scholarly journals Enquire within: cultural evolution and cognitive science

2018 ◽  
Vol 373 (1743) ◽  
pp. 20170051 ◽  
Author(s):  
Cecilia Heyes
Keyword(s):  
Cognitive Science ◽  
Learning Strategies ◽  
Cognitive Processes ◽  
Cultural Evolution ◽  
Interdisciplinary Studies ◽  
Darwinian Evolution ◽  
Cultural Learning ◽  
Third Way ◽  
Cultural Selection ◽  
Cultural Domain

Cultural evolution and cognitive science need each other. Cultural evolution needs cognitive science to find out whether the conditions necessary for Darwinian evolution are met in the cultural domain. Cognitive science needs cultural evolution to explain the origins of distinctively human cognitive processes. Focusing on the first question, I argue that cultural evolutionists can get empirical traction on third-way cultural selection by rooting the distinction between replication and reconstruction, two modes of cultural inheritance, in the distinction between System 1 and System 2 cognitive processes. This move suggests that cultural epidemiologists are right in thinking that replication has higher fidelity than reconstruction, and replication processes are not genetic adaptations for culture, but wrong to assume that replication is rare. If replication is not rare, an important requirement for third-way cultural selection, one-shot fidelity , is likely to be met. However, there are other requirements, overlooked by dual-inheritance theorists when they conflate strong (Darwinian) and weak (choice) senses of ‘cultural selection’, including dumb choices and recurrent fidelity . In a second excursion into cognitive science, I argue that these requirements can be met by metacognitive social learning strategies , and trace the origins of these distinctively human cognitive processes to cultural evolution. Like other forms of cultural learning, they are not cognitive instincts but cognitive gadgets. This article is part of the theme issue ‘Bridging cultural gaps: interdisciplinary studies in human cultural evolution’.

Cumulation

2019 ◽  
pp. 186-212
Author(s):  
Alberto Acerbi
Keyword(s):  
Digital Media ◽  
Cultural Evolution ◽  
Cultural Selection ◽  
Cultural Domain ◽  
Cumulative Cultural Evolution ◽  
Efficient Mechanisms

Chapter 8 considers what cultural evolutionists call cumulative cultural evolution, that is, the idea that culture increases in complexity. For a cultural domain being defined as cumulative, it needs to show accumulation (more traits), improvement (traits are more efficient), and ratcheting (new traits build on previous innovations). The author proposes that this is not a necessary outcome, and that different domains show different signs of cumulation. It is suggested that the fidelity and the hyper-availability provided by digital media allow for more cumulation in domains where it was limited before. Not surprisingly, they also allow for the retention of vast amounts of useless information—junk culture. A central challenge for the coming years is thus finding efficient mechanisms of online cultural selection. Algorithmic selection is finally discussed, along with how mainstream criticisms, such as the fact that algorithms are biased or opaque to users, are not decisive arguments against their efficacy and utility.

scholarly journals Grist and mills: on the cultural origins of cultural learning

2012 ◽  
Vol 367 (1599) ◽  
pp. 2181-2191 ◽  
Author(s):  
Cecilia Heyes
Keyword(s):  
Cognitive Processes ◽  
Cognitive Neuroscience ◽  
Cultural Evolution ◽  
Developmental Psychology ◽  
Empirical Work ◽  
Comparative Psychology ◽  
Cultural Learning ◽  
Ample Evidence ◽  
Cumulative Cultural Evolution ◽  
Cultural Origins

Cumulative cultural evolution is what ‘makes us odd’; our capacity to learn facts and techniques from others, and to refine them over generations, plays a major role in making human minds and lives radically different from those of other animals. In this article, I discuss cognitive processes that are known collectively as ‘cultural learning’ because they enable cumulative cultural evolution. These cognitive processes include reading, social learning, imitation, teaching, social motivation and theory of mind. Taking the first of these three types of cultural learning as examples, I ask whether and to what extent these cognitive processes have been adapted genetically or culturally to enable cumulative cultural evolution. I find that recent empirical work in comparative psychology, developmental psychology and cognitive neuroscience provides surprisingly little evidence of genetic adaptation, and ample evidence of cultural adaptation. This raises the possibility that it is not only ‘grist’ but also ‘mills’ that are culturally inherited; through social interaction in the course of development, we not only acquire facts about the world and how to deal with it (grist), we also build the cognitive processes that make ‘fact inheritance’ possible (mills).

scholarly journals The cultural evolution of cultural evolution

2021 ◽  
Vol 376 (1828) ◽  
Author(s):  
Jonathan Birch ◽  
Cecilia Heyes
Keyword(s):  
Cultural Evolution ◽  
Self Assembly ◽  
Cultural Learning ◽  
Explicit Learning ◽  
Knowledge And Skills ◽  
Cultural Selection ◽  
Evolutionary Account ◽  
Learning Biases ◽  
Cumulative Cultural Evolution ◽  
Attentional Learning

