Towards Assessing Generative AI Based Empathic Systems

Recent advances in generative AI epitomized by Large Language Models (LLMs) demonstrated remarkable capabilities in generating human-like text and understanding contextual nuances. In parallel, advances in domestic applications of AI continue to break new grounds bringing to the forefront the need to address the impact of such systems especially on users' well being through socially aware interactive intelligent systems. This paper takes one step forward in this endeavour to examine the potential of LLMs based systems to generate empathy in its responses. In doing so, we identified through initial tests the key factors to designing empathy triggering responses. We then designed a set of experiments to test systematically the impact each of these factors would have on triggering empathy. We analysed the results against the degree of expressed empathy and its perceived quality.