Jochen Peter

As millions of users increasingly incorporate artificial intelligence (AI) chatbots into their daily lives, scholars have begun to explore the relationships users form with these AI companions. Research on these synthetic relationships suffers from a lack of knowledge about the features of AI companions and how these features may contribute to the development of synthetic relationships. Guided by a theory-driven feature inventory that was based on stage models of relationship formation, this study employed systematic observations and structured interviews with the 20 most popular AI companions to determine how their features may relate to various stages in the formation of synthetic relationships. The results revealed differences between AI companions based on the distinct roles they fulfill. While friendbots displayed more features that are aimed at establishing new behavioral routines for users to engage with the AI companion, assistantbots had more features that integrate the AI companion in users’ digital lives to allow engagement during users’ established routines. The present work suggests that having features to support all stages of the relationship formation can theoretically make AI companions more suitable for intimate interactions.

This chapter gives an overview of the institutional development of the Amsterdam School of Communication Research (ASCoR) in the 25 years since its foundation in 1997, paying attention to both objectives of ASCoR: organising and supporting research, and training of PhD students. The chapter also discusses various factors that shaped this trajectory, including ASCoR’s orientation on media technological and societal changes, its international, funding, output, and research methods’ orientation, and individual factors. The chapter concludes with ASCoR’s new policy being deployed to address some concerns about the current research climate at universities in the Netherlands.

Humans increasingly communicate with machines, such as chatbots and social robots. This has given rise to the field of human–machine communication. Since the second half of the 2010s, ASCoR researchers have embraced research on human–machine communication and studied communicating machines both from a theoretical and an empirical perspective. This chapter first highlights selected theoretical contributions of ASCoR researchers to human–machine communication and then outlines insights gained by empirical studies on conversational agents, social robots, as well as artificial intelligence more generally. The chapter subsequently identifies key empirical and theoretical challenges encountered by ASCoR researchers and concludes with a brief outline of two important issues for future research.

As social robots become increasingly advanced, the rules of human-robot interaction (HRI) may diverge from those of interpersonal communication. In this light, scholars have proposed that the Computers-Are-Social-Actors (CASA) paradigm, which proposes that we respond to machines as we do with humans, may need to be revised. The aim of this study was to investigate whether original CASA findings on interdependence in human-computer interaction hold in interactions with an advanced (i.e., augmented) social robot. To this end, we conducted a 2 (display of augmented cognitive capabilities: control vs. augmented) x 2 (interdependency: interdependent vs. non-interdependent) between-subjects experiment with 260 participants. We measured behavioral conformity, entitativity, and interactivity as outcomes. Interdependency did not have any effect on any of the variables. However, augmentation increased behavioral conformity. These results present tentative evidence that further research on CASA is warranted and suggest the need for a comprehensive theoretical framework to account for technological advancements and explain interactions with advanced media agents.