From Uncertainty to Insight: An Autocatalytic Framework

Abstract

Discontinuities permeate culture, and present a formidable challenge to mathematical models of cultural evolution. Cultural discontinuities have their origin in cognitive processes that include metaphor, analogy, cross-domain transfer, and self-organized criticality. This paper shows how cultural discontinuities can be accommodated by a theory of cultural evolution using cognitive reflexively autocatalytic foodset-generated (RAF) networks. RAF networks, originally developed to model the origin of life, have been used to models the origin of cognitive structure capable of evolving culture. Mental representations of knowledge and experience play the role of catalytic molecules, interactions amongst them (e.g., associations, affordances, or concept combinations) play the role of reactions, and thought processes are modelled as chains of such interactions. The approach tags mental representations with their source, i.e., whether they were acquired through social learning, individual learning (of pre-existing information), or creative thought (resulting in new information). This makes it possible to track the emergence and transformation of cultural novelty. We illustrate how the approach accommodates discontinuities using a historical example, and show how it is amenable to modelling cultural contributions of groups. We provide a RAF interpretation of the self-made worldview, and discuss how the approach can be used to think more concretely about possible future cultural trajectories. Because cross-domain thinking produces cultural discontinuities, it is impossible to pre-specify what features or traits will be present in future iterations of a cultural output. This suggests that cultural lineages are comprised not of external outputs or ‘memes’, but the conceptual networks that generate them.

Modeling Discontinuous Cultural Evolution: The Impact of Cross-Domain Transfer

“…It can thus help us in the task of understanding how culture evolves (Brand et al, 2020 ). A well-known example of analogical transfer is Kekulé's discovery of the structure of benzene by visual analogy to a snake biting its tail (Findlay, 1965 ; Gabora and Steel, in press ). This example reveals an interesting aspect of the phenomenon: the information from the source domain is not always retrieved from memory in the form it was originally encoded.…”

“…We posit that the generation of cumulative cultural novelty reflects the capacity for conceptual networks to evolve. Elsewhere, we have extensively compared and contrasted how RAF theory terminology applies in biological and cultural/cognitive settings (Gabora and Steel, 2017 , 2020a , b , 2021 , in press ). The fact that RAFs have proven useful in both these domains suggests that RAF theory may provide a broad conceptual framework that is applicable to the origins and early stages of diverse evolutionary processes.…”

“… 4 For further details see Gabora and Steel ( 2017 , 2020a , b , in press ). Elsewhere, we investigate the relationship between RAF structure and psychological integration/fragmentation [Ganesh, K., and Gabora, L. (under review), A Dynamical Autocatalytic Model of Therapeutic Change].…”

An Autocatalytic Network Model of Conceptual Change

“…It has been proposed that the origin of a self‐modifying autocatalytic cognitive network is the key to cumulative cultural evolution in our species (Gabora & Steel, 2020b), and the source of our generativity (Gabora & Steel, 2021b). Since autocatalytic networks incorporate the “triggering” or “catalytic” effect that an observation or piece of information can have on network structure, they provide a means of incorporating creativity into cognitive networks.…”

“…Such generativity may result in phase transitions to a network that is self‐sustaining and self‐organizing (Hordijk & Steel, 2004, 2016; Mossel & Steel, 2005), as well as potentially able to self‐replicate (in a relatively haphazard manner, without reliance on a self‐assembly code), and evolve, that is, exhibit cumulative, adaptive, open‐ended change (Gabora & Steel, 2021a; Hordijk & Steel, 2015). Therefore, RAFs have been used to model the origins of evolutionary processes, both biological—the origin of life (OOL) (Hordijk, Hein, & Steel, 2010; Xavier et al., 2020)—and cultural—the origin of culture (OOC), or more specifically, the kind of cognitive structure capable of generating cumulative, adaptive, open‐ended innovation (Gabora & Steel, 2017, 2020a, 2020b, 2021b).…”