Once a certain complexity was reached, the emergence of life itself might have been rapid, explosive, and almost inevitable. Candidate life-forms, emerging into a mode of effective learning, would have carried an overwhelming advantage over their simpler, less flexible rivals. These thoroughbred proto-life knowledge trackers would have been able to adapt, becoming ruthless at exploiting available resources and forcing all the more stable, less flexible alternatives to turn to dust.
Reaching such thresholds, and shifting into higher gear as a result of them, also happens in other contexts. For roughly 99.5 percent of the time that humans have existed, for instance, little scientific progress was made. But over the past four hundred years, with aids such as the printing press, education, and a critical mass of people seriously interested in science, actively discussing theories, and recording evidence, collective human learning—and scientific discovery—have dramatically increased.
WETWARE
At some point, in small, simple steps, basic proto-life objects probably evolved into early life-forms made up of RNA, which is a close cousin of DNA. Compared to any natural non-life alternative we know of, RNA is an exceptionally efficient and flexible information carrier.
How does RNA achieve this? Like DNA, RNA is a long string of connected components (known as bases) of four different flavors, or letters. A “triplet” sequence of three letters is an important combination—it is the way that RNA letters spell words—in DNA/RNA language, all words are three letters long. Each word represents one of the twenty or so amino acids, which are cellular building materials whose combinations form proteins. And proteins are essential for almost all functions of every cell of any organism on the planet. A whole sentence of a sequence of amino-acid-denoting words is needed to instruct the cell to make a specific protein. A whole sentence is also exactly what a gene is.
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Compared to those primitive pre-life copiers, which could represent limited information within their simple molecular structures, RNA can instantiate many times more ideas. It does this by building multiple protein molecules—potentially thousands within a cell. And each protein could be a far more complex chemical construction than would ever be possible in a simple non-life copying object.
We are now dealing with a system capable of enormous complexity and flexibility, even if any change in implicit ideas can largely only arise from the random changes of the RNA code in future generations. Before, it might have appeared a stretch to discuss simple replicating non-life chemicals as representing ideas about the environment, because the information would be so minimal and so closely locked into the shape and chemical properties of the object (although this immature information-carrying capacity was still the critical feature that evolution acted upon to move from non-life to life). But now it should become clear that an RNA-based life-form, with its special code of letters, like the 0’s and 1’s on a desktop computer, and its software programs for making proteins, is carefully shaped by evolution largely as an information-storage device. There is also a vast potential for adaptation across the generations as evolution tweaks the sequence of letters in order to update the successful traits recorded in RNA—killing off those creatures with letters that do not capture the world well, and nurturing those with letters that reveal the best ideas. In this way, the genes are not only storing information, but, if viewed over many generations, also blindly learning about how best to live in the world.
But while RNA is a mammoth step toward life compared with simple replicating chemical objects, it has various drawbacks. As a molecule, RNA is unstable and tends to degrade relatively easily. This is no problem for a short piece of information, which can be replicated quickly, but for anything longer, with many thousands of letters of information, it simply isn’t practical. The longer sequence of information would deteriorate so quickly that the organism would have little chance of passing on to the next generation those useful qualities that natural selection bred into it.
In other words, if you want to increase your information capacity, RNA is not your molecule of choice. It simply doesn’t scale up well: The more information it stores, the less information it can successfully pass on to the next generation. Any useful balance between stability (maintaining a belief) and chaos (creatively exploring new ideas—some good, some bad) will slide disastrously toward the chaotic side, and all beneficial concepts accumulated in that family of RNA life-forms will eventually be lost, inevitably along with the life-forms themselves.
DNA solves this problem. Bacteria, arguably the first real life-form, may seem to us exceedingly simple. However, even the smallest, most basic bacterium requires a DNA string of more than 100,000 letters of code in order to form the recipe of its biological makeup. DNA, despite requiring considerably more energy to copy, is vastly more stable than RNA, which means that far fewer mistakes appear when it is duplicated. For these reasons, there may well have been a strong evolutionary pressure for life to start using DNA as the primary storage molecule for information (with RNA now playing an intermediary role between DNA and protein). So DNA may have arisen relatively easily and early, especially since it is extremely similar in structure to RNA—the main difference being that DNA is made up of pairs of letters in a double strand, rather than the single strand of RNA.
I can now return to the issue of the extent of complexity and adaptability in a concrete way, asking these questions for life rather than for some simpler non-life alternative. When compared to the 3 billion letters of code in the human genome (the entire complement of genes in an organism), the 100,000 letters in a bacterium is tiny. Nevertheless, it is sufficient in principle to generate vastly more possibilities of different types of proteins than there are atoms in the universe. In fact, to exceed the number of atoms in the universe, 10
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, you only need a few hundred DNA letters. So bacteria can, in principle, be reprogrammed to do almost anything you can conceive of. For instance, biotechnology engineers are currently creating novel forms of bacteria to make diesel fuel as a waste product.
A UNIVERSAL RECIPE AND A UNIVERSAL LANGUAGE
We have now arrived at the common blueprint for all life on the planet: DNA stores the instructions for the organism’s structure and function, and RNA, having made a temporary copy of sections of this DNA code, in turn converts this information into many different types of proteins—and proteins are the key molecular tools of all organisms. This model must have been a wild success when it first occurred, by its dominance wiping out all the alternatives. Scientists believe this is the case because virtually all life that we know of, from the simplest bacteria to all the animals, including ourselves, shares exactly this process, and exactly the same language.
