A Framework to Identify Critical Design Parameters for Enhancing User’s Satisfaction in Human-AI Interactions

Abstract

The advancements in artificial intelligence technology have made changes in how people interact with systems. Unique features and user requirements of Human-AI Interactions (HAII) need to be identified with respect to those of Human-Computer interactions (HCI). This study proposes a way to find critical parameters of interaction design for enhancing user’s satisfaction when people interact with intelligent systems through voice user interfaces. We summarised distinguished user requirements for intelligent products identified from previous researches. Then match them with design parameters in terms of performance indexes that will make differences in the user’s satisfaction. The interaction scenario was set as users ask simple questions with their own voices to the system and the system answer to the questions with synthesized voices after it got to the answer by AI function. The critical performance indexes derived are the number of trials to get the right answer for a question, response time to get to the next interaction, sentence structures of the answer, and pace of the answer. An experimental setup is ready to evaluate user’s satisfaction among different levels of the above performance indexes by Wizard of Oz design method applied on a voice user interface we implement. We are going to validate the effects of performance indexes in HAII on the user’s satisfaction, which will be measured in terms of verbal and non-verbal measures.