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A recent issue of Topics in Cognitive Science featured 11 thoughtful commentaries responding to our article “What happened to cognitive science?” (Núñez et al., 2019). Here, we identify several themes that arose in those commentaries and respond to each. Crucial to understanding our original article is the fundamental distinction between multidisciplinary and interdisciplinary endeavors: Cognitive science began (and has stayed) as multidisciplinary but has failed to move on to form a cohesive interdisciplinary field. We clarify and elaborate our original argument and reiterate the importance of a data‐driven evaluation of the current status of the field, which exhibits a marked disciplinary imbalance, a lack of a coherent conceptual core, and a striking absence of a consistent curriculum in the institutions that grant degrees in this domain. Half a century after the creation of cognitive science, it may now be a good time to revisit goals and visions for how to best approach the ever‐fascinating scientific study of the mind(s).

It is often claimed that languages with more non-native speakers tend to become morphologically simpler, presumably because non-native speakers learn the language imperfectly. A growing number of studies support this claim, but there is a dearth of experiments that evaluate it and the suggested explanatory mechanisms. We performed a large-scale experiment which directly tested whether imperfect language learning simplifies linguistic structure and whether this effect is amplified by iterated learning. Members of 45 transmission chains, each consisting of 10 one-person generations, learned artificial mini-languages and transmitted them to the next generation. Manipulating the learning time showed that when transmission chains contained generations of imperfect learners, the decrease in morphological complexity was more pronounced than when the chains did not contain imperfect learners. The decrease was partial (complexity did not get fully eliminated) and gradual (caused by the accumulation of small simplifying changes). Simplification primarily affected double agent-marking, which is more redundant, arguably more difficult to learn and less salient than other features. The results were not affected by the number of the imperfect-learner generations in the transmission chains. Thus, we provide strong experimental evidence in support of the hypothesis that iterated imperfect learning leads to language simplification.

This chapter investigates how morphological complexity is related to socioecological parameters. Results of an iterated artificial language learning experiment are reported, with the focus on how two facets of complexity, overspecification and irregularity, change over time. The presence of imperfect learners in a transmission chain leads to a much stronger decrease in morphological overspecification in the language. Overspecification, however, does not usually get fully eliminated, and its partial decrease often leads to increase in irregularity, thus making languages simpler in one respect, but more complex in another. Additionally, higher irregularity decreases the learnability of the language, and this effect is stronger for imperfect learners compared to normal learners. Thus, to reach a fully simplified state, languages have to pass a suboptimal state (low overspecification, high irregularity), where they often get stuck.

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