Toward Integrative Dynamic Models for Adaptive Perspective Taking

Multi-Level Linguistic Alignment in a Dynamic Collaborative Problem-Solving Task

Cocreating meaning in collaboration is challenging. Success is often determined by people's abilities to coordinate their language to converge upon shared mental representations. Here we explore one set of low-level linguistic behaviors, linguistic alignment, that both emerges from, and facilitates, outcomes of high-level convergence. Linguistic alignment captures the ways people reuse, that is, "align to," the lexical, syntactic, and semantic forms of others' utterances. Our focus is on the temporal change of multi-level linguistic alignment, as well as how alignment is related to communicative outcomes within a unique collaborative problem-solving paradigm. The primary task, situated within a virtual educational video game, requires creative thinking between three people where the paths for possible solutions are highly variable. We find that over time interactions are marked by decreasing lexical and syntactic alignment, with a trade-off of increasing semantic alignment. However, greater semantic alignment does not translate into better team performance. Overall, these findings provide greater clarity on the role of linguistic coordination within complex and dynamic collaborative problem-solving tasks.

What is retained about common ground? Distinct effects of linguistic and visual co-presence

Common ground can be mutually established between conversational partners in several ways. We examined whether the modality (visual or linguistic) with which speakers share information with their conversational partners results in memory traces that affect subsequent references addressed to a particular partner. In 32 triads, directors arranged a set of tangram cards with one matcher and then with another, but in different modalities, sharing some cards only linguistically (by describing cards the matcher couldn't see), some only visually (by silently showing them), some both linguistically and visually, and others not at all. Then directors arranged the cards again in separate rounds with each matcher. The modality with which they previously established common ground about a particular card with a particular matcher (e.g., linguistically with one partner and visually with the other) affected subsequent referring: References to cards previously shared only visually included more idea units, words, and reconceptualizations than those shared only linguistically, which in turn included more idea units, words, and reconceptualizations than those shared both linguistically and visually. Moreover, speakers were able to tailor references to the same card appropriately to the distinct modality shared with each addressee. Such gradient, partner-specific adaptation during re-referring suggests that memory encodes rich-enough representations of multimodal shared experiences to effectively cue relevant constraints about the perceptual conditions under which speakers and addressees establish common ground.

Do People Regard Robots as Human-Like Social Partners? Evidence From Perspective-Taking in Spatial Descriptions

Spatial communications are essential to the survival and social interaction of human beings. In science fiction and the near future, robots are supposed to be able to understand spatial languages to collaborate and cooperate with humans. However, it remains unknown whether human speakers regard robots as human-like social partners. In this study, human speakers describe target locations to an imaginary human or robot addressee under various scenarios varying in relative speaker–addressee cognitive burden. Speakers made equivalent perspective choices to human and robot addressees, which consistently shifted according to the relative speaker–addressee cognitive burden. However, speakers’ perspective choice was only significantly correlated to their social skills when the addressees were humans but not robots. These results suggested that people generally assume robots and humans with equal capabilities in understanding spatial descriptions but do not regard robots as human-like social partners.

Interacting Timescales in Perspective-Taking

Through theoretical discussion, literature review, and a computational model, this paper poses a challenge to the notion that perspective-taking involves a fixed architecture in which particular processes have priority. For example, some research suggests that egocentric perspectives can arise more quickly, with other perspectives (such as of task partners) emerging only secondarily. This theoretical dichotomy-between fast egocentric and slow other-centric processes-is challenged here. We propose a general view of perspective-taking as an emergent phenomenon governed by the interplay among cognitive mechanisms that accumulate information at different timescales. We first describe the pervasive relevance of perspective-taking to cognitive science. A dynamical systems model is then introduced that explicitly formulates the timescale interaction proposed. This model illustrates that, rather than having a rigid time course, perspective-taking can be fast or slow depending on factors such as task context. Implications are discussed, with ideas for future empirical research.

Memory and Common Ground Processes in Language Use

During communication, we form assumptions about what our communication partners know and believe. Information that is mutually known between the discourse partners-their common ground-serves as a backdrop for successful communication. Here we present an introduction to the focus of this topic, which is the role of memory in common ground and language use. Two types of questions emerge as central to understanding the relationship between memory and common ground, specifically questions having to do with the representation of common ground in memory, and the use of common ground during language processing.