Designing and Evaluating User Experience of an AI-Based Defense System
S. Park, Hyun K. Kim, Jaehyun Park, Yuryeon Lee
Abstract
In recent years, artificial intelligence (AI) has been applied in various fields, with rapid expansion of the scope of AI-human interactions. However, most AI technologies continue to exhibit black-box characteristics, i.e., their decisions and actions are not explainable, degrading user experience (UX). Recently, research on explainable AI (XAI), focusing on both AI performance and UX, has garnered significant attention. However, development of generalizable UX evaluation tools for AI and improvement of AI UX have not been investigated adequately. In this study, a UX evaluation tool is developed for AI based on a systematic literature review and verified using exploratory and confirmatory factor analyses. Subsequently, based on identified AI UX factors, UX of an AI defense system is upgraded. Based on user evaluation, significant improvements are confirmed in eight out of nine factors. The proposed evaluation tool is expected to serve as a cornerstone for future evaluation of AI UX advancement.