This universality of DNA is completely staggering. I recently stayed in a hotel on the east coast of Italy, in a village called Vasto, where I was forced to communicate with the local staff in a combination of incredibly meager Italian and awkward hand-gestures. It wasn’t so bad, as I know a smattering of Spanish and French, and we all fumbled our way through conversations. All these languages are relatively similar to each other anyway. After all, we live on the same continent and are—of course—the same species. And yet, it’s entirely understandable that the differences in our histories and culture, stretching back a couple of millennia, would have created changes sufficiently deep that most of the words in Italian sound and look at least somewhat different from English.
But the contrast between European languages and the language of genes couldn’t be more extreme. Our evolutionary path diverged from bacteria a billion years ago.
Nevertheless
, the meanings of virtually every single one of the sixty-four possible words (these triplets of bases that code for amino acids) are identical between us. So throughout the biological world, it’s not just that there is only one universal language, but that there is a single dialect of a single accent within this single language!
There are many practical examples of the extent of this staggering uniformity. For instance, scientists have countless times successfully spliced genes from one species into a completely different one and changed its characteristics. This includes human genes introduced into mice, and mouse genes into flies. You might think that such gene swaps are unnatural, the Frankenstein-like artifacts of biology labs. This couldn’t be further from the truth. For instance, in the wild it is now assumed that about 13 percent of all plant species were formed by the melding together of two or more distinct lineages. And there are also well-documented examples of useful gene swaps between humans and viruses or bacteria.
Part of the reason for the rapid rise of this DNA-RNA-protein system, and its consequent total dominance, may well be the fact that it is very close to an ideal biological system for storing and processing information. DNA is a tremendously safe, reliable holder for vast numbers of genetic ideas, while the machinery in the cell can efficiently retrieve those ideas and express them as proteins. There is also a simple way of making copies of the entire organism: by unzipping the twin strands of DNA code, each strand making a single copy of itself, and then rejoining these into two double strands for the new cells.
With this ideal ability to store information and easily convert it into useful protein tools, the standard DNA-based mechanism we know today must have trounced the alternatives 4 billion years ago, and once this recipe for life took hold in the world, there was no going back.
EXTRA INNOVATION IN DESPERATE TIMES
Now, though, with DNA-based life carefully designed to preserve large sets of ideas, it seems the scales have been aggressively tipped toward the boring, stable side of information processing, with little chance to adapt the DNA code when circumstances change.
To compound this problem, there are various biological mechanisms that make every effort to ensure that organisms avoid the chaotic route. For instance, the DNA words that code for individual amino acids can sometimes still be read correctly, even if they are slightly misspelled, because there are in many cases a few spelling variations for each word. There are also more active and sophisticated mechanisms in play in some organisms by which a careful proofreading of the code is done to detect and correct any errors as they arise.
But to even the score against DNA inflexibility, there is a second set of biological tricks. For example, whole sections of DNA can be mixed up to inject measured levels of chaos into the ordered DNA code, allowing a family of organisms over the generations to soak up new ideas.
Some fixed, equal balance between stability and chaos is an effective learning system: Now you can both maintain your DNA ideas and modify the code across the generations, so that new concepts can be gleaned from the world. But never deviating from this informational midpoint introduces its own inefficient, unintelligent stubbornness. In one extreme, possibly applying to a handful of bacterial species on the planet, if you are living relatively easily in a place that never changes over the millennia, with no enemies to speak of, then doing everything you can to keep your current successful ideas
just as they are
across the generations makes perfect sense. At the other end of the spectrum, if a species’ genetic set of ideas are obviously unsuccessful, and many creatures are dying in droves, possibly because of a violently changing environment or many forms of competitors, then a mode of maximal innovation is the only likely road to safety. This is true despite the fact that the chaotic route itself will also introduce poor ideas that lead to even more deaths, since as long as new accurate genetic ideas are found, some members of the species will definitely be saved. In both cases, the middle ground is far from ideal.
In the usual niches that life inhabits, there is a mixture of good times and bad. Here, the ideal computational solution is to be able to tweak the ratio between existing beliefs and new ideas according to the circumstances. So, ideally, an organism should suppress any chaotic changes to its DNA in successful times, but then positively encourage such dangerous innovations when previous beliefs no longer work in a new, life-threatening world.
In a close analogy to this, the distinction between heavily grooved beliefs and innovation is one of the most prominent psychological features of human experience. We all have habits we’ve carried out a thousand times before, such as having that morning shower. I for one tend to spend the vast majority of each shower daydreaming, as my muscles unconsciously take over the tedious task of sponging myself clean. But if the water would suddenly turn stone cold, I’d come back to myself, know that something is wrong, and explore how to fix the faulty plumbing. This acknowledgment that an error has crept in, and that innovation is required to fix it, makes me feel more conscious, more energized, and certainly cuts out any daydreaming. In fact, it’s no coincidence that moments like these initiate a spike in my awareness. I will elaborate throughout this book that this drive to innovate your way out of a problem is a crucial feature of consciousness, whereas, in contrast, an important role of unconscious, habitual plans is to implement those fully learned products of the initially conscious innovations.
Although simpler DNA-based life, such as bacteria, do not have any form of consciousness by which to modify their levels of innovation from dogmatic autopilot to desperate creativity, they nevertheless have an impressive suite of mechanisms by which to slide the level of creativity back and forth as they track the level of dangers in the environment. This provides striking evidence that sophisticated learning strategies, mirroring those that distinguish between conscious and unconscious thoughts, occur even at the humble level of single-celled organisms.