Decision-making, community, and the evolution of intelligence

All living things from the simplest bacteria to ourselves make decisions, but not all decisions are created equal.  Some are based on simple chemical reactions, or are driven by inflexible rules governing behavior, while others require complex intellectual machinery that ultimately leads to intelligence.  Our own decision making journey began three million years ago and resulted in the invention of language.

Three million years ago, humanity’s ancestors had some difficult decisions to make.  We had not yet shown much promise or prowess as hunters.  We were instead scavengers, devouring the marrow from the bones of massive animals, using primitive tools to crack them open, exploiting a food source other animals could not.  Scavenging, however, is not an easy lifestyle for an animal with our limited senses and range of motion.  We cannot fly in the sky like vultures and detect remains from miles away.  Our ancestors needed both a strategy to find the remains, and a means to share those findings throughout a small tribe of twenty to thirty individuals.  The strategy in principle was simple:  We divided the larger group into smaller groups that searched for decaying remains in different directions, maximizing our chances of finding something.  The challenge became how to communicate the various findings back to the larger group and decide which remains were the best option for exploitation.  This is not an easy problem to solve without language, and this was millions of years before anything resembling the written word.  Most animals communicate only in response to an ongoing stimulus, whether the behavior of another animal or something in the environment.  Here, early humans needed to communicate the location and size of finds that were not present, and then they needed to decide as a group which find to focus their limited resources on.  In other words, they needed to make a potentially life or death decision about something that didn’t exist in the range of their senses and experience.  The decision was about what might or might not happen in the future, and their own future depended on it.  The solution to this problem is likely how primitive language began.  We can imagine our ancestors using some combination of gestures and verbal grunts at first, demonstrating direction and distance by pointing and gesticulating, size by their level of excitement.  Over time, these gestures and grunts would become formalized into something resembling early words.  The words would then be combined into a proto-syntax.  Between the two, and assuming the growth of the supporting intellectual machinery, language could arise though it took over two million years.

If this scenario seems far-fetched, consider that it has happened before to an animal very distantly related to our own.  Honey bees have the same evolutionary challenge.  They live in a complex stratified community and they seek pollen reserves by sending drones out in different directions.  The drones then report back to the hive using a complex dance that communicates the size and location.  The hive then decides which resources are most ripe for exploitation.  That animals as different as humans and honey bees developed a similar strategy to deal with a similar challenge is known as niche selection.  Honey bees, of course, lack our massive brains.  Each individual bee is capable of only limited, programmed behavior.  They cannot break from the pattern of return and report.  Collectively, however, when thousands if not millions of bees coordinate this behavior, the hive makes intelligent decisions about where to exert their efforts and the energy for this effort, as we know, is the most precious commodity an organism has.  Honey bees are not the only hive insects that have solved this problem.  Ants and termites also leverage a combination of programmed behavior for the individual members and collective decision making to prosper.  They do not use a dance to communicate information about food sources, but for their purposes, a trail of pheromones works just as well.  Other ants are programmed to follow these trails based on their relative strength, and the largest food sources will ultimately generate the largest concentration of pheromones.  The same evolutionary imperative is at work across humans, bees, ants, and termites:  The need to solve a complex problem across multiple individuals that requires sophisticated decision making.  In all cases, the result is more intelligent behavior compared to similar animals.

For example, our closest cousins, the great apes live in groups, but they do not have to search far for food.  They do not need any means to communicate their findings and decide where to scavenge.  In other words, they do not need to make these kinds of complex decisions, and so they was no pressure to evolve the ability to do so. This doesn’t mean great apes do not make a lot of decisions.  They remain social animals and live in diverse communities, where power dynamics are ever shifting.  They are capable of incredibly complex behavior, from grooming and caring for each other to fighting their adversaries with finding desirable mates in between.  A chimpanzee needs the capacity to keep track of the dynamics of their group, know and to some extent, understand the players in the group, and decide what is the most advantageous behavior from their perspective.  This requires both the mental hardware to remember these details and evaluate optimal behaviors, both evolutionary pressures the chimpanzee experiences far more acutely than most other animals, leading to something resembling an evolutionary principle:  The more complex the decision making, the more complex the brain (or collection of brains) required to support it.  Putting this another way, animals that do not make complex, variable decisions do not exhibit what we would consider intelligent behavior.  Choosing between two things is easy.  You can flip a coin for a 50-50 chance, and even in an evolutionary context given a large enough population individuals will make the right choice half the time.  The ability to bias the choice towards the right answer at the moment will reap huge rewards, but this becomes far more difficult to do as the number of options expands.  A random choice between ten options will fail 90% of the time.  Weighting the choices will only be beneficial if the weightings can change based on the context, which is a complicated decision making process in its own right.

At the same time, all living things make decisions to survive, even simple bacteria.  E coli is present in all our bodies and serves as an excellent example.  The outer membrane of the bacteria is lined with clusters of proteins that respond to chemicals present in the environment; the protein “detects” the chemical almost like a Lego block, where a specific part of the chemical fits into a specific part of the receptor.  The activation of the receptor triggers the release of another set of proteins inside the bacteria proper.  This set of proteins triggers the bacteria’s “motor,” known as a flagellum, basically a tiny propeller.  This propeller normally pushes the bacteria along a straight path, but the activation of the receptor causes it to move in the direction of the chemical, normally food.  The result of these chemical reactions is fixed.  The bacteria doesn’t decide anything, but because it uses chemical reactions there is a certain amount of variability built in.  E coli spend their lives submerged in bodily fluids.  The chemicals they are exposed to dissolve across these fluids at different intensities, based on the distance from the source and the concentration.  The receptors are clustered together, meaning almost all of them may be active, most, some, or just a few.  The strength of the activation dictates the strength of the activation of the next protein.  Therefore, if E coli are exposed to a significant food source, they will quickly cluster there.  If the food source is small, they will be slower to respond.

