The End Of Universal Lifelong Identifiers: Identity Systems For The AI Era
Journal:
arXiv
Published Date:
May 29, 2025
Abstract
Many identity systems assign a single, static identifier to an individual for
life, reused across domains like healthcare, finance, and education. These
Universal Lifelong Identifiers (ULIs) underpin critical workflows but now pose
systemic privacy risks. We take the position that ULIs are fundamentally
incompatible with the AI era and must be phased out. We articulate a threat
model grounded in modern AI capabilities and show that traditional safeguards
such as redaction, consent, and access controls are no longer sufficient. We
define core properties for identity systems in the AI era and present a
cryptographic framework that satisfies them while retaining compatibility with
existing identifier workflows. Our design preserves institutional workflows,
supports essential functions such as auditability and delegation, and offers a
practical migration path beyond ULIs.