Phronetic Attention to Suffering and Health Agency in Artificial Intelligence Systems

 As Artificial Intelligence (AI) becomes increasingly pervasive in healthcare, the incentives for technical innovation and financial gain driving efficient AI healthcare automation often interfere with patient care and increase health inequity. However, bio- and AI ethical frameworks remain inadequate for guiding this transformation, especially at the speed and scale in which autonomous decision-making is embedded within healthcare. Incorporating compassionate care into AI systems focuses moral attention onto patient suffering and flourishing (eudemonic well-being), translating ethical insights into an AI framework that can be operationalized within current and near-term AI system development. I argue that compassionate AI in healthcare requites modeling multiple dimensions of human suffering and health agency in support of phronetic attention and compassionate response, and that eldercare provides both a rich context and urgent test case.