This simplified model of decision making was present on Earth billions of years ago.  Life would not exist without it, but the multicellular animals that evolved between one billion and five hundred millions years ago developed more complex lifestyles.  Bacteria do not need to find mates.  They simply split into two copies when the conditions are right.  This process is triggered through a simple decision making process similar to when they eat.  There are similar processes for when to spore, or hibernate, and when to perform other functions vital to their existence.  These are essentially “on/off” switches, though the variability inherent in any biological process ensures not all bacteria respond equally at the same time.  Multicellular animals require more complex and adaptive decision making.  For example, they need to decide both when to make and who to mate with.  A purely algorithmic, chemical process will not do in this case.  The stimulus they are responding to is more complicated, meaning they need to observe more of their surroundings.  The observation of their surroundings required specialized mental hardware, the beginnings of a brain.  This hardware replaced the purely chemical processes in bacteria and other single celled organisms, synthesizing information from a wider range of receptors that ultimately became modern senses like vision, smell, and taste.  The brain was now the central place where data about the environment was stored and acted on, but even then most of the decision making process was algorithmic and rules based for hundreds of millions of years.  Most animals simply don’t require anything more.

They are instead closer to automatons, executing a fixed program of varying complexity.  We do not expect the shark to know the difference between a human and a seal.  We expect it only to observe the various stimuli associated with food and strike.  Likewise, the spider does not know whether the organism vibrating its web is a fly or something else.  It knows only the vibration and responds accordingly.  The rules they live by are embedded directly in their brains through evolved instincts, which may be as complex as the construction of a spider web or the process a digger wasp undergoes to build a nest for their young, but they remain essentially a list of steps that their brain executes based directly on stimulus from the environment.  The organism in question exhibits no choice in how these rules are applied.  The digger wasp is an excellent example.  Before laying their eggs, the wasp digs a hole, captures an insect to serve as host for her developing larva, brings the insect to the hole, and then lays her eggs inside.  Somewhere in their evolutionary past, however, another wasp or insect must’ve taken advantage of these holes as well because the wasp checks to make sure the hole is empty before bringing the host inside.  The behavior certainly seems intelligent on the surface.  The female wasp leaves the doomed host outside, peeks in to be sure everything is safe, comes back out and then carries the insect in.  A simple experiment reveals that she has no memory of doing this, however.  If you move the host insect while she is inspecting the hole, she will emerge, find the host insect again, bring it back outside the hole, and repeat the process.  She will do this over and over again, even if the host insect is moved only a couple of inches.  The wasp is executing a program, unaware of how or why or whether or not it was recently executed.

This simplified model is highly effective.  It works for the vast majority of life on the planet, but what it cannot do is harness the benefits of cooperation.  Animals that exhibit only this basic behavior can live in colonies, they can benefit from strength in their numbers like a school of fish, but they cannot unlock the additional benefits of group behavior.  Every animal is out for itself and knows nothing but itself.  Insects unlock these benefits by engineering themselves into biologically programmed roles.  Each insect is no more intelligent than any other, but the relationships between them are programmed in and more complex behavior arises.  There are ants, for example, that build farms to grow food for themselves.  Birds and mammals have taken a different path, increasing the brainpower of each individual in the group, and then using that brainpower to support more complex decision making and more adaptable behavior. The evolutionary needs are largely the same, but the use of a brain instead of the genetic code opens up additional opportunities for behavior to become even more complex and adaptive.  The brain can record the experiences of the individual animal, rather than serve as a repository for all of its ancestors.  The combination of instinct and learned response allows the animal to respond based on its experiences within that specific environment.  It also allows the individual to belong to a group, recognizing the difference between members of its own group and others based on its unique history.  Once part of a group, evolutionary pressure builds to make better decisions as a group for everything from rearing young to hunting and scavenging.  Wolves, whales, dolphins, and lions, for example, are all collaborative hunters, exploiting the benefit of their numbers and their cooperation to increase their chances of success.  This, of course, requires additional brainpower.  Decisions need to be made both in advance and in real time.  The dynamics of hunting as a group are far more variable and the group needs to act cohesively to be effective.  Each individual in a group needs to have the capacity to both remember these details and act upon them at the right time.  Instinct will not be nearly enough when there are hundreds of collective decisions made on a single hunt.  The pressures of rearing young and living as a group might be less, but they are still present.  Membership in a group does not come cheap, but once it comes the group tends to be more successful than isolated individuals.

Thus, we can see something of the hierarchy of intelligence and its evolution in decision making and group behavior throughout the spectrum of life.  All living things need to make simple decisions, but more complex animals that exhibit more complex behavior require more than simple chemical pathways like bacteria.  They make their decisions via brains, which collect information from the environment and act on it.  More complex brains, however, are required to support the combination of memory and decision making to live in groups with coordinated behavior.  The more complex the behavior and the coordination, the more brain power required.  The culmination of this process on planet Earth is us, after decisions that needed to be made 3 million years ago prompted the invention of language and all that came with it.