What makes fast, cumulative cultural evolution work? Where did it come from? Why is it the sole preserve of humans? We set out a self-assembly hypothesis: cultural evolution evolved culturally. We present an evolutionary account that shows this hypothesis to be coherent, plausible, and worthy of further investigation. It has the following steps: (0) in common with other animals, early hominins had significant capacity for social learning; (1) knowledge and skills learned by offspring from their parents began to spread because bearers had more offspring, a process we call CS1 (or Cultural Selection 1); (2) CS1 shaped attentional learning biases; (3) these attentional biases were augmented by explicit learning biases (judgements about what should be copied from whom). Explicit learning biases enabled (4) the high-fidelity, exclusive copying required for fast cultural accumulation of knowledge and skills by a process we call CS2 (or Cultural Selection 2) and (5) the emergence of cognitive processes such as imitation, mindreading and metacognition—‘cognitive gadgets' specialized for cultural learning. This self-assembly hypothesis is consistent with archaeological evidence that the stone tools used by early hominins were not dependent on fast, cumulative cultural evolution, and suggests new priorities for research on ‘animal culture'. This article is part of the theme issue ‘Foundations of cultural evolution’.

scholarly journals The cultural evolution of cultural evolution

2020 ◽  
Author(s):  
Jonathan Birch ◽  
cecilia heyes
Keyword(s):  
Cultural Evolution ◽  
Self Assembly ◽  
Cultural Learning ◽  
Explicit Learning ◽  
Knowledge And Skills ◽  
Cultural Selection ◽  
Evolutionary Account ◽  
Learning Biases ◽  
Cumulative Cultural Evolution ◽  
Attentional Learning

What makes fast, cumulative cultural evolution work? Where did it come from? Why is it the sole preserve of humans? We set out a self-assembly hypothesis: cultural evolution evolved culturally. We present an evolutionary account that shows this hypothesis to be coherent, plausible, and worthy of further investigation. It has the following steps: (0) in common with other animals, early hominins had significant capacity for social learning; (1) knowledge and skills learned by offspring from their parents began to spread because bearers had more offspring, a process we call CS1 (or Cultural Selection 1); (2) CS1 shaped attentional learning biases; (3) these attentional biases were augmented by explicit learning biases (judgements about what should be copied from whom). Explicit learning biases enabled (4) the high-fidelity, exclusive copying required for fast cultural accumulation of knowledge and skills by a process we call CS2 (or Cultural Selection 2), and (5) the emergence of cognitive processes such as imitation, mindreading and metacognition – ‘cognitive gadgets’ specialised for cultural learning. This self-assembly hypothesis is consistent with archaeological evidence that the stone tools used by early hominins were not dependent on fast, cumulative cultural evolution, and suggests new priorities for research on ‘animal culture’.

scholarly journals Generative inference for cultural evolution

2018 ◽  
Vol 373 (1743) ◽  
pp. 20170056 ◽  
Author(s):  
Anne Kandler ◽  
Adam Powell
Keyword(s):  
Social Learning ◽  
Learning Strategies ◽  
Cultural Evolution ◽  
A Priori ◽  
Population Level ◽  
Theoretical Work ◽  
Interdisciplinary Studies ◽  
Learning Processes ◽  
Human Populations ◽  
Frequency Distributions

One of the major challenges in cultural evolution is to understand why and how various forms of social learning are used in human populations, both now and in the past. To date, much of the theoretical work on social learning has been done in isolation of data, and consequently many insights focus on revealing the learning processes or the distributions of cultural variants that are expected to have evolved in human populations. In population genetics, recent methodological advances have allowed a greater understanding of the explicit demographic and/or selection mechanisms that underlie observed allele frequency distributions across the globe, and their change through time. In particular, generative frameworks—often using coalescent-based simulation coupled with approximate Bayesian computation (ABC)—have provided robust inferences on the human past, with no reliance on a priori assumptions of equilibrium. Here, we demonstrate the applicability and utility of generative inference approaches to the field of cultural evolution. The framework advocated here uses observed population-level frequency data directly to establish the likely presence or absence of particular hypothesized learning strategies. In this context, we discuss the problem of equifinality and argue that, in the light of sparse cultural data and the multiplicity of possible social learning processes, the exclusion of those processes inconsistent with the observed data might be the most instructive outcome. Finally, we summarize the findings of generative inference approaches applied to a number of case studies. This article is part of the theme issue ‘Bridging cultural gaps: interdisciplinary studies in human cultural evolution’.

scholarly journals Blackboxing: social learning strategies and cultural evolution

2016 ◽  
Vol 371 (1693) ◽  
pp. 20150369 ◽  
Author(s):  
Cecilia Heyes
Keyword(s):  
Social Learning ◽  
Learning Strategies ◽  
Cognitive Processes ◽  
Cultural Evolution ◽  
Digital Natives ◽  
Artificial Agents ◽  
The Social ◽  
The Relationship ◽  
Social Learning Strategies ◽  
Better Than

