Decoding the Superorganism: From Collective Cognition to Artificial Intelligence

Abstract:

Colonies of social insects are biological benchmarks of adaptive self-organisation. Unlike human societies, they function absent centralised control, and are instead regulated primarily through interactions at the local level. This facilitates the emergence of complex collective behaviour from simple rules, while enhancing network flexibility and system redundancy. Notably, certain highly eusocial species function as integrated ‘superorganisms’—societies that are conceptually analogous to single multicellular bodies. Indeed, processes usually organised at a cellular level—such as the differentiation of germ and soma, or the formation of neural networks—may occur across discrete individuals, presenting unique opportunities for both observation and manipulation. Here, I outline the consequent utility of social insect models when addressing fundamental and applied challenges in biology. Additionally, I summarise how recent advances in artificial intelligence and automated tracking are enabling unprecedented insight into these complex systems.

More about Dr Thomas O'Shea-Wheller here.