Introduction

In recent decades, the proliferation of computational systems around the world has led to a vast increase in the information processing capacities of the planet. This form of planetary computation has revealed the Earth to itself, as in the case of climate change, a kind of planetary-scale evolution rendered visible only via simulations. It would be remiss to tie the emergence of computation to the emergence of computers, however. As biologist Michael Levin and others point out, computation is as old as life itself. Genes, proteins, cells all engage in the ongoing computing of information

. Planetary computation, thus, does not mark a radical break from the “natural” evolution of the world, but rather a continuation of the informatic evolution of the planet

.

The core role of information in the evolutionary history of Earth was famously posited in John Maynard Smith and Eörs Szathmáry’s seminal 1995 book The Major Transitions in Evolution

. For the authors, evolution has been characterized by a series of major transitions, each of which involved a fundamental change in both the unit of the individual (such as the evolution of multicellularity), and the information processing capacity of the system (such as the development of inheritable genetic code).

This theory framed evolution not as a continuous linear development, but rather as a series of discrete phase changes, each of which radically altered the possibility space for evolution to come

. While the first transition marks the shift from a “prebiotic soup” to protocells (also known as the “origin of life”), the authors present the most recent transition as the introduction of natural language, which enabled societies to pass information across much broader scales of space and time.

What if a new major transition was underway? The transition from natural to machinic language over the past century may mark a step change in complexity capable of re-imagining the evolutionary dynamics of the planet

. Just as planetary computation has disclosed its own impacts on the planet, might it also be capable of examining its own emergence as a process of life undergoing perpetual adaptation – a process that researchers call open-ended evolution

?

The Xenobiology Multiplex, or Xenoplex, sets out to explore these questions. This speculative experimental design leverages the most recent transition (planetary computation) in order to elucidate the first transition (origins of life). By simulating origins of life in a chemical-computational array, the project seeks ultimately to understand the mechanisms driving open-ended evolution on and of the planet. As the biosphere and technosphere increasingly constitute each other, an evolutionary theory that encompasses both biotic and abiotic systems is paramount. This project thus traces the evolution of evolution itself

, from biochemical origins to the computational present.

Experimental Design

The Xenoplex acts as an evolutionary time-compression device. Much like particle accelerators enabled the simulation of particles from the Big Bang, the Xenoplex enables us to run highly compressed micro-evolutionary histories in parallel.

The range of possible chemical constituents and temperatures from the “prebiotic soup” form the initial seed conditions for each box in a large array. Crucially, these represent not just the chemical conditions of early Hadean Earth, but also the biosignatures observed on exoplanets via new telescopes, such as the James Webb. This experiment allows us to examine universal principles of open-ended evolution across both origins of biotic life and astrobiology, paralleling attempts to create grand unified theories that accommodate both particle physics and astrophysics. This is crucial for exploring the vast space of counterfactual ‘tapes of life’

, beyond the perceptual doors of our version of evolution to experiment on unrealized biological trajectories. Going outside of our known story is the only way to survey the interplay of chance and necessity

.

This interplay is studied by computational means. Open-ended evolutionary algorithms are designed to explore the possibility space of environmental transformations that may have led to the origins of life. Chemical and temperature gradients are believed to form a crucial precondition; such disequilibria harbors the thermodynamic free energy required for self-organizing behavior to occur. Environmental complexity poses the first problem to solve for emerging life

. The solutions to this optimization problem for dissipating free energy gradients can be explored using parallelized gradient descent algorithms, allowing different parameterizations of the system to be rapidly searched and selected for in the arrays.

Rather than being a purely computational simulation, the Xenoplex empirically tests chemical environments. This avoids the dimensionality reduction of artificial chemistry simulations, and instead leverages the intrinsic reactivity, and creativity of chemical systems. This yields a form of recursive transfer learning, where chemical knowledge guides computational knowledge and vice-versa. This is crucial, as designed systems remain incapable of the ongoing open-ended evolution exhibited by natural and cultural systems. Solving this problem has long been a hallmark of Artificial Life (ALife), a broad field of study attempting to recreate lifelike processes using computational methods as simulations

. While an exact metric for measuring open-endedness remains elusive, generally such processes are characterized by the ongoing generation of (1) adaptive novelty, or (2) complexity.

If “life” were to emerge in the Xenoplex, how would we be able to recognize it as such? First, each reactor box must be carefully constructed such that the box itself interferes minimally with the simulated reactions. This self-contamination, or leakage of life, is epitomized by the iconic Miller-Urey experiments that studied the origins of life in the 1950s, where their use of borosilicate glassware inadvertently helped catalyze pre-biotic reactions

.

