2.1 Planetary intelligence and autopoiesis
The Infinity Mirror project aims to illustrate the role of simulation as a fundamental aspect of intelligence – to chronicle its artificialization and emergence out of human behaviors in technical form, expanded and ultimately integrated at planetary scale. Indeed it was through simulation in the form of global climate models that enabled us to foresee the crisis looming from the 1970s forwards. Likewise there can be no response to climate change and other existential threats that does not include expanded and improved models of the Earth’s coupled systems as a mechanism through which to recognize and halt emerging threats.
An influential paper published in the International Journal of Astrobiology works on the assumption that intelligence is not a property of individuals as conventionally understood, but derives from collective behavior in the biosphere – not something that happens on a planet but to a planet. The authors go on to define planetary intelligence as “the acquisition and application of collective knowledge, operating at a planetary scale, which is integrated into the function of coupled planetary systems.”5 Regardless of whether this takes place within biospheres or technospheres – without simulation, this would be impossible.
It was the Russian-Ukrainian mineralogist Vladimir Vernadsky who first argued that the sum total of biological activity on Earth should be considered a geological force with the power to change systems to it was inextricably coupled: the hydrosphere, cryosphere, lithosphere, and atmosphere. Later on, Vernadsky added another system – that of “cultural biogeochemical energy” – with equivalent power to make changes at planetary scale.
Vernadsky adopted the moniker of “noosphere” from the French Jesuit priest Pierre Teilhard de Chardin to mean the sum total of collective cognition. The idea incorporated both pre- and post-technological information processing meaning it would include everything from organizational interactions between social insects to beavers constructing dams, news updates spreading across social graphs to artificial neural networks.
In their paper, authors Frank, Grinspoon and Walker adapt five possible properties required for a world to show cognitive activity operative across planetary scales. The last of these is autopoiesis – meaning “self-making” of “self-producing” – referring to a system’s capacity to establish “organizational closure” and maintain itself despite fluctuations and perturbations.6 They emphasize that “life is a process of maintaining an identity from within but that this unity is never static. The organism must “operationally reconstitute itself. It must continually create the conditions for its own existence via metabolism. If the dynamic falters or stops, the organism dies.”
2.2 Major transitions
Here it might be useful to schematize the distinction between collective processes in the biosphere capable of exerting force on coupled planetary systems and anthropogenic forcing as a result of burning hydrocarbons or the more general capacity of humans to act collectively and engineer their environment.
The biosphere represents a complex network of feedback loops which uses signals such as incoming sunlight or the abundance of a specific element to modulate behaviors, curbing effects in service to a steady state. This learned behavior is dependent on “knowledge” born from many millions of years of trial and error – an evolutionary dynamic that contains and predates biotic life.
In a 2018 paper, astrophysicist Adam Frank and colleagues proposed five classes of planet according to the degree of thermodynamic complexity exhibited in their coupled systems.7
Moving up the scale from I to IV, the energy available to do work increases with the addition of an atmosphere, and subsequent “thin” and “thick” biospheres, as disequilibrium between coupled systems rises. A speculative class V planet would be one which contains a technological civilization that has entered into a stable relationship with the other coupled systems of their host world, acting with intention to maintain and develop the biosphere from which it emerged and on which it depends for its continued existence.
Along with NASA astrobiologist David Grinspoon and theoretical physicist-turned-biologist Sara Walker, Frank refers to this as the transition from an immature technosphere to a mature technosphere, incorporating feedback loops and reducing forcing timescales much in the way that Earth did when it transitioned from being an immature biosphere during the Archean (with insufficient feedbacks between life and geophysical coupled systems to exert strong co-evolution) to the Proterozoic, when the biosphere began to exert strong forcing on the planet’s geophysical state establishing full co-evolution of the entire system.8
According to geologist Peter Haff, technospheres refer to the activities of civilizational intelligence, the technological corona that metabolizes fossil fuels and includes “communication, transportation, bureaucratic and other systems”.9 On a planet with an immature technosphere this activity will shift coupled planetary systems into new dynamical states with no capacity to regulate them and guarantee the health of the civilization building the technology. By comparison, a planet with a mature technosphere contains feedback loops intentionally modified to ensure maximum stability and productivity of the full system.
A mature biosphere is more stable than an immature technosphere, yet only a mature technosphere can extend itself in time enough to become significant to the search for extraterrestrial intelligence. So-called contact inequality, whereby the probability of contact is proportional to the age of the intelligence being detected, makes it likely that exo-civilizations will be older than those carrying out the search. As such there may be generic features in the evolution of intelligence relevant to astrobiology and SETI. When we use “long-term” in this context, we do not mean a geological era such as the Anthropocene, but “a new eon, which could continue for hundreds of millions of years or more.”
2.3 How Earth becomes Class V
The arrival of a civilization capable of guaranteeing its own continuation in this way is clear evidence for the existence of planetary intelligence. There was some evidence that by the dawn of the 21st century, Earth was already well on its way. For example, the coordinated global response to chlorofluorocarbon uses (CFCs) in the 1990s, or the growth of planetary asteroid defense systems (of which the DART deflection in 2022 was an example) might be ranked alongside nuclear arms treaties, vaccine development and adaptation to natural disasters as examples of nascent planetary intelligence responding in tandem with emerging threats whether generated internally or coming from without.
