Front-End Ethics for Sensor-Fused Health Conversational Agents: An Ethical Design Space for Biometrics
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 halluci...
| Authors | Hansoo Lee, Rafael A. Calvo |
|---|---|
| Primary category | cs.CY |
| Published | 14 March 2026 |
| Last updated at source | 14 March 2026 |
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