Right to Local Intelligence: Protecting Open AI from State Licensing Laws

The Fight for Local AI Freedom

A new grassroots initiative, Right to Local Intelligence (RTI), is mobilizing to protect the right to run open AI models on personal devices without state-mandated licenses. The group argues that emerging state laws could turn open models into tools requiring permission to use, fundamentally altering the landscape of local AI development.

RTI's core mission is to ensure that individuals can download, own, run, study, modify, and share open AI models freely. The initiative explicitly supports enforcing laws against fraud, cybercrime, CSAM, harassment, nonconsensual intimate deepfakes, discrimination, and sabotage. The red line, they say, is requiring a license just to own or run the tool.

What Is Local AI and Why Does It Matter?

Local AI refers to models that run on a user's own machine—a laptop, desktop, or phone—rather than relying on cloud-based APIs or chatbot accounts. RTI argues that this is the next personal computer, offering users the ability to inspect, repair, improve, and use the model without asking a platform to stay online.

Not every AI task requires a warehouse of GPUs. For many everyday tasks, a small open model can run on devices people already own. RTI's position is that the law should not force simple, lawful workloads back into the cloud when the task fits the device.

The Threat: State Licensing Laws

RTI warns that new state laws could put local AI behind a license, turning open models into something you need permission to use. The initiative provides a ten-second sign-up form and a call script for citizens to contact their legislators.

As of July 1, 2026, RTI's civic data tracks 7,359 lawmakers across 50 states, using data from Open States. The group has already seen 124 people take action, with a live count of every signup and call.

Broader Context: AI in Government and Surveillance

The push for local AI freedom comes amid a broader debate about AI governance. In Oregon, city governments and schools are introducing AI tools in various fashions, from local government to universities, tailoring policies to their service and mission. This highlights the growing integration of AI into public-sector operations.

Meanwhile, Maryland counties are building police surveillance hubs that can track patrol cars, scan license plates, and pull footage from surveillance cameras—all from a single room. Legal experts warn that such concentrated surveillance power could shift the balance between citizens and their government, raising questions about the public's right to information held by private entities.

The U.S. Supreme Court recently reaffirmed a reasonable expectation of privacy in cellphone location information, reflecting judicial concern over mass surveillance. This tension underscores the need for clear legal frameworks around data and AI.

AI in Software Development: A New Source of Risk

In the enterprise, AI-driven software development is creating significant boosts in efficiency but also introducing new, often unmanaged risks. A thorough audit of AI/LLM assistants is critical for CISOs to identify vulnerabilities and ensure compliance with emerging regulatory directives.

Research shows that the best LLMs perform comparably with proficient professionals for a limited range of secure coding tasks, such as flagging code smells and anti-patterns. However, they struggle with DoS protection, insufficient logging, and misconfigured permissions. Top security-proficient developers still outperform LLMs, while average developers do not.

CISOs must work closely with development team leaders to record tool usage, map AI assistants to code outputs, and ensure audit readiness. This is essential for balancing efficacy, innovation, and protection in AI-driven software development.

Legal and Privacy Implications

The legal landscape is also shifting. A split Fourth Circuit panel recently affirmed an order requiring the CIA and Office of the Director of National Intelligence to allow intelligence officers fired for their involvement in certain activities to appeal. This case, John Doe 1 v. Office of the Director of National Intelligence, highlights the ongoing tension between national security and individual rights.

In Maryland, Howard County Police can now track patrol cars, scan license plates, and pull footage from surveillance cameras from a single room. Legal experts say this kind of concentrated surveillance power could fundamentally shift the balance between citizens and their government. The Supreme Court's recent ruling on cellphone location data reinforces concerns about mass surveillance.

How to Take Action

RTI offers a simple way to get involved: sign with your email and state, and the group provides a call script tailored to your state. The official lookup may ask for your address to find exact legislators, but RTI does not store it.

For those who want to do more, RTI encourages following the people building this in the open, including @kingbootoshi, @0xSero, and @RayFernando1337. Volunteers can also reach out via email at volunteer@righttointelligence.org.

The initiative also provides a model bill and sources for those interested in deeper research. Every state pack is marked source-verified draft with provenance and a retrieval date where available.

Why It Matters

The debate over local AI freedom is part of a larger conversation about the balance between innovation, privacy, and security. As state legislatures consider laws that could restrict local AI, the outcome will shape the future of personal computing and the open-source AI ecosystem.

RTI's approach is straightforward: protect lawful use and enforce real harm. The group believes that people should be free to download, own, run, study, modify, and share open AI models, while fraud, cybercrime, CSAM, harassment, nonconsensual intimate deepfakes, discrimination, and sabotage should remain illegal and be enforced seriously.

The red line, they say, is requiring a license just to own or run the tool. This is a critical distinction that will define the future of local AI.