The Influence of Generative AI on Interpersonal Communication Dynamics

Introduction

The fundamental premise of interpersonal communication revolves around the exchange of thoughts, ideas, and emotions among individuals (Braithwaite & Schrodt, 2021). This premise is rooted in our understanding of information transmission through message conveyance of messages (Patton & Giffin, 1971). This initial definition of communication, which primarily focuses on the one-way transmission of information, can be traced back to the examination of communication within the context of rhetoric, a field that has been discussed since ancient Greece by philosophers such as Aristotle and Plato (Eadie, 2009). These early discussions often centered on persuading the masses; thus, communication was viewed as a unidirectional instrument for mass manipulation. Nevertheless, over time, our perspective on communication has evolved and grown more nuanced as we discovered different facets and dimensions of communication (Craig, 2017). Although new perspectives have revealed many definitions of communication within the framework of rhetorical definitions, communication has evolved over time from a public understanding of communication to a personal understanding. This evolution in our understanding of communication has spurred researchers to delve into the bilateral nature of the communication between two individuals. In general, apart from communication, interpersonal communication is the notion that it is dyadic, involving an exchange of information between two individuals (Braithwaite & Schrodt, 2021). In other words, interpersonal communication entails mutually crafting and exchanging meanings, instead of the one-dimensional nature of rhetoric. Furthermore, the modern view discusses interpersonal communication in various dimensions, including different processes such as social support, stages in relationship development such as initiation and disengagement, settings such as family or workplace, and types of channels such as nonverbal or computer-mediated communication (Braithwaite & Schrodt, 2021). It would be valuable to discuss how computer-mediated communication tools, or digitalization, transform interpersonal communication, especially through generative artificial intelligence (AI).

Generative artificial intelligence has emerged as a transformative force in the domain of interpersonal communication, introducing multifaceted alterations in the modalities and media of human interactions. Although extensive areas of this transformation warrant further exploration, it is incontrovertible that generative AI offers many opportunities to enhance human communication. One salient example is its capability for advanced real-time translation, which has been instrumental in obliterating linguistic barriers and thereby fostering seamless interactions among speakers of diverse languages. Additionally, the domain of emotion categorization, particularly in the context of deep neural networks, has shown promise in discerning emotional nuances in both written and spoken languages, leading to more contextually enriched dialogue. Drawing from a conceptual framework of communication (Wilson & Sperber, 1993), that accentuates the mutual comprehension of language, codes, or symbols between communicators, generative AI is posited as a pivotal intermediary. Its adeptness to navigate linguistic intricacies and interpret emotional nuances aligns with Wilson's theoretical underpinnings, underscoring its value in bolstering the efficacy of human communication. Generative AI, a specialized subset of artificial intelligence dedicated to generating content reflective of human creativity and cognition, has been recognized for its potential to bridge the gap between linguistic expression and semantic comprehension. Its relevance in interpersonal communication is underscored by its ability to reconcile language with its inherent meaning, thereby facilitating enhanced articulation and comprehension.