Appendix C — Consent & Control Framework

Appendix C — Consent Framework Chart

Comparing consent architectures for AI training on creator works

Consent / Control Mechanism Default State Timing of Choice Scope of Control Individual Creator Control Prospective Effect Binds Partners & Transfers Counts as Consent
(Under This Framework)
Explicit Opt-In (Checkbox at Upload or Onboarding) No training unless creator acts Before training All generative AI uses Yes Yes Yes (if stated) Yes
Granular Opt-In (Per-Work or Per-Use) No training unless creator acts Before training Specific works or uses Yes Yes Yes (if binding and comprehensive) Yes (if binding)
Default Opt-Out (Account-Level Toggle) Training occurs by default After training has begun Usually limited or undefined Partial Sometimes Rarely No
Limited Opt-Out (Feature- or Purpose-Specific) Training occurs by default After training has begun Narrow (e.g., “AI features”) Partial Sometimes Rarely No
Dataset-Level Exclusion (Non-User-Facing) Training occurs by default Unclear or indirect Unclear No (non-user-facing) Unclear Unclear No
Publisher- or Platform-Level Control Only Training occurs by default Outside individual control Site-wide or collective No Sometimes Sometimes No
Disclosure Without Choice Training occurs by default No choice offered All uses No No No No
No Disclosure, No Control Training occurs by default No choice offered All uses No No No No

How to Interpret This Chart

This chart illustrates how different consent and control mechanisms function in practice. It does not evaluate platforms, assign grades,
or determine legal sufficiency. “Counts as consent” reflects this Guide’s methodological definition, not a legal determination
under any statute or doctrine.

Under this framework, consent requires an affirmative choice made before AI training occurs, with training disabled by default unless
the creator actively permits it. Mechanisms that assume permission by default—such as opt-outs, toggles, or disclosures without choice—may offer limited
control, but they do not constitute consent.

Platforms may implement multiple mechanisms simultaneously. Platform grades reflect the overall consent architecture, not the presence
of any single control. This chart is therefore a conceptual reference explaining the logic behind the grading framework, not a standalone scorecard.