NO FAKES Act of 2026
Analysis under review: This bill has generated analysis that may be too generic or incomplete. Clause-level evidence remains available below.
Summary
What This Bill Does
The bill creates voice and visual likeness rights. It relies on definition changes, appropriations, grants, and compliance mandates. The main policy areas are Education, Energy, Environment, and Technology.
Who Benefits and How
The main beneficiaries are the people, organizations, or agencies identified in the bill's substantive provisions.
Who Bears the Burden and How
Federal, state, or local agencies responsible for implementing the clause would take on compliance duties, Telecommunications providers and users affected by the bill could lose revenue opportunities, and Environmental and public health interests affected by the bill could lose revenue opportunities.
Key Provisions
- Creates voice and visual likeness rights.
Evidence Chain:
This summary is generated from the full bill text using AI analysis. Expand "Detailed Analysis" below for identified beneficiaries/burden bearers with clause-level evidence links.
At a Glance
What This Bill Does
The bill creates voice and visual likeness rights.
Key Policy Areas
Education, Energy, Environment, Technology
Primary Purpose
The bill creates voice and visual likeness rights.
Policy Domains
Whole bill
Identified Costs
- Federal, state, or local agencies responsible for implementing the clause
- Telecommunications providers and users affected by the bill
- Environmental and public health interests affected by the bill
- Electric utilities and power customers affected by the bill
- Educational institutions and students affected by the bill
Sponsors
Legislative Progress
In CommitteeRead twice and referred to the Committee on the Judiciary.
Introduced in Senate
Mr. Coons (for himself, Mrs. Blackburn, Ms. Klobuchar, Mr. Tillis, …
Impact analysis is available but no clear stakeholder effects identified. View clause-level analysis →
Bill Structure & Actor Mappings
Who is "The Secretary" in each section?
We use a combination of our own taxonomy and classification in addition to large language models to assess meaning and potential beneficiaries. High confidence means strong textual evidence. Always verify with the original bill text.
Learn more about our methodology