{
  "id": 4903,
  "url": "https://arxiv.org/abs/2605.05017v1",
  "title": "Position: Embodied AI Requires a Privacy-Utility Trade-off",
  "summary": "Embodied AI (EAI) systems are rapidly transitioning from simulations into real-world domestic and other sensitive environments. However, recent EAI solutions have largely demonstrated advancements within isolated stages such as instruction, perception, planning and interaction, without considering their coupled privacy implications in high-frequency deployments where privacy leakage is often irreversible. This position paper argues that optimizing these components independently creates a systemi",
  "authors": "Xiaoliang Fan, Jiarui Chen, Zhuodong Liu, Ziqi Yang, Peixuan Xu, Ruimin Shen et al.",
  "category": "research",
  "topics": "privacy-surveillance,environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-06T15:16:05.000Z",
  "fetched_at": "2026-07-14T16:31:21.932Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/4903",
  "original_url": "https://arxiv.org/abs/2605.05017v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}