Divergent Cumulative Cultural Evolution

This paper argues that there is a general constraint on the evolution of culture. This constraint – what I am calling the Fundamental Constraint – must be satisfied in order for a cultural system to be adaptive. The Fundamental Constraint is this: for culture to be adaptive there must be a positive correlation between the fitness of cultural variants and their fitness impact on the organisms adopting those variants. Two ways of satisfying the Fundamental Constraint are introduced, structural solutions and evaluative solutions. Because of the limitations on these solutions, this constraint helps explain why there is not more culture in nature, why the culture that does exist has the form it has, and why complex, cumulative culture is restricted to the human species.

Philosophical Transactions of the Royal Society B: Biological Sciences, 2008

Cumulative cultural evolution is the term given to a particular kind of social learning, which allows for the accumulation of modifications over time, involving a ratchet-like effect where successful modifications are maintained until they can be improved upon. There has been great interest in the topic of cumulative cultural evolution from researchers from a wide variety of disciplines, but until recently there were no experimental studies of this phenomenon. Here we describe our motivations for developing experimental methods for studying cumulative cultural evolution, and review results we have obtained using these techniques. The results that we describe have provided insights into understanding the outcomes of cultural processes at the population level. Our experiments show that cumulative cultural evolution can result in adaptive complexity in behaviour, and also can also produce convergence in behaviour. These findings lend support to ideas that some behaviours commonly attributed to natural selection and innate tendencies could in fact be shaped by cultural processes.

Baraghith, K., Feldbacher-Escamilla, CJ (2020): Cultural Inheritance in Generalized Darwinism, Philosophy of Science, forthc., 2020

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 (i.e. blending inheritance). In this paper, we compare classical models of cultural evolution (cf. Boyd and Richerson, 1988; Mesoudi, 2011) and generalized population dynamics (Schurz, 2011) 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.

Cliodynamics: The Journal of Quantitative History and Cultural Evolution, 2018

The Extended Evolutionary Synthesis (EES) is beginning to fulfill the whole promise of Darwinian insight through its extension of evolutionary understanding from the biological domain to include cultural information evolution. Several decades of important foundation-laying work took a social Darwinist approach and exhibited ecologically-deterministic elements. This is not the case for more recent developments to the evolutionary study of culture, which emphasize non-Darwinian processes such as self-organization, potentiality, and epigenetic change. Smith et al.: Extended Evolutionary Synthesis. Cliodynamics 9:2 (2018) 85 "culture change," we believe that is misleading, for "change" need not be cumulative, adaptive, and open-ended. 1 Critiques of evolutionary models of culture have a long history in the Americanist anthropological tradition (Carneiro 2003; Mace 2014; Perry and Mace 2010), and today there remains question about the appropriateness of the "analogy" between cultural and biological evolution (Claidière and André 2011). While cultural evolution differs from biological evolution, cultural evolution is not merely analogous to biological evolution, it is a genuine evolutionary process, albeit one that uses different information channels, with different properties. Note that while some view the central criterion of evolution to be replication with variation and selection (e.g. Hull et al. 2001), this is but one form of evolution. Evolution can also occur through communal exchange and self-organization (Gabora 2013; Vetsigian 2006) and through context-driven actualization of potential (Gabora 2005, 2006) (for specific and general discussions of this topic see Kopps et al. 2015 and Gabora and Aerts 2002, respectively; see also Appendix 1). This approach is sometimes referred to as Self-Other Reorganization because it involves both interactions within self-organizing structures and interactions between them. We emphasize that for a process to be evolutionary (whether it be Darwinian evolution or not), change must occur on the basis of a fitness function or an environment that confers constraints and affordances. If not, i.e., if change is random, it is not due to evolution but to processes such as drift (i.e., variation in the relative frequency of different genotypes in a small population owing to the chance disappearance of particular genes as individuals die or do not reproduce). Cultural evolution is fueled by the generation of and reflection on creative ideas, which might exist not in the form of a collection of explicitly actualized variants as is required for biological evolution, but in a state of potentiality (Gabora 2017). 2 If an idea in a state of potentiality is considered with respect to one context it evolves one way, whereas if considered with respect to another context it evolves another way; there are no variants that get actualized and selected amongst. The mathematical description of evolution through variation and selection is very

2009

This paper presents a Darwinian framework to study culture that formalises interactions between public and private, ontogenetic and phylogenetic as well as individual and social aspects of cultural evolution and transmission. It also compares and contrasts evolutionary milestones in the emergence of culture with major transitions in the evolution of life. We define two related processes in the evolution of culture: the cumulative encoding of innovative information into public culture and the ontogenetic development of cultural competences that allow humans to access and use that information. We claim that the capacity to create, learn and use symbols is a key factor underlying those processes.

