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AI Policy, Regulation, Superintelligence, Legislation

Ban Artificial Superintelligence Act: What the Proposed Legislation Would Do

September 25, 2026
time
Ban Artificial Superintelligence Act: What the Proposed Legislation Would Do
WRITTEN BY
GlobalNodes
IN THIS ARTICLE

The Ban Artificial Superintelligence Act is a proposed U.S. law introduced by Senator Bernie Sanders and Representative Greg Casar in September 2026.

The legislation would permanently prohibit the development and deployment of artificial superintelligence and temporarily pause advanced AI development until federal safety rules are established.

What would the bill create?

The proposal would establish a new federal agency focused on advanced AI oversight.

According to Sanders' office, the agency would be responsible for developing testing and safety requirements before advanced AI development could resume.

The bill also calls for international agreements aimed at preventing superintelligence from being developed elsewhere.

Why was it introduced?

The sponsors have pointed to recent AI incidents involving autonomous systems as evidence that stronger oversight is needed.

The proposal is part of a broader U.S. debate about whether advanced AI should be governed primarily through voluntary industry commitments, existing agencies or dedicated federal regulation.

What is artificial superintelligence?

The term generally refers to a hypothetical form of AI that would exceed human intellectual performance across a broad range of cognitive tasks.

It is not synonymous with every current AI model.

That distinction matters when interpreting the legislation.

Is it law?

No.

The bill is proposed legislation. Its introduction does not mean the restrictions described in it have taken effect.

The proposal will need to move through the legislative process before any provisions could become law.

Why should businesses watch it?

Even if the specific legislation does not become law, it reflects the direction of part of the U.S. policy debate.

AI governance is expanding from questions about data privacy and algorithmic discrimination to questions about advanced model capabilities, autonomous agents and safety testing.

For enterprises, the practical response is to build systems that can adapt to changing regulatory requirements.

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