Forwork & Your Data
A foundation for understanding data on Forwork: ownership, control, permission, visibility, and trust before discussing AI, indexing, or third-party crawlers.
Who Owns Your Data? — Ownership Before AI
A foundation for understanding data on Forwork: ownership, control, permission, visibility, and trust before discussing AI, indexing, or third-party crawlers.
Public, Private & Selective Sharing — Not Every Proof Should Be Public
How to choose the right visibility for Profiles, Projects, Results, and Evidence on Forwork instead of assuming all proof should be public.
What Can AI Read? — Machine Readability Must Follow Permission
How Forwork can design machine readability so AI understands Work Identity correctly while still respecting user-controlled permissions, visibility, and scope.
GEO & Machine Readability — Help AI Understand, Not Merely Crawl
How to structure Work Identity data so AI can understand entities, relations, context, sources, and meaning instead of merely crawling text.
Third-party Crawlers — Enable Indexing Without Losing Control
How to design third-party crawling and indexing for Work Identity using consent, scope, access, indexing, and revocation instead of all-or-nothing exposure.
Data Portability — Work Identity Should Not Be Locked into One Platform
Why data portability is part of ownership and how Work Identity should be exported, reused, and moved across systems without losing context.
Permission History — Access Rights Need a Timeline Too
Why permission should be more than a current state, and how grants, scope, changes, and revocation create auditable access history.
Trust by Design — Privacy and Control Should Not Be Late Additions
How to build trust into product architecture through defaults, control, transparency, reversibility, and the data lifecycle instead of relying on policy alone.