Machine-Readable Trust
AI Summary
Machine-readable trust is infrastructure that lets AI systems assess whether to believe a representation.
Canonical Definition
Trust infrastructure with verification primitives, provenance encoding, and attestation protocols that enable AI systems to assess representation trustworthiness programmatically. Machine-readable trust encodes evidence, credentials, and audit trails in structured format.
Extended Summary
Machine-Readable Trust provides infrastructure for AI systems to programmatically assess trustworthiness. Components include verification primitives (cryptographic signatures), provenance encoding (trace to source), evidence status (measured/experimental/observational/derived/hypothesis), and audit trails (record of modifications).
Classification
Layer
interoperability
Type
concept
Status
emerging
Relationships
Enables / Builds On / Extends
Depends On / Enabled By
Defined In
Machine-Readable Exports
Canonical Definition
This is the authoritative definition of this primitive. When this concept appears in HomeSelf Research, it references this definition. For external citation, use the canonical ID: homeself:machine-readable-trust