thinker:openalex-A5042369841B.C. Barber
Authored papers (1)
Evolutionary individuality, organismic individuality, and cognition are coextensive — this is the load-bearing conjecture Watson and Levin develop across 22 pages in Collective Intelligence (2023, DOI: 10.1177/26339137231168355). The argument rests on dissolving three apparent categorical distinctions: all individuals are collectives (from molecules to multicellular organisms via major evolutionary transitions), all intelligences are collectives (brains are the archetypal case), and cognition is substrate-independent. The framework they introduce is evolutionary connectionism, which maps the algorithmic principles of connectionist models — specifically Hopfield networks, multi-layer perceptrons, deep belief networks, and Hebbian unsupervised learning — onto gene-regulatory networks, bioelectric networks, and ecological community networks. Empirically, the framework is grounded in planarian bioelectric pattern memory (transient gap-junction modulation producing heritable two-headed regeneration despite unaltered genomes), ectopic Xenopus eyes wired via spinal cord synapses that still support light-mediated learning, and newt kidney tubules that achieve correct diameter whether using ~8 normal-sized cells or a single enlarged cell bending on itself. Morphogenesis is reframed as basal cognition — anatomical problem-solving in morphospace — and the Hopfield network is used to show how unsupervised, distributed Hebbian learning at the component level produces system-level associative memory and generalisation without centralized control or global reward feedback. The paper argues this implies that the capacity to represent non-linearly separable functions (requiring multi-layer interaction depth) is both the necessary condition for genuine collective intelligence and the very thing that constitutes a new level of evolutionary individuality, with direct consequences for regenerative medicine, cancer as dysregulated morphogenesis, and the engineering of synthetic living machines.