"Do you trust me?": Increasing User-Trust by Integrating Virtual Agents in Explainable AI Interaction Design

Abstract

While the research area of artificial intelligence benefited from increasingly sophisticated machine learning techniques in recent years, the resulting systems suffer from a loss of transparency and comprehensibility. This development led to an on-going resurgence of the research area of explainable artificial intelligence (XAI) which aims to reduce the opaqueness of those black-box-models. However, much of the current XAI-Research is focused on machine learning practitioners and engineers while omitting the specific needs of end-users. In this paper, we examine the impact of virtual agents within the field of XAI on the perceived trustworthiness of autonomous intelligent systems. To assess the practicality of this concept, we conducted a user study based on a simple speech recognition task. As a result of this experiment, we found significant evidence suggesting that the integration of virtual agents into XAI interaction design leads to an increase of trust in the autonomous intelligent system.