Work

Facilitating Natural Conversational Agent Interactions: Lessons from a Deception Experiment

Year: 2014

Type: article

Abstract: This study reports the results of a laboratory experiment exploring interactions between humans and a conversational agent. Using the ChatScript language, we created a chat bot that asked participants to describe a series of images. The two objectives of this study were (1) to analyze the impact of dynamic responses on participants’ perceptions of the conversational agent, and (2) to explore behavioral changes in interactions with the chat bot (i.e. response latency and pauses) when participants engaged in deception. We discovered that a chat bot that provides adaptive responses based on the participant’s input dramatically increases the perceived humanness and engagement of the conversational agent. Deceivers interacting with a dynamic chat bot exhibited consistent response latencies and pause lengths while deceivers with a static chat bot exhibited longer response latencies and pause lengths. These results give new insights on social interactions with computer agents during truthful and deceptive interactions.

Source: DigitalCommons@UNO

Authors: Ryan M. Schuetzler, G. Mark Grimes, Justin Scott Giboney, Joseph Buckman

Institution: University of Arizona

Language: English

Topic: Social Robot Interaction and HRI

Subfield: Social Psychology

Field: Psychology

Domain: Social Sciences

Open Access status: green

Funder: National Science Foundation

Award: I/UCRC CGI: Collaborative Research - I/UCRC for Identification Technology Research

OpenAlex ID: W97617351