Designing and Evaluating Multi-Chatbot Interface for Human-AI Communication: Preliminary Findings from a Persuasion Task
<|reference_start|>Designing and Evaluating Multi-Chatbot Interface for Human-AI Communication: Preliminary Findings from a Persuasion Task: The dynamics of human-AI communication have been reshaped by language models such as ChatGPT. However, extant research has primarily focused on dyadic communication, leaving much to be explored regarding the dynamics of human-AI communication in group settings. The availability of multiple language model chatbots presents a unique opportunity for scholars to better understand the interaction between humans and multiple chatbots. This study examines the impact of multi-chatbot communication in a specific persuasion setting: promoting charitable donations. We developed an online environment that enables multi-chatbot communication and conducted a pilot experiment utilizing two GPT-based chatbots, Save the Children and UNICEF chatbots, to promote charitable donations. In this study, we present our development process of the multi-chatbot interface and present preliminary findings from a pilot experiment. Analysis of qualitative and quantitative feedback are presented, and limitations are addressed.<|reference_end|>
@article{yoon2024designing,
    title={Designing and Evaluating Multi-Chatbot Interface for Human-AI
  Communication: Preliminary Findings from a Persuasion Task},
    author={Sion Yoon, Tae Eun Kim, Yoo Jung Oh},
    journal={arXiv preprint arXiv:2406.19648},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.19648},
    primaryClass={cs.HC cs.AI cs.CL}
}