Hannah Cornish

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.

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.

The Cultural Evolution of Structured Languages in an Open-Ended, Continuous World

Abstract Language maps signals onto meanings through the use of two distinct types of structure. First, the space of meanings is discretized into categories that are shared by all users of the language. Second, the signals employed by the language are compositional: The meaning of the whole is a function of its parts and the way in which those parts are combined. In three iterated learning experiments using a vast, continuous, open‐ended meaning space, we explore the conditions under which both structured categories and structured signals emerge ex nihilo. While previous experiments have been limited to either categorical structure in meanings or compositional structure in signals, these experiments demonstrate that when the meaning space lacks clear preexisting boundaries, more subtle morphological structure that lacks straightforward compositionality—as found in natural languages—may evolve as a solution to joint pressures from learning and communication.

Identifying innovation in laboratory studies of cultural evolution: rates of retention and measures of adaptation

In recent years, laboratory studies of cultural evolution have become increasingly prevalent as a means of identifying and understanding the effects of cultural transmission on the form and functionality of transmitted material. The datasets generated by these studies may provide insights into the conditions encouraging, or inhibiting, high rates of innovation, as well as the effect that this has on measures of adaptive cultural change. Here we review recent experimental studies of cultural evolution with a view to elucidating the role of innovation in generating observed trends. We first consider how tasks are presented to participants, and how the corresponding conceptualization of task success is likely to influence the degree of intent underlying any deviations from perfect reproduction. We then consider the measures of interest used by the researchers to track the changes that occur as a result of transmission, and how these are likely to be affected by differing rates of retention. We conclude that considering studies of cultural evolution from the perspective of innovation provides us with valuable insights that help to clarify important differences in research designs, which have implications for the likely effects of variation in retention rates on measures of cultural adaptation.

Sequence memory constraints give rise to language-like structure through iterated learning

Human language is composed of sequences of reusable elements. The origins of the sequential structure of language is a hotly debated topic in evolutionary linguistics. In this paper, we show that sets of sequences with language-like statistical properties can emerge from a process of cultural evolution under pressure from chunk-based memory constraints. We employ a novel experimental task that is non-linguistic and non-communicative in nature, in which participants are trained on and later asked to recall a set of sequences one-by-one. Recalled sequences from one participant become training data for the next participant. In this way, we simulate cultural evolution in the laboratory. Our results show a cumulative increase in structure, and by comparing this structure to data from existing linguistic corpora, we demonstrate a close parallel between the sets of sequences that emerge in our experiment and those seen in natural language.

The Effects of Generation Turnover and Interlocutor Negotiation on Linguistic Structure

Cultural transmission has a key impact on the evolution of linguistic structure (Kirby, Cornish & Smith, 2008). During transmission, new individuals learn the conventions of the language through observation and participation in communicative interactions in context. We present a series of experiments which disentangle the role of generation turnover, or new minds coming into the linguistic community (e.g. Kirby et al. 2008) from that of negotiation of shared form-meaning conventions during interlocutor interaction (studied in graphical, but not linguistic, systems by e.g. Fay et al. 2007, Galantucci 2005). In the experimental task, two interlocutors played a communicative cooperative game using an artificial miniature language. Players were trained on a random language, which they then used to ask each other for specific objects; they scored a point for each successful interaction. The language produced by one (randomly selected) participant was then used as training data for the following training-and-usage round. We manipulated generation turnover: in dyads, two participants played six training-and-usage rounds; in chains, six different participant pairs played one round each. We also manipulated negotiation. In the negotiation condition there were two human players; in the no-negotiation condition, one of the players was replaced with a simulated computer agent who had perfect memory (i.e. it always used the training language without errors, and never offered or adopted suggestions during usage). The training languages in this condition came from the human player. We examined the effects of generation turnover and negotiation on the systematic structure of the resulting languages (measured using the technique described in Kirby et al., 2008) and found a significant effect of both factors. Structure increased over the six rounds in chains, but not in dyads. Looking at chains only, the level of structure at the final round was markedly higher when there was negotiation between two interlocutors than when a single participant

EVOLUTION OF TENSE AND ASPECT

One cognitive domain that may have influenced, and perhaps even shaped, the evolution of language is mental time travel the ability to mentally relive events in the past (episodic memory) or imagine events in the future. Language structure has evolved to express different points in time, including past, present and future, and to make other temporal distinctions, such as action completed versus action ongoing. We examine the activation of Broca’s and Wernicke’s area in the evolution of tense and aspect of English using near-infrared spectroscopy. We demonstrate that the activation of the core brain system used in remembering the past and imagining the future induced the evolution of tense and aspect, which do not present themselves as separate categories and are interwoven in grammatical systems in that one and the same grammatical form may combine temporal and aspectual elements. After categorization of the periphrastic constructions of progressive and perfective, and auxiliaries to denote future tense, aspect is specialized to the left hemisphere, and the distinction of the forms between present, past and future tense caused less activation of the core networks of the brain. Here we can see the interaction between brain and language.

The cumulative cultural evolution of category structure in an infinite meaning space

Current iterated learning experiments use meaning spaces that are discrete, finite, prespecified, and low-dimensional. Such meaning spaces are poor representations of the world. For this reason, we have conducted two experiments to look at the cumulative cultural evolution of category structure in an infinite meaning space. In the first experiment, the number of words used to describe the stimuli collapses dramatically after only a few generations. Within a few more generations, a system emerges that arbitrarily divides the space into a small number of categories pertaining primarily to the size and shape of the stimuli. In the second experiment, we apply an artificial constraint which prevents the size of the languages from collapsing. This constraint was implemented to model the pressure for expressivity that exists in languages when they are used functionally for communication. We predicted that this would allow compositional structure to emerge so that the space could be carved up in more finely grained and/or higher dimensional ways using a compressible linguistic system. However, there was little sign of compositionality emerging under the parameters of this experiment. Although the meaning space presented here is a simple one, we hope that this project represents a first step towards thinking about how iterated learning experiments deal with the problem of discrete infinity. We briefly discuss the background literature, then present the methods and results for this project, and end with some discussion about how the results relate to our research questions.