Before talking about ants, here are three propositions which summarize, in broad strokes, the central principles of the metaphysics of the French philosopher Gilles Deleuze, as they will help us to understand and appreciate the genius of supposedly “primitive” animals such as ants:
1) Materialist affirmation of the immanent and rejection of the metaphysically transcendent – there is metaphysically nothing beyond the purely immanent and metaphysically univocal realm of matter and motion in spacetime, entailing that systems of thought which privilege a metaphysically “vertical” hierarchy of a “boss” at the top, dictating the behavior of, or imposing form or order on, metaphysically subordinate entities, gives way to a conception of reality as decentralized, democratic and self-organizing.
2) Rejection of the metaphysically substantial, essential or static – everything, including apparently stable or densely or tightly packed entities, are in a state of continual, material “becoming” that precedes the supposedly spurious identity or essence imposed upon them by human concepts.
Reality consists of a “body without organs” which is constituted entirely by an endless process of “becoming” and difference which precedes conceptual identity. The “body without organs,” to use the language of Deleuze, appropriated from Artaud, refers to a substrate which is also referred to as a “plane of consistency.” The body without organs is “non-formed, non-organised, non-stratified, or destratified.” It simply refers to reality insofar as it consists of a difference which precedes conceptual organization.
3) Rejection of the one/many distinction – Embodied in his concept of “multiplicity,” Deleuze rejects as artificial any distinction between “whole” and “part,” and any kind of doctrine which privileges any level or stratum of causal or mereological granularity (the linguistic, the economic, the material, the physical, the mental, the biological, the chemical, etc.), whether coarse-grained or fine-grained, entailing that any “cut” of reality can be considered either in light of another force or body (or set of forces or bodies) which it is affecting, or being affected by, regardless of the granularity-level of either, or as something interesting or worthy of study in its own right.
4) Affirmation of emergence – Relations of bodies to one another are not necessarily “additive” or reducible to the sum of their parts, but are, instead, emergent, or productive of fundamentally novel phenomena greater than the sum of their parts. There is a distinction between intensive or continuous differences and extensive or discrete differences, and Deleuze is interested in changes that result in fundamentally novel phenomena, patterns or “repetitions” not reducible to the sum total of their parts.
5) Rejection of the interiority/exteriority dichotomy – Deleuze rejects a hard-and-fast metaphysical distinction between interiority vs. exteriority, which would see the “interior” of an organism (such as a human) as a transcendent, indivisible, immaterial, hierarchically vertical and despotic, master of a contingent body and immune to an external environment (think the Cartesian ego cogito), preferring instead a plane of (semi)porous bodies determined, on the one hand, genetically, by a network of pre- and non-subjective relations and components, according to the dynamisms of its internal milieu, but also, by the impact of environmental and ecological influences, to which the complex adaptive system continually has to adapt, and with which it is continually (inter)penetrated.
William Sulis, in his essay “Collective Intelligence: Observations and Models” gives the reader a fascinating look into the relevance of non-linear dynamics for the study of ethology. The American myrmecologist W.M. Wheeler, anticipating the insights of modern complexity theory, described an organism as “a complex, definitely coordinated and therefore individualized system of activities, which [is] primarily directed to obtaining and assimilating substances from an environment, to producing other similar systems, known as offspring, and to protecting the system itself and usually also its offspring from disturbances emanating from their environment.” Organisms possess intelligence, and this intelligence sometimes manifests itself in ways very different from that found in humans. For example, certain insects, such as ants, are capable of collective intelligence. Collective intelligence is defined by William Sulis as “collective behavior that is stably correlated with ecologically meaningful features of the environment, salient for the survival of the collective, adaptive to changes in the environment, and that transcends the capability of any single member of the collective.”
Unsurprisingly, insect colonies are prime candidates for the study o collective intelligence. They consist of a large number of individuals which can be easily maintained and which, as Sulis notes, provide “an opportunity for the replication of statistically robust experiments.” Wheeler even suggested that the insect colony be considered an organism in its own right, since it possesses “the ability to regulate both its behavior and its environment to fulfill particular salient needs.” Colonies are able to do all of this even without a central authority, such as a hierarchically primordial central nervous system. Insect colonies constitute emergent phenomena insofar as the tasks a colony accomplishes are far beyond the scope of any individual among the colony. The behavior of insects is quite impressive:
“…when workers of the species Eciton burchelli are placed on a small surface, they are capable of carrying out radially distributed statory raids and constructing nests of their own bodies, both of which can be regulated within tight limits, given the presence of an entire colony of more than 200,000 workers. On the other hand, when only small numbers are present, they will walk endlessly in never-decreasing circles until they die of exhaustion.”
