Human language looms large in the emergence and evolution of graphic codes. Here, I argue that language not only acts as a strong constraint on graphic codes, but it is also a precondition for their emergence and their evolution as computational devices.

In his profound discussion, Sterelny draws out common themes in the contributions to this topic: selective drivers in the coevolution of cognition and culture, the role of language in it, characteristics of cumulative cultural evolution, and issues of testability. He highlights the growing body of evidence for positive feedback mechanisms in cultural evolution, but also notes that progress is piecemeal, calling for more cross‐border work between cognitive science and research on cultural evolution.

An ideography is a general-purpose code made of pictures that do not encode language, which can be used autonomously – not just as a mnemonic prop – to encode information on a broad range of topics. Why are viable ideographies so hard to find? I contend that self-sufficient graphic codes need to be narrowly specialized. Writing systems are only an apparent exception: At their core, they are notations of a spoken language. Even if they also encode nonlinguistic information, they are (...) useless to someone who lacks linguistic competence in the encoded language or a related one. The versatility of writing is thus vicarious: Writing borrows it from spoken language. Why is it so difficult to build a fully generalist graphic code? The most widespread answer points to a learnability problem. We possess specialized cognitive resources for learning spoken language, but lack them for graphic codes. I argue in favor of a different account: What is difficult about graphic codes is not so much learning or teaching them as getting every user to learn and teach the same code. This standardization problem does not affect spoken or signed languages as much. Those are based on cheap and transient signals, allowing for easy online repairing of miscommunication, and require face-to-face interactions where the advantages of common ground are maximized. Graphic codes lack these advantages, which makes them smaller in size and more specialized. (shrink)

Cognitive Science, Volume 46, Issue 2, February 2022.

The amount of information conveyed by linguistic conventions depends on their precision, yet the codes that humans and other animals use to communicate are quite ambiguous: they may map several vague meanings to the same symbol. How does semantic precision evolve, and what are the constraints that limit it? We address this question using a multiplayer gaming app, where individuals communicate with one another in a scaled-up referential game. Here, the goal is for a sender to use black and white (...) symbols to communicate colors. We expected that the players’ mappings between symbols and colors would grow more specific over time, through a selection process whereby precise mappings are preferentially copied. We found that players become increasingly more precise in their use of symbols over the course of their interactions. This trend did not, however, result from selective copying of precise mappings. We explore the implications of this result for the study of lexical ambiguity, Zipf's Law of Meaning, and disagreements over semantic conventions. (shrink)

There is an extensive literature on the usage of Blissymbolics in augmentative and alternative communication that contradicts Morin's contention that it fails as an ideography. Morin's notion of “standardization” (target article, sect. X, para. X) is at odds with the highly developed understanding of this notion in linguistics. What Morin seems to have in mind corresponds to the notion of emergence in iterative and multiagent models of language learning.

Evidence of cultural influences on cognition is accumulating, but untangling these cultural influences from one another or from non-cultural influences has remained a challenging task. As between-group differences are neither a sufficient nor a necessary indicator of cultural impact, cross-cultural comparisons in isolation are unable to furnish any cogent conclusions. This shortfall can be compensated by taking a diachronic perspective that focuses on the role of culture for the emergence and evolution of our cognitive abilities. Three strategies for reconstructing early (...) human cognition are presented: the chaîne opératoire approach and its extension to brain-imaging studies, large-scale extrapolations, and phylogenetic comparative methods. While these strategies are reliant on our understanding of present-day cognition, they conversely also have the potential to advance this understanding in fundamental ways. (shrink)

Since the emergence of our species at least, natural selection based on genetic variation has been replaced by culture as the major driving force in human evolution. It has made us what we are today, by ratcheting up cultural innovations, promoting new cognitive skills, rewiring brain networks, and even shifting gene distributions. Adopting an evolutionary perspective can therefore be highly informative for cognitive science in several ways: It encourages us to ask grand questions about the origins and ramifications of our (...) cognitive abilities; it equips us with the means to investigate, explain, and understand key dimensions of cognition; and it allows us to recognize the continued and ubiquitous workings of culture and evolution in everyday instances of cognitive behavior. Taking advantage of this reorientation presupposes a shift in focus, though, from human cognition as a general, homogenous phenomenon to the appreciation of cultural diversity in cognition as an invaluable source of data. (shrink)

Beller, Bender, & Jordan [Intro]. Which factors have triggered, constrained, or shaped the course of cognitive evolution is a question of key interest to cognitive science. The topic introduced here highlights the relevance of culture as a driving force in this process. It provides an overview of current empirical and theoretical work leading this field, and it investigates the potential for integrating multiple perspectives across several timescales and levels of analysis.