Empathy AI in healthcare - Muthukumar, Karishma (Frontiers in Psychology, 2025)
IntroductionAI is changing healthcare and potentially even how humans interpret and express empathy. Patients and healthcare professionals are consulting AI for medical concerns, so it is critical to identify when AI expressions of empathy are helpful versus harmful. Whether or not AI is considered genuinely empathetic, the common goal is to improve AI outputs as well as healthcare outcomes. The paper explores how generative AI can impact care in a digital future.MethodsWe develop a tool for evaluating empathy called the Chatbot Compassion Quotient, or CCQ. We created a set of nine prompts, assessing compassion in various capacities, including delivering difficult news and alleviating frustration, based on the psychology literature. We compare ChatGPT and Claude-generated responses with responses from healthcare professionals. Participants also guessed which of the responses was AI-generated versus human-generated. In this corollary to the Turing test, the central question “can machines think?” became “can machines demonstrate compassion?” Thirty participants rated 3 responses to 9 scenarios on a 5-point Likert scale of 1 (not at all compassionate) to 5 (very compassionate). Responses corresponded to either ChatGPT, human, or Claude-generated results and were labeled A, B, and C in random order. After rating on the compassion scale, participants were asked to identify which, between two options, was AI-generated.ResultsResults indicated that participants considered responses from ChatGPT (aggregate score: 4.1 out of 5) and Claude (aggregate score: 4.1 out of 5) more empathetic than human (aggregate score: 2.6 out of 5) responses, with length being a potential factor impacting evaluations. Longer responses were typically rated as more compassionate. The scores for ChatGPT and Claude were comparable. Responses that appeared most obviously AI-generated performed well compared to human responses. High-scoring responses were action-oriented with multiple forms of social support.ConclusionThe study highlights the promise of human-machine synergy in healthcare. AI may alleviate fatigue and burnout in the medical field, contributing thorough responses that offer insight into patient-centered care. Further research can build on these preliminary findings to evaluate and improve expressions of empathy in AI.