Explainable Agents Through Social Cues: A Review
It addresses the problem of high variance in terminology and methods for explainable agents, primarily for researchers in AI and human-computer interaction, but is incremental as it synthesizes existing work.
The paper reviews the literature on making embodied agents explainable, organizing existing definitions, implementations using social cues, and impact measurements, and identifies open questions for future research.
The issue of how to make embodied agents explainable has experienced a surge of interest over the last three years, and, there are many terms that refer to this concept, e.g., transparency or legibility. One reason for this high variance in terminology is the unique array of social cues that embodied agents can access in contrast to that accessed by non-embodied agents. Another reason is that different authors use these terms in different ways. Hence, we review the existing literature on explainability and organize it by (1) providing an overview of existing definitions, (2) showing how explainability is implemented and how it exploits different social cues, and (3) showing how the impact of explainability is measured. Additionally, we present a list of open questions and challenges that highlight areas that require further investigation by the community. This provides the interested reader with an overview of the current state-of-the-art.