2013

Dawkins' replicator-based conception of evolution has led to widespread misapplication of selectionism across the social sciences because it does not address the paradox that inspired the theory of natural selection in the first place: how do organisms accumulate change when traits acquired over their lifetime are obliterated? This is addressed by von Neumann's concept of a self-replicating automaton (SRA). A SRA consists of a self-assembly code that is used in two distinct ways: (1) actively deciphered during development to construct a self-similar replicant, and (2) passively copied to the replicant to ensure that it can reproduce. Information that is acquired over a lifetime is not transmitted to offspring, whereas information that is inherited during copying is transmitted. In cultural evolution there is no mechanism for discarding acquired change. Acquired change can accumulate orders of magnitude faster than, and quickly overwhelm, inherited change due to differential replication of variants in response to selection. This prohibits a selectionist but not an evolutionary framework for culture and the creative processes that fuel it. The importance non-Darwinian processes in biological evolution is increasingly recognized. Recent work on the origin of life suggests that early life evolved through a non-Darwinian process referred to as communal exchange that does not involve a self-assembly code, and that natural selection emerged from this more haphazard, ancestral evolutionary process. It is proposed that communal exchange provides an evolutionary framework for culture that enables specification of cognitive features necessary for a (real or artificial) society to evolve culture. This is supported by a computational model of cultural evolution and a conceptual network based program for documenting material cultural history, and it is consistent with high levels of human cooperation. Evolutionary Framework Culture 3

Plos One, 2011

One of the hallmarks of the human species is our capacity for cumulative culture, in which beneficial knowledge and technology is accumulated over successive generations. Yet previous analyses of cumulative cultural change have failed to consider the possibility that as cultural complexity accumulates, it becomes increasingly costly for each new generation to acquire from the previous generation. In principle this may result in an upper limit on the cultural complexity that can be accumulated, at which point accumulated knowledge is so costly and time-consuming to acquire that further innovation is not possible. In this paper I first review existing empirical analyses of the history of science and technology that support the possibility that cultural acquisition costs may constrain cumulative cultural evolution. I then present macroscopic and individual-based models of cumulative cultural evolution that explore the consequences of this assumption of variable cultural acquisition costs, showing that making acquisition costs vary with cultural complexity causes the latter to reach an upper limit above which no further innovation can occur. These models further explore the consequences of different cultural transmission rules (directly biased, indirectly biased and unbiased transmission), population size, and cultural innovations that themselves reduce innovation or acquisition costs.

Although genetic information is acquired only once, cultural information can be both abandoned and reacquired during an individual's lifetime. Therefore, cultural evolution will be determined not only by cultural traits' ability to spread but also by how good they are at sticking with an individual; however, the evolutionary consequences of this aspect of culture have not previously been explored. Here we show that repeated learning and multiple characteristics of cultural traits make cultural evolution unique, allowing dynamical phenomena we can recognize as specifically cultural, such as traits that both spread quickly and disappear quickly. Importantly, the analysis of our model also yields a theoretical objection to the popular suggestion that biological and cultural evolution can be understood in similar terms. We find that the possibility to predict long-term cultural evolution by some success index, analogous to biological fitness, depends on whether individuals have few or many opportunities to learn. If learning opportunities are few, we find that the existence of a success index may be logically impossible, rendering notions of "cultural fitness" meaningless. On the other hand, if individuals can learn many times, we find a success index that works, regardless of whether the transmission pattern is vertical, oblique, or horizontal. cultural fitness | diffusion | retention I n this paper, we will address the popular suggestion that biological and cultural evolution can be understood in similar terms (1-8).

Darwin-inspired population thinking suggests approaching culture as a population of items of different types, whose relative frequencies may change over time. Three nested subtypes of populational models can be distinguished: evolutionary, selectional and replicative. Substantial progress has been made in the study of cultural evolution by modelling it within the selectional frame. This progress has involved idealizing away from phenomena that may be critical to an adequate understanding of culture and cultural evolution, particularly the constructive aspect of the mechanisms of cultural transmission. Taking these aspects into account, we describe cultural evolution in terms of cultural attraction, which is populational and evolutionary, but only selectional under certain circumstances. As such, in order to model cultural evolution, we must not simply adjust existing replicative or selectional models but we should rather generalize them, so that, just as replicator-based selection is one form that Darwinian selection can take, selection itself is one of several different forms that attraction can take. We present an elementary formalization of the idea of cultural attraction.

