Karim Baraghith

Generalized Darwinism models cultural development as an evolutionary process, where traits evolve through variation, selection, and inheritance. Inheritance describes either a discrete unit’s transmission or a mixing of traits. In this article, we compare classical models of cultural evolution and generalized population dynamics with respect to blending inheritance. We identify problems of these models and introduce our model, which combines relevant features of both. Blending is implemented as success-based social learning, which can be shown to be an optimal strategy.

The generalized theory of evolution suggests that evolutionary algorithms apply to biological and cultural processes like language alike. Variation, selection and reproduction constitute abstract and formal traits of complex, open and often self-regulating systems. Accepting this basic assumption provides us with a powerful background methodology for this investigation: explaining the emergence and proliferation of semantic patterns, that become conventional. A teleosemantic theory of public (conventional) meaning (Millikan 1984; 2005) grounded in a generalized theory of evolution explains the proliferation of public language forms in terms of their adaptive proper function. It has also been suggested, that the emergence of meaning, can be formalized with game-theoretical tools (Skyrms 2010) within signaling systems of coordination. I want to show how closely related these approaches are, both in terms of explanandum and of outcomes. To put it in a nutshell: If the emergence of public meaning can be satisfyingly explained in terms of signaling games, then the cultural evolutionary dynamics will serve as an adequate model to describe their proliferation. Public or conventional meaning (in contrast to personal meaning) can be fully understood in terms of its evolutionary function in a population of communicators. Furthermore, I want to argue how this understanding of conventional meaning could lead us to a strong semantic holism.

Darwinian evolution is a population-level phenomenon. This paper deals with a structural population concept within the framework of generalized Darwinism, resp. within a generalized theory of evolution. According to some skeptical authors, GD is in need of a valid population concept in order to become a practicable research program. Populations are crucial and basic elements of any evolutionary explanation—biological or cultural—and have to be defined as clearly as possible. I suggest the “causal interactionist population concept”, by R. Millstein for this purpose, and I will try to embed the approach into a generalized evolutionary perspective by mathematically formalizing its key definitions. Using graph-theory, populations as described in the CIPC can serve as proper clusters of evolutionary classification based on the rates of interactions between their elements. I will introduce the concept of a cohesion index as a measurement of possible population candidates within a distribution of elements. The strength of this approach lies in its applicability and interactions are relatively easy to observe. Furthermore, problems of clustering tokens via typicality, e.g. their similarity in intrinsic key characteristics, can be avoided, because CIPC is a external approach. However, some formal problems and conceptual ambiguities occur within a simple version of this CI, which will be addressed in this paper as well as some possible applications.

What is it that evolves in cultural evolution? This is a question easily posed but not so easily answered. According to common interpretations of cultural evolutionary theory, it is not strictly agents that change over time or proliferate during cultural transmission, but their socially transmitted behavior, what they communicate or acquire via social learning – in short: their interactions. This means that we have to put these cultural interactions into an evolutionary setting and show how they evolve within cultural populations, i.e. within social networks. But the social networks themselves also evolve, which brings us to a multi-level approach of cultural evolution, implementing both, individual and group selection. In this paper I will assume that the microlevel is given by a description of cultural agents, their behavior and decisions, whereas the macrolevel describes the dynamics on population structure and in particular population boundaries in social networks (since we are not really able to identify something analogous to ‘species’ in cultural evolution). In this paper, I am going to offer a specific mathematical model, that makes use of game theory for representing the cultural microlevel and graph theory for the cultural macrolevel. It has to be shown, how both can formally be linked in a synthetic attempt.

Das Buch untersucht die Mechanismen der kulturellen Evolution, insbesondere die Rolle von Memen – kulturelle Muster also, die von Generation zu Generation weitergereicht werden. Gesellschaften durchlaufen einen evolutionären Prozess, Prinzipien wie Variation, Selektion und Reproduktion können als abstrakte Eigenschaften dynamischer Systeme verstanden werden. Sie finden sowohl Anwendung bei der Entwicklung von Organismen als auch bei kulturell erworbenen Verhaltensweisen. Dies ist der Erklärungsansatz einer interdisziplinären verallgemeinerten Evolutionstheorie. Was aber evolviert genau innerhalb der kulturellen Evolution? Der Autor versucht Einheiten der kulturellen Entwicklung (Meme) möglichst exakt zu definieren, um spezifische kulturelle Phänomene zu erklären.

Ever since proposals for generalizing the theory of natural evolution have been put forward, the aims and ambitions of both proponents and critics have differed widely. Some consider such proposals as merely metaphors, some as analogies, some aim at a real generalization and unification, and some have even proposed to work out full reductions. In this paper it is argued that these different forms of generalizing the theory of evolution can be systematically re-framed as different approaches for transferring justification from the natural to the cultural realm, and that their differences are basically a matter of degree. With the help of such a classification it should become clearer what to expect, but also what not to expect from the different approaches.

In this paper, we critically consider the analogy between “infodemic” and “pandemic”, i.e. the spread of fake news about COVID-19 as a medial virus and the infection with the biological virus itself from the perspective of cultural evolutionary theory (CET). After confronting three major shortcomings of the ‘infodemic’ concept, we use CET as a background framework to analyze this phenomenon. To do so, we summarize which bi-ases are crucial for transmission in terms of cultural selection and how transmission is restricted by filter bubbles or echo chambers acting as TRIMS (transmission isolating mechanisms) post “infection”, which isolate false from trustworthy scientific information in the context of the Corona pandemic. This is followed by a demonstration of the threat to biological fitness posed by the effects of an infection with fake news, which leads to a reduced willingness to vaccinate and follow health measures. We identify fake news on Covid as pseudoscience, trying to immunize itself from external influences. We then address the question of how to combat the infodemic. Since debunking strategies, such as warnings by fact-checking, have proven relatively ineffective in combating fake news, the inoculation theory from psychology might offer an alternative solution. Through its underlying ‘prebunking strategy’, which educates individuals about the risks and tactics of fake news prior to a potential infection, they could be ‘immunized’ in advance, similar to a virological vaccination. Although we recognize that the pandemic/infodemic analogy is in fact far from perfect, we believe that CET could provide a theoretical underpinning in order to give much more semantic depth to the concept ‘infodemic’.