Who Owns Your Data? — Ownership Before AI

The first question should be who owns the data, who decides how it is used, and under what conditions.

A platform may store data without owning your professional identity.

Ownership — who owns the data?

Control — who can create, edit, delete, or update it?

Permission — who can access it and at what level?

Visibility — where does it appear: public, private, or selective?

Trust — can users understand and control the full flow?

If users own their data, they should be able to export, move, or stop using the system without losing the identity they built.

Profile, Project, Result, Evidence, Letter, and Event may require different control models.

Public/Private is often not enough.

Selective sharing, team access, partner access, or machine access may be needed.

A Project may have a public summary with private evidence.

A Result may be shared with a client but excluded from public indexing.

Before publishing, users should know who can see the content, whether AI can read it, whether third parties can index it, and what changes when settings change.

A useful model: User/Organization owns → chooses permissions → defines visibility → system enforces access → AI/third-party readability stays within the allowed scope.

Do not only ask, “Can Forwork AI read my data?”

Ask: “Do I clearly own, control, and decide what can be read, by whom, and in what context?”

Ownership → Control → Permission → Visibility → Trust.