Dignity-Aware AI: Positioning Edge and Federated Intelligence for Ethical Elderly Monitoring
Xun ShaoThe rapid integration of artificial intelligence into elderly monitoring systems has primarily emphasized safety—detecting falls, anomalies, or emergencies—while overlooking the deeper human dimension of dignity. This paper advances the concept of dignity-aware AI, a position that redefines how edge and federated intelligence can support autonomy, privacy, and ethical accountability in aging societies. Rather than proposing new algorithms, the paper argues for a shift in architectural thinking: computation locality and model governance should be treated as moral design parameters. By embedding ethical reasoning directly into system topology, dignity-aware AI transforms monitoring from surveillance into partnership. The discussion outlines a research roadmap linking technical maturity with ethical responsibility and calls for new value metrics that measure respect, trust, and human agency alongside performance. This opinion piece aims to provoke dialogue across AI ethics, distributed systems, and human-centered design.