Identity for Embodied AI

Abstract

Humanoid robots create an identity problem that is broader than device inventory. A robot can move between environments, receive new AI packages, operate under different human sponsors and invoke digital services while interacting with the physical world. A serial number identifies hardware, but it does not answer whether the machine is currently authorized, whether its software state is approved, or whether the evidence surrounding its actions can be reconstructed.

This research note proposes a persistent robot identity object derived from Compute Passport™ concepts. The objective is not to replace enterprise IAM, robotics safety systems or OEM identity mechanisms. It is to create a portable governance layer that can bind a machine to accountable ownership, hardware evidence, authorized software, operating scope and lifecycle state.

1. The embodied identity gap

Traditional enterprise identity models were designed around people, applications and relatively stable devices. Embodied AI combines all three properties: it is a physical asset, a software runtime and an autonomous or semi-autonomous actor. This combination produces a changing trust surface.

The identity system therefore needs two levels of state: a durable identity for the robot itself and versioned claims describing what is currently authorized to run on it.

2. Proposed robot passport object

A robot passport can be modelled as a signed or verifiable record anchored by a CPID. The object should be deliberately minimal: it should point to sensitive enterprise records rather than carrying unnecessary personal or operational data.

3. Identity is not authorization

A valid passport should not automatically grant action. Identity answers who or what is making the request; policy decides whether that identity may perform the requested action in the current context. For robotics, context may include location, software state, health status, operator approval, time, network zone and task assignment.

This separation enables a robot to remain correctly identified while temporarily losing permission to enter a zone, access an enterprise API or receive a new software package.

4. Runtime binding

The strongest model binds robot identity to a desired software state. Each approved AI package can carry its own artifact identifier, cryptographic digest, provenance record and risk classification. The robot reports its actual state through an edge channel. A verifier compares desired and reported state before policy grants sensitive access.

5. Location as identity context

Location should be treated as contextual evidence, not identity itself. GPS, indoor localization or facility-zone information can strengthen a policy decision—for example, a warehouse robot may be authorized for inventory APIs only while operating inside an assigned facility. Location evidence can also detect impossible travel, unexpected route behavior or a robot reporting from a prohibited zone.

6. Security implications

A robot identity architecture must assume credential theft, cloned software, stale attestations and compromised edge gateways. Private keys should migrate toward hardware-backed protection where supported. Credentials require rotation and revocation. High-risk actions should depend on short-lived proof and current status rather than long-lived bearer secrets.

Quarantine is especially important. A robot can remain physically present and correctly identified while its passport status changes to a state that blocks enterprise integrations and software rollout until an investigation is complete.

7. Research direction

The next research step is interoperability: defining a stable claim schema that can map robot identity into IAM, asset management, Zero Trust policy engines, ROS 2 security domains and OEM fleet systems without creating a second isolated identity stack. Longer-term work includes privacy-preserving location proofs, stronger hardware attestation and cross-organization trust federation.