Ethics Dumping in Medical AI: Sketching a Roadmap for AI-Enabled Human Flourishing

Abstract: This talk examines the phenomenon of ethics dumping within healthcare AI, highlighting how normative responsibilities are increasingly shifted from AI developers and institutions onto clinicians and healthcare organizations. Ethics dumping occurs when broad and ambiguous ethical guidelines obscure accountability, leaving end-users to contend with risks and unintended consequences that arise from AI integration. This presentation begins by outlining the concept of ethics dumping, discussing its normative implications and its potential to reinforce existing power imbalances in healthcare.

Focusing on case studies of large language model (LLM) applications in clinical settings, the talk illustrates that while LLMs can generate coherent, human-like text, they operate on statistical correlations rather than genuine comprehension. This fundamental limitation challenges established standards of evidence and care, exposing a gap between AI’s technical promise and its ethical accountability. The examples underscore how ethics dumping not only compromises clinical practice but also diverts attention from the broader goal of leveraging AI to enhance human well-being.

Building on these insights, the presentation sketches a roadmap for reorienting AI integration toward human flourishing. This roadmap calls for a reimagining of accountability frameworks that emphasize transparency, collaboration, and a commitment to ethical care. The goal is to foster an AI ecosystem that supports meaningful, context-sensitive innovations in healthcare—ensuring that AI serves as a tool for enhancing human capabilities and well-being, rather than as a means of offloading ethical burdens onto vulnerable practitioners.

Keywords: ethics dumping, normative challenges, AI-enabled human flourishing