The Ravenous Brain: How the New Science of Consciousness Explains Our Insatiable Search for Meaning (9 page)

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Authors: Daniel Bor

BOOK: The Ravenous Brain: How the New Science of Consciousness Explains Our Insatiable Search for Meaning
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A more surprising notion is that all life is itself an implicit scientific enterprise, albeit one that cares only for information relevant to survival and reproduction, rather than anything whatsoever that is intriguing about the wider universe.
Nature resembles science closely in its catalog of successes and failures to such an extent that, just as the first lesson in science is failure, so one could easily claim that the first lesson in nature is also failure. Of all the species that have ever existed, only about one in a thousand survive today. But much more than this, the whole mechanism for specifying the recipe for life is honed from natural experimentation to creatively store and refine a set of working hypotheses about the world.
The main thesis of this book is that consciousness simply is a certain kind of processing of information, especially information that is useful, that captures some pattern to the world. This chapter will provide the context to this argument: Consciousness didn’t pop mysteriously out of the biological ether. Instead, it evolved, like almost everything else in nature, in an incremental way, and is intimately linked to the universal blind biological enterprise of accurately capturing useful ideas. Consequently, almost all features of evolutionary “learning” are mirrored in the computational details of the brain, and of the landscape of our conscious minds.
THE ESSENCE OF EVOLUTION
 
The standard theory of evolution is beautiful in its simplicity: Over billions of years, from a single common ancestor, there arose all the millions of wildly differing life-forms that ever existed and that populate the earth today. Such variety occurs partly because there are limited resources, and creatures need to compete to grab the choicest morsels. Some organisms consume others, so competition can deteriorate into vicious battles, both within and between species. The traits that keep an organism alive and help it to breed will flourish, whereas features that hamper survival and successful reproduction will, over the generations, slowly disappear from the population. It is this shifting of traits within a population and across the generations that eventually creates new species.
These traits are mainly determined by genes, individual instructions in the recipe for how to make an organism. A creature’s genes are copied to its offspring, which will therefore closely resemble its parent. But these recipe instructions can sometimes by chance get misspelled, potentially creating a new variety of traits with each successive generation. These misspellings are not like typos in books, which are always wrong. Instead, misspellings, or mutations, in the genetic code will sometimes be beneficial. And if sexual reproduction is involved, rather than simple self-replication, the resemblance across generations will be far from perfect, injecting even greater fluidity into the transformation of life over time.
From this schematic of how all life evolved on this planet, there is a hidden agenda, namely, the blind “need” to accurately represent the relevant features of the world. This requirement is in some ways the essence of evolution, and probably helped create genes, DNA, and even life.
BREEDING CHEMICAL COMPLEXITY AND REBELLIOUS OFFSPRING
 
Although there is a paucity of evidence to support the specific details of the origins of life, broad general comments can still be usefully made. In whatever location gave birth to life, there would have been a rich chemical soup of molecules. A small subset of these might have been capable of making copies of themselves from simple chemical reactions. (A surprising range of self-assembling non-life molecules have in fact been discovered and even technologically exploited.)
Multiply this tapestry of chemical activity by hundreds of millions of years of random interactions, and there will inevitably be a large variability in the qualities of all these different types of self-replicating micro-objects. Some molecules will require less energy and resources to generate copies, and these copies will be more faithful versions of the original, and more robust to potentially dramatic environmental changes.
One or two chemical forms may by chance be stupendously, ruthlessly good at making faithful replicas. In a sense, this is the first purchase point for evolution, even though there are as yet no life-forms.
Now, rapidly, there will be a thinning out of possibilities—all inefficient non-life replicators will lose the race to the resources and disappear, and the superior chemical copiers will dominate. The new battle is between these thoroughbred survivors. The active fight for energy and chemicals, even at this early pre-life stage, is an evolutionary process, because the main ingredients are already present: a vibrant competition for limited resources, on a superficial level, between different forms of chemical objects—and, more essentially, between different “ideas” about how to maintain one’s shape and make copies—which the chemical details of these proto-creatures encapsulate.
For instance, it’s a “bad idea” to be a great replicator dependent on potassium abundance when there’s usually none of it nearby. There’s no point requiring sunlight to maintain your shape when your habitat is normally in pitch darkness. There’s also, more generally, no point having a chemical makeup that requires huge quantities of energy to replicate when energy is sparse, especially if rivals are around. Success as measured by a burgeoning population in the primordial soup is predicated on maintaining a chemical composition that reflects or tracks the environment most closely—what resources
are
readily available, what’s the best way to extract energy from the local world, what environmental changes are likely to occur that may threaten many chemical reactions and that one may need to be protected against, and so on.
(At this stage, I should stress, I’m not assuming any consciousness whatsoever in any organism except for humans—terms like “beliefs” and “ideas” are meant as a kind of shorthand to describe creatures that internally represent a certain informational perspective about the world, but without any requirements for awareness of those representations.)
In this pre-life arms race, these close analogies to micro-beliefs about the environment, as stored in the shape of a chemical self-replicating object, are critical for survival. So it’s natural to assume that those objects that somehow represent the world more accurately, with greater detail, will carry an advantage. Indeed, the key reason that life might have evolved from simpler non-life equivalents is that non-life could not have developed the complexity of physical structure, or, very closely related to this, the extent of information storage, that organic life as we know it easily can.
Let me illustrate with a schematic example. Imagine there are three primordial copying objects, Alice, Beth, and Claire, all close to an active volcanic vent. Alice has stored the information that this precise location equals resources ad infinitum (perhaps by a strong chemical bond to the rock wall). When this particular volcanic vent becomes dormant, she degrades; she doesn’t make a single copy. Beth’s chemical components, instead, hold within them the “idea” that resources can potentially be found in multiple locations (perhaps by a chemical bond to the rock wall that weakens without sufficient heat, but strengthens again when another heated rock is chanced upon). When this particular vent becomes dormant, the lack of heat means she detaches herself from the rock and floats randomly until she’s jostled against another hot rock, which allows for a chemical reaction to bond her to the rock surface. She is again close to heat and other useful resources, allowing her to make some copies of herself. But when this rock, too, becomes dormant, and there is no other vent nearby, she degrades. In a sense, Beth’s structure is molding itself more closely than Alice’s to the external data concerning where resources can be found—instead of the chemical equivalent of a belief that Alice holds that “this location is all that matters,” Beth’s concept is that any hot rock will do. Claire has a physical structure that reflects the information that heat equals resources, regardless of location (by chemically sensing and gravitating toward the nearest heat source—behavior probably too sophisticated for non-life). So Claire has a chemical form that most accurately shapes itself to the information about her requirements for heat energy, as well as how in the world to find this, and this gives her—and her similar offspring—a distinct advantage. She follows Beth to the second vent, but when this vent fails and Beth degrades, Claire directionally moves toward the next nearest heat source. Over time, in response to these dangerously intermittent vents, Claire-forms will be the only population that survives.
LIVING ON THE EDGE OF CHAOS
 
