In their recent book, Ladyman and Wiesner (What is a complex system?, Yale University Press, 2020) delineate the bounds of the exciting interdisciplinary field of complexity science. In this work, they provide examples of generally accepted complex systems and common features which these possess to varying degrees. In this paper, I plan to extend their list to include the formal study of natural language, i.e. linguistics. In fact, I will argue that language exhibits many of the hallmarks of a complex (...) system, specifically a complex biological system. Thus, my aim is to advocate contra the the ‘Minimalist Program’ (Chomsky, The minimalist program, MIT Press, Cambridge, 1995), which motivates simple underlying mechanisms (i.e. Merge) in their idealisations, that biolinguistics should embrace a ‘Maximalist Program’ in which multiple subfields contribute component explanations to an emerging whole. (shrink)

To what degree can language be acquired from linguistic input alone? This question has vexed scholars for millennia and is still a major focus of debate in the cognitive science of language. The complexity of human language has hampered progress because studies of language–especially those involving computational modeling–have only been able to deal with small fragments of our linguistic skills. We suggest that the most recent generation of Large Language Models (LLMs) might finally provide the computational tools to determine empirically (...) how much of the human language ability can be acquired from linguistic experience. LLMs are sophisticated deep learning architectures trained on vast amounts of natural language data, enabling them to perform an impressive range of linguistic tasks. We argue that, despite their clear semantic and pragmatic limitations, LLMs have already demonstrated that human-like grammatical language can be acquired without the need for a built-in grammar. Thus, while there is still much to learn about how humans acquire and use language, LLMs provide full-fledged computational models for cognitive scientists to empirically evaluate just how far statistical learning might take us in explaining the full complexity of human language. (shrink)

Howson famously argues that the no-miracles argument, stating that the success of science indicates the approximate truth of scientific theories, is a base rate fallacy: it neglects the possibility of an overall low rate of true scientific theories. Recently a number of authors has suggested that the corresponding probabilistic reconstruction is unjust, as it concerns only the success of one isolated theory. Dawid and Hartmann, in particular, suggest to use the frequency of success in some field of research \ to (...) infer a probability of truth for a new theory from \. I here shed doubts on the justification of this and similar moves and suggest a way to directly bound the probability of truth. As I will demonstrate, my bound can become incompatible with the assumption specific testing and Dawid and Hartmann’s estimate for success. (shrink)

Recent theoretical work in developmental psychology suggests that humans are predisposed to align their mental states with those of other individuals. One way this manifests is in cooperative communication ; that is, intentional communication aimed at aligning individuals’ mental states with respect to events in their shared environment. This idea has received strong empirical support. The purpose of this paper is to extend this account by proposing an integrative model of the biobehavioral dynamics of cooperative communication. Our formulation is based (...) on active inference. Active inference suggests that action-perception cycles operate to minimize uncertainty and optimize an individual’s internal model of the world. We propose that humans are characterized by an evolved adaptive prior belief that their mental states are aligned with, or similar to, those of conspecifics (i.e., that ‘we are the same sort of creature, inhabiting the same sort of niche’). The use of cooperative communication emerges as the principal means to gather evidence for this belief, allowing for the development of a shared narrative that is used to disambiguate interactants’ (hidden and inferred) mental states. Thus, by using cooperative communication, individuals effectively attune to a hermeneutic niche composed, in part, of others’ mental states; and, reciprocally, attune the niche to their own ends via epistemic niche construction. This means that niche construction enables features of the niche to encode precise, reliable cues about the deontic or shared value of certain action policies (e.g., the utility of using communicative constructions to disambiguate mental states, given expectations about shared prior beliefs). In turn, the alignment of mental states (prior beliefs) enables the emergence of a novel, contextualizing scale of cultural dynamics that encompasses the actions and mental states of the ensemble of interactants and their shared environment. The dynamics of this contextualizing layer of cultural organization feedback, across scales, to constrain the variability of the prior expectations of the individuals who constitute it. Our theory additionally builds upon the active inference literature by introducing a new set of neurobiologically plausible computational hypotheses for cooperative communication. We conclude with directions for future research. (shrink)

