Updates
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Updates will appear here as the strategy progresses.
Pass laws requiring AI disclosure and limiting surveillance uses.
Advance clear federal rules that require disclosure when AI is used in consequential contexts and that constrain high-risk surveillance uses. This strategy translates public concern into enforceable standards with real penalties, while reducing the patchwork that leaves rights dependent on geography. It can also complement near-term agency efforts, like FCC disclosure and consent reforms, by setting a clearer baseline.
Why this works
- This strategy creates clear, democratic mandates: e.g.
- a federal law could require any AI system used in critical decisions to be transparent and auditable, and could ban high-risk surveillance like real-time facial recognition by government.
- Legislation can also include enforcement teeth (penalties for agencies or companies that fail to comply).
- It provides uniform protections – important for civil liberties – and can be comprehensive (covering both government and private sector in some respects).
Public Citizen is a nonprofit consumer advocacy organization founded in 1971 by Ralph Nader. It works to ensure that all citizens are represented in the halls of power by promoting public health and safety, government transparency, and corporate accountability. Public Citizen fights for campaign finance reform and ethics (it helped create the Office of Congressional Ethics:), advocates for safe pharmaceuticals and medical devices, pushes for strong consumer protections in trade deals, and litigates to enforce health, safety, and environmental laws.
Mechanism
How Public Citizen uses funding
- Define the specific disclosure and surveillance limits the bill should require and how they would be enforced.
- Build the case with real-world harms and public demand already cited in the cause materials.
- Engage lawmakers and staff with targeted briefings and coalition coordination.
- Track committee movement, amendments, and vote timing; negotiate to keep standards meaningful.
- Close the loop with an implementation-focused readout of what passed and what comes next.
Partner notes
Partner notes coming soon.