[2604.06203] Front-End Ethics for Sensor-Fused Health Conversational Agents: An Ethical Design Space for Biometrics

Computer Science > Computers and Society arXiv:2604.06203 (cs) [Submitted on 14 Mar 2026] Title:Front-End Ethics for Sensor-Fused Health Conversational Agents: An Ethical Design Space for Biometrics Authors:Hansoo Lee, Rafael A. Calvo View a PDF of the paper titled Front-End Ethics for Sensor-Fused Health Conversational Agents: An Ethical Design Space for Biometrics, by Hansoo Lee and 1 other authors View PDF HTML (experimental) Abstract:The integration of continuous data from built-in sensors and Large Language Models (LLMs) has fueled a surge of "Sensor-Fused LLM agents" for personal health and well-being support. While recent breakthroughs have demonstrated the technical feasibility of this fusion (e.g., Time-LLM, SensorLLM), research primarily focuses on "Ethical Back-End Design for Generative AI", concerns such as sensing accuracy, bias mitigation in training data, and multimodal fusion. This leaves a critical gap at the front end, where invisible biometrics are translated into language directly experienced by users. We argue that the "illusion of objectivity" provided by sensor data amplifies the risks of AI hallucinations, potentially turning errors into harmful medical mandates. This paper shifts the focus to "Ethical Front-End Design for AI", specifically, the ethics of biometric translation. We propose a design space comprising five dimensions: Biometric Disclosure, Monitoring Temporality, Interpretation Framing, AI Stance, and Contestability. We examine how thes...