Second, the dynamics within each box must be quantified. Every reactor is connected to a mass spectrometer which samples the chemical space of each box. Fixed objective functions and equilibria are likely unrealistic, heuristic limitations that nature neither cares for nor obeys. Thus, the Xenoplex leverages a variety of metrics.

One possibility is the molecular assembly index, which was developed by astrobiologist Sara Walker with chemist Lee Cronin, as a measure of chemical complexity

. Derived from their concept of “assembly theory,” the molecular assembly index can be experimentally measured using conventional mass spectrometry, which produces chemical spectra where more peaks suggest more complexity and thereby more lifelike-processes.

Autocatalytic behavior (measured through copy number) and novelty (measured through diversity of chemical species) can also be measured, enabling a more open-ended evolution experiment to be designed with various nested goals that are dynamically adjusted. As these new specialized properties (e.g. self-replication) are acquired by populations of these boxes, the conditions of both the chemical gradient and computational gradient descent get propagated to nearby boxes, thus optimizing different properties in parallel.

Implications

The outcomes of the Xenoplex remain highly uncertain. However, five possible scenarios may emerge:

Scenario One: Null Result

A null result, where measures of lifelikeness plateau before self-replicating order emerges in any of the reactors. 

This implies the development of life requires deeper interactions with planetary processes, as microbiologist Lynn Margulis and chemist James Lovelock have argued in the Gaia hypothesis. Thus, life relies on tightly coupled feedback loops across multiple scales that are not easily reproduced in a lab

.

Scenario Two: Great Perceptual Filter

Life is observed only from prebiotic terrestrial simulations, but not exobiotic ones.

This could imply that life on Earth is universally unique, but a more compelling explanation is that the array still lacks the requisite technological sophistication for observing, simulating, or evolving non-canonical life forms. A great perceptual filter, as coined by Sara Walker, prevents the so-called “shadow biosphere” or xenosphere to be noticed

– akin to the invisibility of microbial life before microscopes were developed in the 1600s.

Scenario Three: Cosmoevolutionary Convergence

All of the successful boxes, including those with exoplanet initial conditions, are found to evolve some kind of biological life similar to Earth. 

This could illustrate cosmological-scale convergent evolution analogous to the terrestrial phenomenon of carcinisation where evolutionary trajectories often converge independently towards crab-like forms

. Alternatively, this scenario suggests theories of panspermia, where a common biotic ancestor “seeded” planets throughout the universe with life.

Scenario Four: Simulated Contact

A form of simulated contact in which life-like structures successfully evolve from experiments that are constrained by the exoplanet biosignatures.

This simulated contact may reveal forms of life that are entirely non-biotic – for example, convection cells that evolve the capability to detect, compute, and consume thermal information to replicate

. Such forms would likely require measurements of lifelikeness beyond chemical content for the algorithmic feedback loops; the emergence of this artificial tornado life would not be observed by a mass spectrometer.

This case might also represent a kind of xeno-xeno-life, where the lifeforms generated in the array are themselves a simulacrum constructed from putative biosignatures –  such that the alien life in the box no longer resembles those that actually exist on the exoplanet upon which it was modeled.

Scenario Five: Algorithmic Life

The most lifelike phenomenon that emerges is not found as a material substrate, but instead the algorithm itself that takes on a collective life of its own.

One of the hallmark goals of Artificial Life research is the discovery of the mechanisms driving open-ended evolution. By enabling various general characteristics of lifelikeness, such as novelty, complexity, and self-replication, to be selected in parallel, open-endedness might emerge through a kind of meta-learning process across all of the simulation boxes.

The discovery of such a mechanism would have deep ramifications for the development of artificial general intelligence as the next major evolutionary transition. Goal-oriented optimization and training tasks from machine learning are currently incapable of the exploratory dynamics we associate with evolution. A mechanistic understanding of such a process applied to neural networks would present a fundamental paradigm shift in how models train, learn, and replicate.

Regardless of the outcome, these simulations present an opportunity to decenter life away from a terrestrial, biocentric view. What is life if it is decoupled from the earth, or even from the realm of the biotic itself? Or conversely, what is life if it is so seamlessly integrated into its planetary realm that it is impossible to draw a separation between life and environment

? The Xenoplex does not promise a clean resolution, but rather further alienation. This is precisely the kind of otherworldly, uncomfortable zone that we must delve into for knowledge to expand itself.