive success being the cornerstone of biological evolution? Why do we engage in behaviors that harm our survival prospects? Pan-Evo suggests that humans have increasingly transitioned into the Noetic evolutionary epoch, where knowledge systems, rather than pure genetic inheritance, drive our development3 4 .
This perspective has gained urgency during events like the COVID-19 pandemic, which demonstrated that cultural and socioeconomic factors often outweigh biological ones in determining survival3 . Access to resources, healthcare systems, and information networks proved more decisive than genetic fitness in many cases—a phenomenon difficult to explain through traditional Darwinian frameworks but perfectly coherent within Panevolutionary Theory.
As we stand at the threshold of unprecedented technological evolution, Panevolutionary Theory offers both a warning and a promise. It suggests that harm to biology from AI might be minimal if humans and machines occupy different environmental niches2 . But realizing this potential requires that "humans learn to evaluate information and cooperate better to minimise both human stupidity and artificial simulated stupidity (ASS—a failure of AI)"2 .
The theory ultimately presents a unified vision of reality, where biological, cultural, and technological evolution represent different manifestations of the same fundamental processes. In this view, the development of AI isn't an alien invasion of the natural world but rather the latest development in a continuous evolutionary process that began with the first self-replicating molecules. Understanding these connections may be crucial for navigating the challenges ahead and steering evolution in beneficial directions for both biology and technology.
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