The response to anthropogenic climate change needed to be radically quicker than, say, Earth’s recovery from an ice house condition as a result of microorganisms evolving to process trapped carbon and release it. Aside from future scenarios proposed by science-fiction, some of the best models for network-environment regulation were to be found in other evolved systems – including the human brain.
Simulations are vital to processing semantic information as it flows across the planet’s geosphere, biosphere and technosphere.10 Much like the information networks of our own minds they are sites of active inference in which new knowledge is assimilated and made accessible for utilization as a constantly shifting array of predictions.
2.4 3-D Prediction Engines
The human brain constructs an incredibly complex model of the world. This model is the basis for all of our predictions, perceptions and actions. When attempting risky maneuvers in a flight simulator, for example, a pilot creates new connections in their neocortex, a frame of reference they can call upon should they ever need it in the future.
Our brains calculate the relative position of our bodies in their environment, but also the relative positions of other objects to each other, all of which is constantly on the move. A similarly spatialized process is at work for higher order concepts such as democracy, space flight or envy making thought a kind of movement. In each case, our world model (our expectations about the world) is the basis for planning. Comparison with sensory data upgrades the model.
Predictive coding in neuroscience maintains that the reality we experience is built from mental models that we update when our best guesses miss the mark. This is why in fMRI scans, unexpected inputs lead to much higher rates of brain activity. Regardless of whether the scale is personal or planetary: planning is an attempt to resolve ambiguities about the future and minimize errors. The two are fundamentally linked. As cognitive philosopher Andy Clark has argued: “Minds are not merely what brains do. They are what brains create – distributed cognitive engines spanning brain, body, and world.”11
The basis for predictive coding emerges in the microcircuitry of cortical columns: the 2.5 cubic millimeter cylinders which comprise the neocortex, the most recently evolved, outer layer of the mammalian brain folded up inside the skull like a napkin in a wine glass. The columns consist of groups of neurons. Of the many billions in each human brain, just two percent are active at once. This two percent is everything you think and perceive.
Cells within columns are networked vertically, up and down, but also at great distance across the brain or down the spinal column across the nervous system. Crucially, cortical columns appear to operate the same regardless of which region (visual, touch) they are found – constituting a universal modeling toolkit (for language, music, mathematics) that creates predictions. When a pattern of activity is recognized, dendrite spikes raise the voltage in the cell putting it into a predictive state. This is before the cell spikes – ensuring that the predictions we make are not experienced as hallucinations.
Although the precise evolutionary story of the neocortex remains the subject of some debate, one theory argues it emerged from an increase in map-creating neurons from the much older hippocampus and entorhinal cortex in mammalian brains. These structures contain “grid cells” whose activity seeks to mirror minute details of their environment. In studies of rats moving through a maze, brain activity remained similar so long as they took the same route. When a new journey opened up, a new pattern of activity (a new reference frame) was created, like arriving in a new city or entering an unfamiliar house.12
2.5 Map makers
In A Thousand Brains: A New Theory of Intelligence (2021) , neuroscientist (and co-inventor of the Palm Pilot ) Jeff Hawkins argues “it is as if nature stripped down the hippocampus and entorhinal cortex to a minimal form, made tens of thousands of copies, and arranged them side by side in cortical columns.” To become an expert in any domain requires the creation of a highly detailed mental map. Within that map – or simulation – are many more simulations that we open a little like hyperlinks on the web.
Cortical columns enact a sensory-motor process according to the region through which sense data arrives – but knowledge of objects is distributed by its relationship to other reference frames much as neurons use many synapses and a network of neurons is never dependent on a single cell. Strokes can knock out multiple cortical columns and the brain will continue to function because it is a complex adaptive system. This is similar to how Frank and colleagues argue planetary intelligence will be collective due to the way intelligence appears as a feature in eusocial species like ants, termites, or humans on Earth.
There is a limit to the number of objects a single column can learn but across the vast network of axons and synaptic terminals the number becomes exponentially larger. Hawkins’ proposal for how we alight upon a single perception from the many ghost simulations contained within our brains is a process of voting. “Using its long-range connections,” he writes, “a column broadcasts what it thinks it is observing. Often a column will be uncertain, in which case its neurons will send multiple possibilities at the same time. Simultaneously, the column receives projections from other columns representing their guesses. The most common guesses suppress the least common ones until the entire network settles on one answer.”
Given that 90 percent of the neocortex – traditionally considered the seat of intelligence – is given over to maintaining sub-perceptual processes like breathing or digestion, it may be that intelligence is better understood as predictive monitoring and self-maintenance, making the convention focus on “problem solving” an extension of this process. Much as a child learns a model of the world – its possible threats and sources of nourishment – and their place within it, the planet’s Anthropocene-era technosphere built thousands of spatialized models in the form of computer simulations. And just as it is for children, the ability to build those models emerged in the twin arenas of competition and play.