Kenny Smith

Cumulative cultural evolution in the laboratory: An experimental approach to the origins of structure in human language

We introduce an experimental paradigm for studying the cumulative cultural evolution of language. In doing so we provide the first experimental validation for the idea that cultural transmission can lead to the appearance of design without a designer. Our experiments involve the iterated learning of artificial languages by human participants. We show that languages transmitted culturally evolve in such a way as to maximize their own transmissibility: over time, the languages in our experiments become easier to learn and increasingly structured. Furthermore, this structure emerges purely as a consequence of the transmission of language over generations, without any intentional design on the part of individual language learners. Previous computational and mathematical models suggest that iterated learning provides an explanation for the structure of human language and link particular aspects of linguistic structure with particular constraints acting on language during its transmission. The experimental work presented here shows that the predictions of these models, and models of cultural evolution more generally, can be tested in the laboratory.

Eliminating unpredictable variation through iterated learning.

Human languages may be shaped not only by the (individual psychological) processes of language acquisition, but also by population-level processes arising from repeated language learning and use. One prevalent feature of natural languages is that they avoid unpredictable variation. The current work explores whether linguistic predictability might result from a process of iterated learning in simple diffusion chains of adults. An iterated artificial language learning methodology was used, in which participants were organised into diffusion chains: the first individual in each chain was exposed to an artificial language which exhibited unpredictability in plural marking, and subsequent learners were exposed to the language produced by the previous learner in their chain. Diffusion chains, but not isolate learners, were found to cumulatively increase predictability of plural marking by lexicalising the choice of plural marker. This suggests that such gradual, cumulative population-level processes offer a possible explanation for regularity in language.

Compression and communication in the cultural evolution of linguistic structure

Language exhibits striking systematic structure. Words are composed of combinations of reusable sounds, and those words in turn are combined to form complex sentences. These properties make language unique among natural communication systems and enable our species to convey an open-ended set of messages. We provide a cultural evolutionary account of the origins of this structure. We show, using simulations of rational learners and laboratory experiments, that structure arises from a trade-off between pressures for compressibility (imposed during learning) and expressivity (imposed during communication). We further demonstrate that the relative strength of these two pressures can be varied in different social contexts, leading to novel predictions about the emergence of structured behaviour in the wild.

Cultural evolution: implications for understanding the human language faculty and its evolution.

Human language is unique among the communication systems of the natural world: it is socially learned and, as a consequence of its recursively compositional structure, offers open-ended communicative potential. The structure of this communication system can be explained as a consequence of the evolution of the human biological capacity for language or the cultural evolution of language itself. We argue, supported by a formal model, that an explanatory account that involves some role for cultural evolution has profound implications for our understanding of the biological evolution of the language faculty: under a number of reasonable scenarios, cultural evolution can shield the language faculty from selection, such that strongly constraining language-specific learning biases are unlikely to evolve. We therefore argue that language is best seen as a consequence of cultural evolution in populations with a weak and/or domain-general language faculty.

Cross-Situational Learning: An Experimental Study of Word-Learning Mechanisms

Cross-situational learning is a mechanism for learning the meaning of words across multiple exposures, despite exposure-by-exposure uncertainty as to the word’s true meaning. We present experimental evidence showing that humans learn words effectively using cross-situational learning, even at high levels of referential uncertainty. Both overall success rates and the time taken to learn words are affected by the degree of referential uncertainty, with greater referential uncertainty leading to less reliable, slower learning. Words are also learned less successfully and more slowly if they are presented interleaved with occurrences of other words, although this effect is relatively weak. We present additional analyses of participants’ trial-by-trial behavior showing that participants make use of various cross-situational learning strategies, depending on the difficulty of the word-learning task. When referential uncertainty is low, participants generally apply a rigorous eliminative approach to cross-situational learning. When referential uncertainty is high, or exposures to different words are interleaved, participants apply a frequentist approximation to this eliminative approach. We further suggest that these two ways of exploiting cross-situational information reside on a continuum of learning strategies, underpinned by a single simple associative learning mechanism.

Iterated learning and the evolution of language

Iterated learning describes the process whereby an individual learns their behaviour by exposure to another individuals behaviour, who themselves learnt it in the same way. It can be seen as a key mechanism of cultural evolution. We review various methods for understanding how behaviour is shaped by the iterated learning process: computational agent-based simulations; mathematical modelling; and laboratory experiments in humans and non-human animals. We show how this framework has been used to explain the origins of structure in language, and argue that cultural evolution must be considered alongside biological evolution in explanations of language origins.

Learning Times for Large Lexicons Through Cross-Situational Learning

Cross-situational learning is a mechanism for learning the meaning of words across multiple exposures, despite exposure-by-exposure uncertainty as to a words true meaning. Doubts have been expressed regarding the plausibility of cross-situational learning as a mechanism for learning human-scale lexicons in reasonable timescales under the levels of referential uncertainty likely to confront real word learners. We demonstrate mathematically that cross-situational learning facilitates the acquisition of large vocabularies despite significant levels of referential uncertainty at each exposure, and we provide estimates of lexicon learning times for several cross-situational learning strategies. This model suggests that cross-situational word learning cannot be ruled out on the basis that it predicts unreasonably long lexicon learning times. More generally, these results indicate that there is no necessary link between the ability to learn individual words rapidly and the capacity to acquire a large lexicon.

Auditory sequence processing reveals evolutionarily conserved regions of frontal cortex in macaques and humans

An evolutionary account of human language as a neurobiological system must distinguish between human-unique neurocognitive processes supporting language and evolutionarily conserved, domain-general processes that can be traced back to our primate ancestors. Neuroimaging studies across species may determine whether candidate neural processes are supported by homologous, functionally conserved brain areas or by different neurobiological substrates. Here we use functional magnetic resonance imaging in Rhesus macaques and humans to examine the brain regions involved in processing the ordering relationships between auditory nonsense words in rule-based sequences. We find that key regions in the human ventral frontal and opercular cortex have functional counterparts in the monkey brain. These regions are also known to be associated with initial stages of human syntactic processing. This study raises the possibility that certain ventral frontal neural systems, which play a significant role in language function in modern humans, originally evolved to support domain-general abilities involved in sequence processing.

Cultural Evolution and Perpetuation of Arbitrary Communicative Conventions in Experimental Microsocieties

Previous studies have shown that iconic graphical signs can evolve into symbols through repeated usage within dyads and interacting communities. Here we investigate the evolution of graphical signs over chains of participants. In these chains (or “replacement microsocieties”), membership of an interacting group changed repeatedly such that the most experienced members were continually replaced by naïve participants. Signs rapidly became symbolic, such that they were mutually incomprehensible across experienced members of different chains, and new entrants needed to learn conventionalised meanings. An objective measure of graphical complexity (perimetric complexity) showed that the signs used within the microsocieties were becoming progressively simplified over successive usage. This is the first study to show that the signs that evolve in graphical communication experiments can be transmitted to, and spontaneously adopted by, naïve participants. This provides critical support for the view that human communicative symbols could have evolved culturally from iconic representations.

Natural selection and cultural selection in the evolution of communication

It has been postulated that aspects of human language are both genetically and culturally transmitted. How might these processes interact to determine the structure of language? An agent-based model designed to study gene-culture interactions in the evolution of communication is introduced. This model shows that cultural selection resulting from learner biases can be crucial in determining the structure of communication systems transmitted through both genetic and cultural processes. Furthermore, the learning bias that leads to the emergence of optimal communication in the model resembles the learning bias brought to the task of language acquisition by human infants. This suggests that the iterated application of such human learning biases may explain much of the structure of human language.