Social learning strategies (SLSs) enable humans, non-human animals, and artificial agents to make adaptive decisions about when they should copy other agents, and who they should copy. Behavioural ecologists and economists have discovered an impressive range of SLSs, and explored their likely impact on behavioural efficiency and reproductive fitness while using the ‘phenotypic gambit’; ignoring, or remaining deliberately agnostic about, the nature and origins of the cognitive processes that implement SLSs. Here I argue that this ‘blackboxing' of SLSs is no longer a viable scientific strategy. It has contributed, through the ‘social learning strategies tournament', to the premature conclusion that social learning is generally better than asocial learning, and to a deep puzzle about the relationship between SLSs and cultural evolution. The puzzle can be solved by recognizing that whereas most SLSs are ‘planetary'—they depend on domain-general cognitive processes—some SLSs, found only in humans, are ‘cook-like'—they depend on explicit, metacognitive rules, such as copy digital natives . These metacognitive SLSs contribute to cultural evolution by fostering the development of processes that enhance the exclusivity, specificity, and accuracy of social learning.

Social Learning

2013 ◽  
Author(s):  
William Hoppitt ◽  
Kevin N. Laland
Keyword(s):  
Spatial Distribution ◽  
Social Learning ◽  
Learning Strategies ◽  
Cognitive Neuroscience ◽  
Cultural Evolution ◽  
Experimental Psychology ◽  
Academic Disciplines ◽  
Mathematical Methods ◽  
Indispensable Tool ◽  
Social Learning Strategies

Many animals, including humans, acquire valuable skills and knowledge by copying others. Scientists refer to this as social learning. It is one of the most exciting and rapidly developing areas of behavioral research and sits at the interface of many academic disciplines, including biology, experimental psychology, economics, and cognitive neuroscience. This book provides a comprehensive, practical guide to the research methods of this important emerging field. It defines the mechanisms thought to underlie social learning and demonstrate how to distinguish them experimentally in the laboratory. It presents techniques for detecting and quantifying social learning in nature, including statistical modeling of the spatial distribution of behavior traits. It also describes the latest theory and empirical findings on social learning strategies, and introduces readers to mathematical methods and models used in the study of cultural evolution. This book is an indispensable tool for researchers and an essential primer for students.

Focused Tasks, Mental Actions and Second Language Learning. Cognitive and Connectionist Accounts of Task Effectiveness

2006 ◽  
Vol 152 ◽  
pp. 35-53 ◽  
Author(s):  
Machteld Moonen ◽  
Rick de Graaff ◽  
Gerard Westhoff
Keyword(s):  
Second Language ◽  
Language Learning ◽  
Learning Strategies ◽  
Cognitive Processes ◽  
Second Language Learning ◽  
Theoretical Framework ◽  
Future Research ◽  
Depth Of Processing ◽  
Mental Actions ◽  
Involvement Load Hypothesis

Abstract This paper presents a theoretical framework to estimate the effectiveness of second language tasks in which the focus is on the acquisition of new linguistic items, such as vocabulary or grammar, the so-called focused tasks (R. Ellis, 2003). What accounts for the learning impact offocused tasks? We shall argue that the task-based approach (e.g. Skehan, 1998, Robinson, 2001) does not provide an in-depth account of how cognitive processes, elicited by a task, foster the acquisition of new linguistic elements. We shall then review the typologies of cognitive processes derived from research on learning strategies (Chamot & O'Malley, 1994), from the involvement load hypothesis (Laufer & Hulstijn, 2001), from the depth of processing hypothesis (Craik & Lockhart, 1972) and from connectionism (e.g Broeder & Plunkett, 1997; N. Ellis, 2003). The combined insights of these typologies form the basis of the multi-feature hypothesis, which predicts that retention and ease of activation of new linguistic items are improved by mental actions which involve a wide variety of different features, simultaneously and frequently. A number of implications for future research shall be discussed.

scholarly journals Atheists

2017 ◽  
Author(s):  
Sarah R. Schiavone ◽  
Will M Gervais
Keyword(s):  
Cognitive Processes ◽  
Scientific Progress ◽  
Psychological Research ◽  
Cultural Learning ◽  
Negative Attitudes ◽  
Complex Interactions ◽  
Cultural Origins ◽  
Made In ◽  
Do So

Atheists represent an inconspicuous minority, identifiable only by their disbelief in God(s). Despite being highly stigmatized and disliked, until recent scientific endeavors, little has been known about this group including why they don’t believe, how many people are atheists, and why they trigger intense reactions. Thus, this paper aims to synthesize what is known about atheists (so far), and to help explain the widespread negative attitudes and prejudice towards atheists; the possible cognitive, motivational, and cultural origins of disbelief; and the unique challenges facing the study of religious disbelievers. To do so, we will explore current findings in psychological research on atheism by considering the complex interactions of cultural learning, motivations, and core cognitive processes. Although significant scientific progress has been made in understanding the factors underlying atheism, there remains much to be explored in the domain of religious disbelief.

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