The Hive Mind: Leafcutter ants act like farmhands, but…

Eric Cassell, author of Animal Algorithms: Evolution and the Mysterious Origins of Ingenious Instincts (2021), tells us that his favorite kind of ant (p. 97) is the leaf cutter (attini). The complex fungal culture provides insight into the ‘hive mind’, in which a natural version of a computer algorithm makes very complex decision-making possible.

There are 39 known species of leafcutters in the American tropics, easily identified by the long tracks (up to 100 feet) of ants, all of which carry bits of leaves picked from trees. They put them in underground nests with maybe a thousand rooms with millions of ants. There they chew the leaves and grow the fungus that feeds their larvae and themselves (along with plant sap). The leaf cutters are well adapted to the task as their jaws function as saws and they can support about 50 times their weight. They can strip a small tree at night:

In the tropical rainforests of the New World, these ants’ large nests are often found among large trees that are widely spaced with little undergrowth — a park-like environment created by the ants themselves. Many Atta species clear ant “highways” radiating from the nest, along which broad columns of their species can march unimpeded. – Britannica

Managing the fungus brought to the nest is a highly technical affair, as Cassell points out:

There are several other ways the ants maintain the health of the fungus. These include producing growth hormones and secreting antibiotics to suppress competing fungi and microorganisms. Hölldobler and Wilson note that the symbiotic relationship between leafcutter ants and fungi “must be viewed as a highly integrated superorganism that is greater than the sum of its parts. The ants’ division of labor and much of their social behavior is shaped by the details of these symbiotic relation.”

Eric Cassell, Animal Algorithms: Evolution and the Mysterious Origins of Ingenious Instincts Bee Discovery Institute Press, 2021, p. 99

The study of the antibiotic protocols followed in these vast, complex, yet impersonal structures has provided useful insights into chemicals and medicines for humans.

The Beehive

But what organizes all this? Well, no ant does that. It is best to see the colony as a whole as a superorganism, of which the ants are components. Much of what appears to be decision-making is the elaboration of algorithms, as Cassell points out in his book.

Stephen Pratt

Behavioral biologist Stephen Pratt of Arizona State University offers a helpful analogy to: Known magazine:

Bob Holmes: How is an ant colony like a brain?

Stephen Pratt: In the analogy, an ant is a brain cell, or neuron, and a colony is a brain. Neurons are simple in relation to the whole to which they belong. Their interactions with each other generate the highly complex output of the brain as a whole. Cognition arises from the interactions between very large numbers of neurons.

The same thing happens in an ant colony. Colonies make decisions, divide labour, move in cohesion. All of these group-level traits arise from interactions between large numbers of individual colony members. A brain or a colony processes information about its environment and about its own state, then produces some adaptive behavior appropriate to the circumstances.

Bob Holmes“The Ghost of an Anthill” on Known magazine (September 14, 2018)

So, just as a neuron is a small part of a brain, the individual ant is a small part of a self-organizing colony with a hive. Individual ants make instant decisions – but they make them in light of the direction of the colony as a whole.

Elva Robinson, an ant behavior specialist, gives an example of how the bee colony works among the ant colonies in her lab: The survival of a colony depends in part on fat stored in the bodies of ants, and the younger ants are the thicker. They stay in the colony and care for the eggs, larvae and pupae – as well as guarding the fat. The older ants, going out to forage, have become leaner (and perhaps hungry as a result). They also have a shorter expected lifespan, so overall their greatly increased risk of dying outside the nest is less of a loss to the colony. They bring food back but mainly give it to the thicker, protected ants, who themselves remain skinny. Robinson comments:

Elva Robinson

These ants are great examples of self-organization, as each ant makes a decision based on the information it has about itself. It doesn’t need to know the overall system of the colony and that’s a pretty important lesson for a lot of human systems where we tend to focus a lot on centralized control where you have one control center that collects all the information and decides what to do. But it’s clear that if there’s a problem with that control center, your whole system will break down. For ants, decisions are processed in a very distributed way, so all individuals contribute. And if someone is taken out of the system, it will still work. So in the case of our experiment, if some ants were removed as we did in our experiment, then the next skinny ants will go out. And if you keep getting rid of ants, more and more corpulent ants — more fat ants — will move out. So it’s all very self-regulating.

Elva Robinson“The Hive Mind – How Ants Know Their Place” on The naked scientists (June 6, 2010)

With their very small individual brains, the ants would need a self-regulating system to work together as a colony on a very complex task such as cultivating fungi:

We humans struggle to understand the hive mind because our human condition is a world of individual minds that, with some effort, can work together to solve a problem – at least for a while. But individuality inevitably gains the upper hand, for for better or for worse we are made that way. And apparently it is not how ants are made.

You may also want to read: Do ants think? Yes, they do – but they think like computers. Computer programmers have adapted some ant problem-solving methods to software programs (but without the need for complex chemical scents). Navigation expert Eric Cassell points out that algorithms have made the ant one of the most successful insects ever, both in number and complexity.


How do insects use their tiny brains to think clearly? How do they deal with complex behavior involving only 100,000 to a million neurons? Researchers are discovering that insects have a number of strategies for making the most of relatively few neurons to enable complex behavior.

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