• Media type: E-Article
  • Title: AI-Mediated Communication : Language Use and Interpersonal Effects in a Referential Communication Task : Language Use and Interpersonal Effects in a Referential Communication Task
  • Contributor: Mieczkowski, Hannah; Hancock, Jeffrey T.; Naaman, Mor; Jung, Malte; Hohenstein, Jess
  • imprint: Association for Computing Machinery (ACM), 2021
  • Published in: Proceedings of the ACM on Human-Computer Interaction
  • Language: English
  • DOI: 10.1145/3449091
  • ISSN: 2573-0142
  • Origination:
  • Footnote:
  • Description: <jats:p>AI-Mediated Communication (AI-MC) is interpersonal communication that involves an artificially intelligent system that can modify, augment, or even generate content to achieve communicative and relational goals. AI-MC is increasingly involved in human communication and has the potential to impact core aspects of human communication, such as language production, interpersonal perception and task performance. Through a between-subjects experimental design we examine how these processes are influenced when integrating AI-generated language in the form of suggested text responses (Google's smart replies) into a text-based referential communication task. Our study replicates and extends the impacts of a positivity bias in AI-generated language and introduces the adjacency pair framework into the study of AI-MC. We also find preliminary yet mixed evidence to suggest that AI-generated language has the potential to undermine some dimensions of interpersonal perception, such as social attraction. This study contributes important concepts for future work in AI-MC and offers findings with implications for the design of AI systems in human-to-human communication.</jats:p>