The social insect colony exhibits systematic and adaptive character insofar as its members are able to effectively and stably interact with their environment in such a way conducive to its well-being. While there is a great deal of variability on an individual level, there is a great deal of stability on a collective level. It is fascinating that the apparently random behavior of individual insects nonetheless results in a corporately adaptive and highly ordered system. As Sulis notes, “This ability o a sytem of interacting agents to respond stably to global features of the environment is typical of many complex systems models.”
Intelligence involves the ability to learn from experience and to adapt to the environment. In the case of humans, it involves the use of metacognition, in which the individual is able to think about his own cognitive processes and reflect upon itself. This is a uniquely human method of learning which favors “introspection, self-awareness, internalized representations, symbolic processes, and their expression through language.” Ant colonies clearly exhibit intelligence, but not of this sort. It is a form of intelligence nonetheless, however, and it becomes apparent that a different set of criteria may be required of non-human animals.
“Fundamentally, intelligence should describe how well an entity meets the challenges of procuring sustenance, providing defense, achieving reproduction, and caring for offspring in dynamic, nonstationary environments. McFarland and Bosser (1993) argued for a notion of intelligence that avoids a human bias by emphasizing the role of intelligent behavior. They have three requirements for intelligent behavior (a) behavior requires a body, (b) it is only the consequences of behavior that can be called intelligent, and (c) intelligent behavior requires judgment.”
Clearly ants possess some form of intelligence. The “collective intelligence” of an ant colony is what is known as an “emergent” phenomenon, in which the whole is greater than the sum of its parts and is not suggested by one of its individual constituents. In other words, no one would guess, by looking at an ant or a brain cell, that groups of these could give rise to a stable, adaptive colony or the phenomenon of qualia or consciousness, respectively. As noted before, this intelligence does not involve the use of language:
“A collective intelligence such as a social insect colony lacks the use of language and symbolic reasoning, although it does have the use of various signs and pheromones (chemical signals secreted by specialized glands of workers) and stigmergic relics (physical modifications to the local environment by the direct actions of workers) that can serve as triggers to particular classes of behavior. Thus the processes by means of which its decision-making strategies are implemented must reside in the dynamical interactions that arise between the members of the colony following exposure to the environmental context. It is therefore expected that a detailed understanding of the nature of the dynamics of interactions within the collective intelligence through such approaches as complex systems theory and nonlinear dynamical systems theory will hep to inform us about the types of decision making that can be carried out by a collective intelligence and the mechanisms by means of which these decisions are implemented by the collective. An important question si whether the decision making carried out by a collective intelligence can be nonrational or irrational, or worse, merely random.”
While typically associated with syntax and symbolic processing, ant colonies can be computational geniuses without the use of language. This is because they exhibit something called emergent computation:
“Computer scientists have looked to collective intelligence in their search for effective algorithms for parallel processing…especially to help with the difficult synchronization problem. Computer scientists often speak of collective computation or emergent computation. Forrest defined emergent computation as follows:
“This is the essence of the following constituents of emergent computation: i) A collection of agents, each following explicit instructions; ii) Interactions among the agents (according to the instructions), which form implicit global patterns at the macroscopic level i.e. epiphenomena; iii) A natural interpretation of the epiphenomena as computations.
The term explicit instructions refers to a primitive level of computation, also called micro-structure, low-level instructions, local programs, concrete structure, and component subsystems…The important point is that the explicit instructions are at a different (and lower) level than the phenomena of interests.”
Hirsch and Gordon (reviewed various models of collective intelligence viewed as distributed and parallel processing systems. They focused on models that deal with an individual ant’s judgment of its own success, usually based on its level of activity and on its wait time for either delivering or receiving information from its nestmates. Both of these can induce the ant to carry out particular tasks. They also highlighted work…showing that the stochastic model of an ant colony…was computational complete, meaning that the colony could carry out any computation that a computer could.”