The Robotics Guardian Standard: A Non-Binding Conformance Framework and Public Pledge for Safety, Privacy, and Human Dignity in Home Robots and Ambient AI
A new class of machine now enters the home: an embodied, always-present intelligence with cameras, microphones, memory, and increasingly a body, welcomed past every threshold a household once guarded. Existing safety frameworks do not reach it: they govern the personal-care robots of the last decade or AI in public space, not an always-on domestic guardian owned by one member of a household and lived under by the others. This paper introduces The Robotics Guardian Standard, the first open conformance framework and public pledge for safety, privacy, and human dignity in home robots and ambient AI. Its central claim is the vector problem: the danger of domestic AI is not capability but direction, whom the sensing serves, and a home already saturated with extractive listening needs sensing turned from extraction to guardianship, not less sensing. The Standard grounds eight design dimensions in adjacent law across the United States and the European Union (child-safety reporting, the EU AI Act's prohibitions on manipulative and exploitative systems, the Children's Online Privacy Protection Act, and vehicle event-data ownership) and introduces a working vocabulary for the field: individual sovereignty in place of household sovereignty, the fidelity floor, and structural content incapacity, safety built as an architectural inability rather than a revocable policy. Makers self-assess across all eight dimensions, publish the full profile, and carry a headline score set by their weakest dimension, which defeats safety-washing at the root. Adoption is a free public pledge recorded in an open registry; a seal marks the commitment and never certification. The framework holds its own author's company to the same ruler, in public, scored at Level 1. It names openly the one problem it cannot yet solve, the good parent and the bad parent who hold the same legal key, and invites the field to build with it.