Life began when algorithms took control

Second of two parts (read Part 1)

It’s no wonder that scientists haven’t been able to solve the mystery of the origin of life. They don’t know what the solution would look like if they found it.

Any proposal for how life originated faces the inconvenient annoyance that life has evaded all attempts to precisely define it. Consequently it’s pretty hard to say exactly how it started.

“Without a definition for life, the problem of how life began is not well posed,” write physicists/astrobiologists Sara Imari Walker and Paul Davies of Arizona State University.

Presumably, life originated with the arrival of some particularly complicated chemistry. Various nonliving molecules somehow accumulated in a way that initiated metabolism, reproduction and eventually evolution. So searchers for life’s origins have focused on finding out what those molecules were and how they worked. But it’s important, Walker and Davies point out, to narrow that focus to the right aspect of molecular activity.

“A common source of confusion stems from the fact that molecules play three distinct roles: structural, informational and chemical,” the scientists write in a paper published last year in the Journal of the Royal Society Interface.

It’s the informational role that is the key to transforming nonliving chemistry into life, they contend. “The manner in which information flows through and between cells and sub-cellular structures is quite unlike anything else observed in nature. If life is more than just complex chemistry, its unique informational management properties may be the crucial indicator of this distinction.”

Specifically, Walker and Davies argue that life’s origin involved the separation of information processing from information storage. Metabolism is itself a sort of information processing — input information is “processed” via chemical reactions into output products, just as a computer program converts input data into output. But chemical reactions happening on their own do not in themselves constitute life. It’s the origin of the computer program — the stored information controlling what happens — that marks life’s beginnings.

“Living and nonliving matter differ fundamentally in the way information is organized and flows through the system: biological systems are distinctive because information manipulates the matter it is instantiated in,” Walker and Davies assert. Information’s control over the matter containing it — what Walker and Davies call “context-dependent causation” — is therefore life’s defining feature. “The origin of life may thus be identified when information gains top-down causal efficacy over the matter that instantiates it.”

In other words, when the information stored in molecules begins telling the molecules what to do, chemistry becomes life.

Walker and Davies refer to this transformation as an “algorithmic takeover.” Chemical reactions such as those of metabolism process analog information — the information is represented in the actual molecules physically performing the processes. Life’s computer program is stored digitally, in DNA. (Too bad it is not short for digital nucleic acid.) DNA’s information is processed algorithmically, by the reading of codes contained in the arrangement of molecules that are distinct from the molecules that participate in the actual metabolism.

This digitally stored information contains not only the blueprint for making the organism, but also the instructions for constructing the organism from the blueprint. These instructions, the algorithm, control the chemistry. So algorithmic takeover is the hallmark of life’s origin. It marks a sharp transition between life and nonlife, framing the origin of life question more precisely.

“The real challenge of life’s origin is thus to explain how instructional information control systems emerge naturally and spontaneously from mere molecular dynamics,” Walker and Davies write.

Perhaps, they acknowledge, some sort of “analog” life could exist, but it would be at a serious disadvantage once “information control” assumed command in a competing chemical system. A digital algorithmic system would be better able to cope with changing environments thanks to “the physical separation of information and its material representation.”

“Therefore, life forms that ‘go digital’ may be the only systems that survive in the long run and are thus the only remaining product of the processes that led to life,” Walker and Davies speculate.

A key feature of biological information in algorithmic life is feedback from the environment. That means the algorithmic rules can change over time, “in a manner that is both a function of the current state and the history of the organism,” Walker and Davies write. Understanding how the rules change could have implications for evolution. It’s possible, for instance, that evolution’s complexity could be represented by processes described by algorithmic systems known as cellular automata, as Walker, Davies and other collaborators explore in a recent paper (see Part 1).

In any case, viewing life as a computational process addresses some old controversies about life in new ways. In particular, it demolishes the old argument that life is too complex to have originated without a designer. Whereas in fact, algorithmic systems such as cellular automata show that systems of vast complexity can emerge from simple rules operating on initially simple systems, as Stephen Wolfram emphasized in his book A New Kind of Science in 2002.

So with algorithms and digital information, complexity is the natural expectation. You need a designer only if you want to keep things simple.

Follow me on Twitter: @tom_siegfried

Tom Siegfried is a contributing correspondent. He was editor in chief of Science News from 2007 to 2012 and managing editor from 2014 to 2017.

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