Hunter Gentry

We use language to communicate our thoughts. But is language merely the expression of thoughts, which are themselves produced by other, nonlinguistic parts of our minds? Or does language play a more transformative role in human cognition, allowing us to have thoughts that we otherwise could (or would) not have? Recent developments in artificial intelligence (AI) and cognitive science have reinvigorated this old question. We argue that language may hold the key to the emergence of both more general AI systems and central aspects of human intelligence. We highlight two related properties of language that make it such a powerful tool for developing domain-general abilities. First, language offers compact representations that make it easier to represent and reason about many abstract concepts (e.g., exact numerosity). Second, these compressed representations are the iterated output of collective minds. In learning a language, we learn a treasure trove of culturally evolved abstractions. Taken together, these properties mean that a sufficiently powerful learning system exposed to language—whether biological or artificial—learns a compressed model of the world, reverse engineering many of the conceptual and causal structures that support human (and human-like) thought.

Some embodied theories of concepts state that concepts are represented in a sensorimotor manner, typically via simulation in sensorimotor cortices. Fred Adams (2010) has advanced an empirical argument against embodied concepts reasoning as follows. If concepts are embodied, then patients with certain sensorimotor impairments should perform worse on categorization tasks involving those concepts. Adams cites a study with Moebius Syndrome patients that shows typical categorization performance in face-based emotion recognition. Adams concludes that their typical performance shows that embodiment is false. Moebius patients must draw on amodal (non-embodied) emotion concepts. In this paper, I review face-based emotion recognition studies with Moebius patients yielding conflicting results and diagnose these conflicts as a difference in experimental design. When emotion labels are provided, patients have typical performance, but when labels are not provided patients are severely deficient. I then show how an embodied, psychological constructionist view of emotions predicts and explains these performance differences. The upshot is that embodied theories of concepts are vindicated.