While “the meaning of life” might be a tough personal or philosophical question, life itself also has a rather clear natural purpose. As humans, we are an extension of the biological life on this planet. In this article, I would like to elaborate what this purpose is, and what it means as a possible direction for our species. This is not necessarily related to the meaning of our personal lives, but if you, personally, are struggling with this question, this might also offer you a very general direction outside of religion or esoterics.
If you know how DNA works, and how life probably began, please feel free to skim through following paragraph and the entire “What happened” chapter.
Unfortunately, I have to begin with an obligatory disclaimer: Evolution is not “just another theory”. It is a theory backed by thousands of years of breeding experiments resulting in modern livestock and fruiting plants as we know them; with hundreds of years of those experiments well documented. It is backed by Mendel’s experiments on peas, and it is backed by modern genetics which allows you to find out your ancestry using an online service and a cotton swab. We understand rather well how DNA works, how protein synthesis works, how mutations happen, and so on, and so forth. We don’t have a complete picture, so we can’t predict precisely what tweaking one particular gene will do, but it is not because the theory is not sound — it is because we are still learning the rules, and because our genes are a work of a multi-billion-year long chain of accidents.
How did life happen?
We don’t know how exactly life arose on this planet, or where exactly. Some theories say, it was at the geothermal vents. Some place it into tidal pools. It seems to have happened exactly once, or the current genome/protein systems, ancestors of LUCA who lived 4.5 billion years ago, have out-competed every other version. Due to the amazingly long time that has passed since, we will probably never find out the exact details. But what we can say with confidence, is that at some point, a positive feedback loop happened: a molecule was able to shape another molecule in its own mirror image out of the building blocks in the soup around them. It was likely some early form of RNA. We know that the building blocks, the nucleobases, can arise naturally — we found them in metheorites, but also found the reactions that can spontaneously create them under the right conditions — conditions which were present on primordial Earth.
From here on, statistics took over. Two RNA strands are twice as likely to copy themselves as one, given enough resources. Then four, then eight. After 16 steps there were over 65 thousand copies, after step 20 — over a million. Some copies weren’t perfect, some fell back apart before copying themselves. Some had changes that made copying slower, some — faster. There is no will to this, simple math: if an RNA strand copies itself twice as fast, it will be ahead of the others by over sixty-five thousand copies in step 16, by four billion in step 32. Eventually, you run out of resources in the environment. The new building blocks come from RNA falling apart. RNA that is more stable or can grab the blocks up faster wins.
The next steps are complicated, but the principle is the same: the “best” apparatus for copying itself — its own information — wins. Best being, the best suited for the environment it is in, best suited for its role. In different niches, a different apparatus wins. Some niches change or disappear. The apparatus that was the best at surviving those changes won out. Everything else got fried, dried out, eaten, burned, drowned, frozen, or whatever cataclysm it had to deal with.
In the end, most RNA-based organisms switched over mostly to DNA, probably because it was more stable. This way of describing it, by the way, is just a shorthand. It looks as if it implies cause and effect — but no, it is still pure math. Some accident allowed a changed organism to happen, and it turned out beneficial. The new organisms out-competed old organisms. When a biologist says “it evolved, because…” , this is the process it implies — because the full explanation is simply too long to write down every single time we talk about a change.
What’s the point?
The — purely mathematical, as you have seen above — “point” of life is, to survive. For this, it needs to continuously optimize the process of information copying and adaptation. Whenever life stops doing this, it stops existing very shortly — it can not survive. There is no life without adaptation to the ever-changing niche. There is no life without being able to escape the old niche in favor of a new, when the old niche becomes uninhabitable. Whenever it optimizes itself, it copies faster, feeding the positive feedback loop.