A word often expresses many different morphological functions. Which part of a word contributes to which part of the overall meaning is not always clear, which raises the question as to how such functions are learned. While linguistic studies tacitly assume the co-occurrence of cues and outcomes to suffice in learning these functions (Baer-Henney, Kügler, & van de Vijver, 2015; Baer-Henney & van de Vijver, 2012), error-driven learning suggests that contingency rather than contiguity is crucial (Nixon, 2020; Ramscar, Yarlett, Dye, (...) Denny, & Thorpe, 2010). In error-driven learning, cues gain association strength if they predict a certain outcome, and they lose strength if the outcome is absent. This reduction of association strength is called unlearning. So far, it is unclear if such unlearning has consequences for cue–outcome associations beyond the ones that get reduced. To test for such consequences of unlearning, we taught participants morphophonological patterns in an artificial language learning experiment. In one block, the cues to two morphological outcomes—plural and diminutive—co-occurred within the same word forms. In another block, a single cue to only one of these two outcomes was presented in a different set of word forms. We wanted to find out, if participants unlearn this cue's association with the outcome that is not predicted by the cue alone, and if this allows the absent cue to be associated with the absent outcome. Our results show that if unlearning was possible, participants learned that the absent cue predicts the absent outcome better than if no unlearning was possible. This effect was stronger if the unlearned cue was more salient. This shows that unlearning takes place even if no alternative cues to an absent outcome are provided, which highlights that learners take both positive and negative evidence into account—as predicted by domain general error-driven learning. (shrink)

Two of the main theoretical approaches to the evolution of language are biolinguistics and usage-based approaches. Both are often conceptualized as belonging to seemingly irreconcilable “camps.” Biolinguistic approaches assume that the ability to acquire language is based on a language-specific genetic foundation. Usage-based approaches, on the other hand, stress the importance of domain-general cognitive capacities, social cognition, and interaction. However, there have been a number of recent developments in both paradigms which suggest that biolinguistic and usage-based approaches are actually moving (...) closer together. For example, theoretical advancements such as evo-devo and complex adaptive system theory have gained traction in the language sciences, leading to changed conceptions of issues like the relative influence of “nature” and “nurture.” In this paper, we outline points of convergence between current minimalist biolinguistic and usage-based approaches regarding four contentious issues: (1) modularity and domain specificity; (2) innateness and development; (3) cultural and biological evolution; and (4) knowledge of language and its description. We show that across both paradigms, researchers have come to increasingly embrace more complex views of these issues. They also have come to appreciate the view that biological and cultural evolution are closely intertwined, which lead to an increased amount of common ground between minimalist biolinguistics and usage-based approaches. (shrink)

The article reconstructs the main lines of three hypotheses in the current literature concerning the evolutionary pace which characterized the natural history of human language: the “continuist” and gradualist perspective, the “discontinuist” and evolution-free perspective, and the “punctuationist” view. This current debate appears to have a long history, which starts at least from Darwin’s time. The article highlights the similarities between the old and the modern debates in terms of history of ideas, and it shows the current limits of each (...) of these perspectives. In the final part, we present an alternative approach which considers human language not as a single trait, but as the result of a mosaic of different elements, some of which recently evolved, and some others gradually evolved and phylogenetically ancient. When matched with a tree thinking and comparative perspective, this view suggests that expressions of symbolic and linguistic behaviors in other human species could have preceded the more complex and systematic behaviors showed by Homo sapiens. (shrink)

For decades, interdisciplinary research efforts have accumulated insights that diminish the significance of the classic nature versus nurture dichotomy, instead calling for a nuanced, multifactorial approach to ontogeny. Similarly, the role of genes in both phylogeny and ontogeny, once seen as rather deterministic, is now conceptualized as highly dependent on environmental factors, including behavior. Linguistic theories have, in principle, made an effort to incorporate these changing views. However, the central claim of the given paper is that this apparent compliance with (...) biological insights remains superficial. As such, considerable disconnects between linguistic theory and what is known about the biological underpinnings of complex traits persist, negatively impacting pertinent views on language acquisition, language universals and the evolution of language. Given the breadth of these fields of study, the aim of this paper is to tackle the root of the problem: It begins by sketching out linguistic nativism as conceptualized within generativism, pointing to aspects within this position that stand in conflict with the interdisciplinary literature. It will then review select areas of research in a succinct manner in order to substantiate the criticism and characterize the counterposition as found within the biological sciences. The paper will culminate in addressing these disconnects on conceptual grounds, i.e. invoking the term emergence as employed in neuroscience as a possible means to reconcile those biological insights with linguistic nativism. (shrink)