What a controlled user-study could tell about assessing empathy in two well-being chatbots
Abstract
Interactive software agents, such as chatbots, are progressively being used in the area of health and well-being. In such applications, where agents engage with users in interpersonal conversations for, e.g., coaching, comfort or behavior-change interventions, there is an increased need for understanding agents’ empathic capabilities. In the current state-of-the-art, there are no tools to do that. In order to understand empathic capabilities in interactive software agents, we need a precise notion of empathy. The literature discusses a variety of definitions of empathy, but there is no consensus of a formal definition. Based on a systematic literature review and a qualitative analysis of recent approaches to empathy in interactive agents for health and well-being, a formal definition—an ontology—of empathy is developed. The ontology, implemented in Web Ontology Language (OWL), may serve as an automated tool, enabling systems to recognize empathy in interactions—be it an interactive agent evaluating its own empathic performance or an intelligent system assessing the empathic capability of its interlocutors. We present a potential application of the formal definition in a controlled user-study by applying it as a tool for assessing empathy in two state-of-the-art well-being chatbots; Replika and Wysa.
Speaker
Andreas Brännström is a Doctoral student at Department of Computing Science, Umeå University. In his research, he aim to provide artificial intelligent systems with decision-making models that consider human mental attributes, such as: beliefs, values, goals and intentions. Decision-making models are based on formalizations of psychological theories. To this end, he develop formal reasoning models, using non-monotonic reasoning techniques such as Formal Argumentation and Answer Set Programming. The models are evaluated from formal, practical and ethical points of view.
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