But there is also something else. An optimization process is a learning process. You can see evolution itself as a slow and clumsy learning process, in hardware and by accident, with DNA as the learned information — learned, most truly, the hard way — the hardest way there is: everything that explored a particularly bad idea, has died. This is not the most efficient way to utilize the resources. And this is why many successful organisms on Earth have evolved numerous ways to learn faster. For example Epigenetics — “runtime”, temporary alterations to DNA that allow cells to switch functions. Another example are chemical traces that mark pathways most taken — these have evolved many times, in organisms as different as ants and slime molds. There is also habituation — learning to ignore a stimulus, evolved in animals, but also, again, in slime molds. All of those are mechanisms to help the organism learn without the need to die first. It is clear that learning is advantageous for what life does — which is, adapt, multiply, and occupy new niches.
The faster and more flexible the learning, the better the organisms are able to adjust to new niches. The flexibility comes from the ability to apply the learned information to a new situation —the ability to generalize, that we associate with higher intelligence. We grudgingly admire culture followers like raccoons, crows or rats for how well they can adjust from the wilderness to environments modified by humans. While other species are dying out due to our intrusion, the adaptable species are managing to be incredibly successful — annoyingly so.
The next step for this, is adjusting the environment to the species’ needs, or tool use. This, too, has evolved multiple times. We know it from primates, from some birds — and from the totally unrelated, but equally adaptable octopus.
One of the ways how we humans have become so incredibly successful, the ability to create our own environment, has to do with another aspect of learning: we don’t need to learn every new thing ourselves. We can learn it from our parents or members of the tribe, just like other primates. Just like them, a whole group can learn from one member of another group. But unlike our closest relatives, we can do more: thanks to books, we can also learn new behaviors and conclusions from somebody who has been dead for a thousand years. Thanks to the Internet, we can learn something from a researcher who has just discovered it on the other side of the world. With the scientific method, we can learn to distinguish fact and wishful thinking. Our technology allows us a faster learning and adaptation process.
What does it mean for us?
As we have seen above, the basic imperative for every living organism is to survive, whether by spreading into new ecological niches, or by adapting to the changed conditions, or both. As much as we like Earth, as much as we are adapted to it — like every planet, it is doomed: eventually, due to the inevitable changes in the Sun, our Earth will become too hot to survive. Some estimates give Earth another 300 million years of habitability, some assert that we can survive for longer with geo-engineering, and only when our Sun expands into a gas giant will the life on Earth cease. This is, if no asteroid hits us earlier, and no supervolcano ruins the Earths’ climate — things that, according to our understanding of the fossil record, have not just happened in the past, but have led to massive die-offs on Earth, where only the most adaptable and resilient creatures survived — or only those most adapted to the last habitable niche on the planet. The question is not if a disaster will hit Earth, but when. Sooner or later, all life on Earth will end.
As humans, we are the only species on this planet that is so adaptable that some of us can purposefully leave this planet — humanity can send out our seeds from the ecological niche we have almost filled, and bring other life with us. We can colonize the solar system and beyond. This is our biological purpose, as living beings. If we fail, life as evolved on Earth, life as we know it, will cease to exist. All the information that life on Earth has acquired in the last 4.5 billion years will be lost. Everything we learned and done will have been for nothing.
There are other ways of preventing it, of course. As we have seen, life is an evolution of knowledge — of information. We are on the brink of creating AI, machines that can learn and adapt just as we do, that could possibly simulate outcomes better than we do. Learning just by thinking, not by trying things out. If they prove to be more adaptable than us, maybe it will become their role to bring life to the stars, in form of evolving machines and information. A learning and evolution process continued by other means, not by the children of our bodies, but by the children of our minds. Combinations are possible. We could merge with the machines, either integrate them into us, or integrate our minds into them. These are thoughts for another story.
But whichever way it goes, life’s imperative is to adapt and survive, or it ceases to be life. We are life, children of Earth. We are the only life on Earth that can spread out into the universe, and bring pieces of Earth with us. Let’s do it.
For only we are Earthseed. And the Destiny of Earthseed is to take root among
the stars. — Octavia Butler, Parable of the Sower (1993)