Evaluating Empathy in Artificial Agents
This work tackles the foundational problem of evaluating empathy in AI agents, which is crucial for advancing computational empathy, but it is incremental as it initiates dialogue rather than presenting a definitive solution.
The paper addresses the lack of standardized evaluation methods for empathy in artificial interactive systems, examining human empathy metrics and proposing systematic approaches for developing better metrics tailored to diverse applications.
The novel research area of computational empathy is in its infancy and moving towards developing methods and standards. One major problem is the lack of agreement on the evaluation of empathy in artificial interactive systems. Even though the existence of well-established methods from psychology, psychiatry and neuroscience, the translation between these methods and computational empathy is not straightforward. It requires a collective effort to develop metrics that are more suitable for interactive artificial agents. This paper is aimed as an attempt to initiate the dialogue on this important problem. We examine the evaluation methods for empathy in humans and provide suggestions for the development of better metrics to evaluate empathy in artificial agents. We acknowledge the difficulty of arriving at a single solution in a vast variety of interactive systems and propose a set of systematic approaches that can be used with a variety of applications and systems.