While Claire’s more sophisticated, accurate “idea” would have caused her to be the dominant pseudo-life creature in her world, an even more successful way of responding to a changing environment is to update your ideas about it. Making true copies of yourself is important, but with such a dynamic world, where superior rivals or new dangers might emerge at any moment, being too fixed in your representations is dangerous. In this situation, exact copies of the originally superior chemical look doomed by their antiquated inflexibility. So some mechanism that can actually inject new creative ideas—in other words, that can “learn”—could potentially be very advantageous.
At this primordial stage, on the cusp of life, changing “beliefs” simply means making nonidentical copies. In other words, a family of proto-creatures needs to maintain a healthy balance between keeping useful knowledge and accepting that their world-picture could be better; they want their offspring to be faithful copies of themselves, but not
too
faithful. This loosening of the fidelity of the information is potentially expensive, because by chance many offspring will be inferior, perhaps just disintegrating at birth, or in other ways missing some vital chemical detail that enhances the chances of survival or replication. But it also raises the opportunity for some of the next generation to be an improvement on the model.
This tension between maintaining beliefs and injecting new ideas is a profound issue for any complex information-processing system, be it proto–life-forms, the neural interactions in our brains, or the scientific enterprise as a whole. Usually, though, a Goldilocks middle state, with chaos on one side and utter stability on the other, is the optimal way for any system to process information, and especially to learn useful new details about the world. This semi-chaotic activity is found whenever efficient information processing is required. It is probably the default state for networks of neurons, and it is one explanation for how complex thoughts in the human mind emerge from neuronal chatter.
A similar optimal balance between order and chaos exists in the scientific enterprise. There are cases, particularly in the softer sciences, where a prominent professor with a large ego—and a history of drawing in a large amount of grant money based on his well-established ideas—will do all he can to maintain these theories, including engaging in practices that are essentially unscientific and dogmatic. He may bend the rules to publish papers confirming his results, ignore experiments his lab carries out that contradict them, insist that his lab tow the party line, that those working under him always believe in his theory absolutely, and so on. He and his scientific progeny, his PhD students and postdoctoral assistants, may well be maintaining this viewpoint in the face of increasing evidence opposing it. For a while, due to his influence and personality, his theory may continue to flourish, but eventually it will be superseded, and his research staff will find it increasingly difficult to grab decent academic posts because of their long-standing defense of a scientific position shown to be wrong.
In a separate category are scientists who constantly generate outlandish ideas but are not particularly interested in testing them with carefully controlled experiments. Admittedly these rarely get past the PhD stage, but if they do, their careers always seem hampered by their overactive creativity.
The best scientists not only have the most respectable careers but also leave a lasting legacy of work, along with a new set of high flyers, who were former students. These renowned scientists are skilled at establishing successful theories and empirical results. But they are also quick to ditch these theories when the evidence racks up against them. They then generate new ways of perceiving the field—always with a
qualified
creativity.
The ability to settle on this healthy balance between stability and chaos is probably too much to ask of pre-life creatures, except for the most advanced—those on the cusp of life—because they would lack the complexity to support it. Specifically, for effective, flexible information processing skills related to survival and replication, you first need a means of storing many solid preexisting beliefs, which DNA, as I will discuss in the next section, is supreme at doing. You then need techniques for testing new hypotheses about the environment. In life, the main method for this involves creating a host of successful offspring subtly different from yourself, with a small proportion of those differences potentially being an improvement, reflecting useful novel innovations.
Let me illustrate the relationship between complexity and adaptability with another schematic example. Imagine you have 5 different words (analogous to different kinds of atoms within a proto-life object) by which to make up a sentence 5 words in length (analogous to a replicating chemical creature made up of 5 atoms). In each case, the sentence of 5 words gives you very little information. However, there are 3,125 possible different sentences you can make. This is a reasonable number, but in the face of an incredibly dynamic world, it is still potentially very limiting. Now imagine you still have 5 different words, but you can make up a sentence 100 words long (like a replicating chemical with 100 atoms in it). Each 100-word sentence potentially carries 20 times more information than was represented by the simpler creature with sentences of 5 words. A far more striking feature, though, is that, instead of 3,125 possible different sentences, there are now 8 × 10
69
! Therefore, if the capacity to represent a greater variety of ideas is beneficial, the chemical object needs to be larger and more complex. Some chemical designs of equivalent size will be better than others at storing information and getting the balance of stability and flexibility correct. The specifics of the design, along with complexity itself, will provide further hooks for evolution to clasp onto.

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