One of my surprises when first studying biology was the smallness of the living world. After all, the most abundant organisms on the planet are bacteria, and even within the relatively small club that is the animal kingdom, most creatures are arthropods, and 86 percent of arthropods are insects.

We tend to forget how successful these creatures are, but, as we say of mosquitoes in my home state of Rhode Island, “They're small…but they're organized!” 

It is a certain type of insect organization, however, that has become a model for a new scientific paradigm. This is the “superorganism” and our mimicking of its behavior continues to hold promise for sustainable design.

In my last essay I wrote of the lessons from mound-building termites that architect Mick Pearce had learned and applied to climate control in high-rise office buildings. While mimicking the structure of termite architecture to save energy has yielded some impressive results, there is more to learn from these creatures that is germane to that third key parameter, information.

These tiny creatures manage to build structures that are 25 feet high. They share child rearing, farm, hunt and wage war. To do this they maintain order and perpetuate communities of upwards to the millions. How do they do this with brains the size of pinheads? Surely their communication network must be incredibly sophisticated, and it is… and it isn't.

Termites, bees, ants and wasps belong to the so-called eusocial (“truly social”) insects. To be a truly social society in the biologist's sense is to possess three basic traits: Adult members must be divided into those who reproduce and those who do not; these adults must coexist across two or more generations in the same nest; and non-reproducers (or those that reproduce less) must care for the young. As you might guess, all of these attributes have survived the natural selection numbers game because they perpetuate the gene pool so well.

These communities are the “superorganisms,” a word coined by William Morton Wheeler in the 1920s, and discussed by the eminent biologist E.O. Wilson in his latest book with Bert Holldobler, “The Superorganism: the Beauty, Elegance and Strangeness of Insect Societies.”

It is an apt description of these colonies of creatures, for they dominate our terrestrial world, accounting for more than 1,000 trillion individuals. Indeed, Wilson estimates that their global weight is equal roughly to that other overachiever, Homo sapiens. More to the point, the name also indicates a more systemic characteristic. The colony, rather than the individual, is what functions as a unit, adapts to change, and is maintained and perpetuated. As such, argues Wilson, these societies are the perfect window into "the emergence of one level of biological organization into another.”

Emergence is a key trait of biological organization. Within the nested scales of hierarchy from the atom to the biosphere, life exhibits this principle: Whole systems cannot be explained by an examination of their parts because they are the product, rather than the sum, of these parts. The final formula and product, therefore, include the complexities of the array, relationships and interactions of those parts. Emergent properties are everywhere in nature, from DNA to ecosystems. Your mind, for instance, cannot be explained by an analysis of neurons; it has so-called irreducible properties that make it a completely new and different phenomenon.

The mound building of termite colonies is also a good example. A complex, many-part structure rises 2,500 times the height of any one of its individual builders, full of arched tunnels, nurseries, growing chambers and ventilation shafts. Within, different castes tend to young, reproduce, farm fungus, maintain ventilation, build, repair and defend the nest.

If we were to build such a structure in a similar fashion it would be done without blueprints, architects, engineers or construction managers. Indeed, no one would be in charge. Each tradesperson would operate with simple “If-then” rules, concerned only with his small set of preprogrammed actions. How he chose those actions would be based on another small set of context scenarios.

Often the actions of some workers would trigger the work programs of others. If carpenters sensed that there were too many of themselves on the third floor, some of them would switch to plumbing. When corners were completed perhaps the work crew would start building upwards. Over time these local actions would produce a global result.  If made to scale, the building would be almost three miles high…and, oh yes, it would be made of dirt mixed with the workers' own spit (and other waste products).

This is self organization and in the insect societies it happens because of two things: Developmental algorithms that determine the castes with their specialized skills, and behavioral algorithms that determine how everybody will act toward each other and respond to a few environmental possibilities. Moment to moment communication occurs via pheromones, the chemical messages of the insect world. At a higher level, the algorithms themselves evolve through the process of natural selection, just as the traits of the non-super organisms do. 

It is a successful strategy indeed. While these types of societies represent only 2 percent of the world's insect species, they account for over half of the biomass. These insect societies “…illustrate, through thousands of examples, how the division of labor can be crafted with flexible behavior patterns to achieve an optimal efficiency of a working group.”

It is not surprising that such a successful and fascinating strategy should have gained our attention. Over the past several decades, “bottom-up” logic has been ascendant in the fields of artificial intelligence, cybernetics, physiology, telecommunications, management and logistics. Internet searches, market predictions, customer preferences, vehicle routing and manpower management have all benefited from the eusocial insect organizational model. The reason is that it works: in many cases because its simplicity, adaptability and robustness outperform our traditional “top-down” methods, particularly in complex systems. 

Take, for instance, something like the routing of workers and materials to a job site. Icosystem of Cambridge, Mass., has used so-called evolutionary computation to organize field crews for oil and gas drilling. In reviewing schedules, the consultants employed algorithms based on the foraging behavior of ants, and rated routes based on similar feedback mechanisms. Instead of finding food, however, the company wanted to find efficiency: the shortest routes, the lowest supply prices, the fastest delivery, full employment of their workers. Only by analyzing (and optimizing) all the factors together, could the company find new savings. Often the routes chosen for the day were not the closest to the material supplies, but, overall, were the cheapest.

Similarly, Soutwest Airlines wanted to improve the efficiency of its plane routes on the ground. It used an ant-based simulation model for tracking the planes and, like the pheromone trails that ants leave, informed each agent of its path and those of its fellow agents. Best routes to gates were thus learned and remembered and the company was able to eliminate wasted time and money. 

Swarm intelligence is also being explored by Volvo in developing its injury-proof car by 2020. In this case, locusts, rather than ants, are being studied for their ability to avoid collisions while flying in groups of millions. They do it by neural circuitry that connects visual input directly to their wings for near-instantaneous adjustment of flight. Volvo is hoping that this “sensory input routing methodology” can be reconciled to our current technological limits in manufacturing and put to use. Avoiding crashes, and mitigating them by automatic steering and breaking will be combined with other features for this car of the future.  If successful, it will be a major breakthrough in car safety, using information, rather than energy or materials, to keep passengers safe.

The superorganism model has implications beyond the efficiency of operations, for it offers an expanded paradigm for growth and control. New markets and solutions can be found by studying the individual behaviors that determine overall effects. Growth can be managed and sustained in a new way. Interdisciplinary coordination, so important in solving complex system problems, can be expanded. Finally, whole new forms can be explored using these models. Indeed, architects are doing that now and it is changing our notion of what a building is. This is what I will write of next time.

Tom McKeag teaches bio-inspired design at the California College of the Arts and University of California, Berkeley. He is the founder and president of BioDreamMachine, a nonprofit educational institute that brings bio-inspired design and science education to K12 schools. 

Ants - / CC BY 2.0; / CC BY-ND 2.0