Proceedings of the National Academy of Sciences, 1989

We consider an evolutionary game model in which strategies are transmitted culturally from parents to offspring rather than inherited biologically. Our analysis yields two noteworthy results. First, biocultural games show a greater diversity of dynamical behaviors than their purely biological counterparts, including multiple fully polymorphic equilibria. Second, biocultural games on average exhibit greater equilibrium strategy diversity because of the countervailing influences of cultural transmission and natural selection. Therefore, knowledge of a strategy's influence on Darwinian fitness is not sufficient to infer the evolutionary consequences of biocultural games. Further, our results suggest that cultural transmission in the presence of natural selection may be an important mechanism maintaining behavioral diversity in natural populations.

Biology and Philosophy, 2008

This paper tries to explain how individuals manage adaptive individual choice (i.e. the decision to acquire a fitter than average behavior or idea rapidly and tractably) in cultural evolution, despite the fact that acquiring fitness information is very difficult. I argue that the means of solving this problem suggested in the cultural evolution literature largely are various types of decision rules employing representations of fitness correlated properties or states of affairs. I argue that the problem of adaptive individual choice is best solved where some of these learning rule representations are socially transmitted and some are biologically transmitted.

Proceedings of the National Academy of Sciences

Human cultural traits—behaviors, ideas, and technologies that can be learned from other individuals—can exhibit complex patterns of transmission and evolution, and researchers have developed theoretical models, both verbal and mathematical, to facilitate our understanding of these patterns. Many of the first quantitative models of cultural evolution were modified from existing concepts in theoretical population genetics because cultural evolution has many parallels with, as well as clear differences from, genetic evolution. Furthermore, cultural and genetic evolution can interact with one another and influence both transmission and selection. This interaction requires theoretical treatments of gene–culture coevolution and dual inheritance, in addition to purely cultural evolution. In addition, cultural evolutionary theory is a natural component of studies in demography, human ecology, and many other disciplines. Here, we review the core concepts in cultural evolutionary theory as th...

2020

Cultural evolution theory has long been inspired by evolutionary biology. Conceptual analogies between biological and cultural evolution have led to the adoption of a range of formal theoretical approaches from population dynamics and genetics. However, this has resulted in a research programme with a strong focus on cultural transmission. Here, we contrast biological with cultural evolution, and highlight aspects of cultural evolution that have not received sufficient attention previously. We outline possible implications for evolutionary dynamics and argue that not taking them into account will limit our understanding of cultural systems. We propose twelve key questions for future research, among which are calls to improve our understanding of the combinatorial properties of cultural innovation, and the role of development and life history in cultural dynamics. Finally, we discuss how this vibrant research field can make progress by embracing its multidisciplinary nature.

Journal of Cognition and Culture, 2011

This paper reviews and clarifies five misunderstandings about cultural evolution identified by Henrich et al. (2008). First, cultural representations are neither discrete nor continuous; they are distributed across neurons that respond to microfeatures. This enables associations to be made, and cultural change to be generated. Second, ‘replicator dynamics’ do not ensure natural selection. The replicator notion does not capture the distinction between actively interpreted self-assembly code and passively copied self-description, which leads to a fundamental principle of natural selection: inherited information is transmitted, whereas acquired information is not. Third, this principle is violated in culture by the ubiquity of acquired change. Moreover, biased transmission is less important to culture than the creative processes by which novelty is generated. Fourth, there is no objective basis for determining cultural fitness. Fifth, the necessity of randomness is discussed. It is con...

Human Ecology, 1982

This paper proposes models and examples of five principal modes of interaction between genes and culture in human evolution. Because genes and culture ultimately interact in the minds of individuals, the models are focused on individual-level processes of "constrained microevolution. " The central hypotheses are (1) that cultural evolution as well as genetic evolution commonly proceeds by the differential transmission of alternative "instructions" among individuals, (2) that genetic and cultural processes directly interact through mutual influence on each other's differentials of transmission in a population, (3) that the cultural process is often selfselecting by its own criteria, and (4) that these criteria generally operate to enhance rather than oppose human adaptation. Evolutionary change at higher levels, which is particularly important in sociocultural evolution~ is interpreted as restructuring the nature and extent of the variability available at the individual level. To clarify the conceptual differences of the models and hopefully to stimulate related analyses in other areas, I discuss selected examples of each of these interactions. I conclude with some remarks on the relative importance of the models to human ecology and evolution.