{
  "id": 7258,
  "url": "https://arxiv.org/abs/2604.06203v1",
  "title": "Front-End Ethics for Sensor-Fused Health Conversational Agents: An Ethical Design Space for Biometrics",
  "summary": "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 fr",
  "authors": "Hansoo Lee, Rafael A. Calvo",
  "category": "research",
  "topics": "bias-fairness,healthcare,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-03-14T03:31:16.000Z",
  "fetched_at": "2026-07-14T16:33:03.575Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/7258",
  "original_url": "https://arxiv.org/abs/2604.06203v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}