When The Government Owns a Piece of Your AI, and the Private, Locally Controlled Alternative

Most people use cloud AI as though they are having a private conversation with a machine.

In reality they are transmitting information to a corporation with institutional backing. The information moves through infrastructure they do not own, is processed under policies they may not ever read, and sits inside legal jurisdictions they do not control. Most people are speaking, literally, with black boxes thousands of miles away from that.

The ramifications of this are unprecedented. From your AI data being distributed to third parties (already confirmed, and over 6 major companies have been sued), to meshing your mind with remote controlled systems owned by third-parties, most people instinctively understand the complications with this arrangement.

And yes, in case you did not know, six major companies alone have been implicated across high-profile cases and enforcement actions involving some combination of harvesting AI data, retaining it, sharing it, using it to train systems, or failing to clearly disclose how it was being handled.

The exact allegations differ from case to case. Some involved voice assistants activating without clear intent. Some involved advertising systems. Some involved biometric or location data. Some involved material used to train AI systems. Some involved information passed to outside parties. Regardless, settlements and regulatory penalties tied to these acivities have already exceeded billions of dollars.

As for OpenAI and Washington: Financial Times reported earlier this month that Sam Altman, CEO of OpenAI, has personally pitched the Trump administration on handing the United States government a 5% stake in his company. At OpenAI's current $852 billion valuation, that stake is worth roughly $42.6 billion. Altman took the proposal directly to President Trump, Commerce Secretary Howard Lutnick, and Treasury Secretary Scott Bessent.

Altman has reportedly encouraged the same arrangement from Anthropic, Google, and Meta. Distributed across roughly 133 million American households, the value comes out to something like $300 per family — as a paper stake in a company that has never posted a profit. What's interesting is how this seems to formalize enmeshment between corporations and governments that already occurred begind the scenes, and that means something as it pertains to your data, privacy with these technologies.

Corporations and governments were always enmeshed. AI is just the newest iteration, and your data is on the line.

Most people imagine a clean dividing line between a private technology company and the government that regulates it.

They were always enmeshed.

Cloud companies operate under national laws, their servers sit inside legal jurisdictions, their executives negotiate with governments, their infrastructure can be reached through subpoenas, warrants, court orders, regulatory demands, national-security authorities, export controls, and political pressure. That does not mean every prompt is being actively read by the government. It means the data was never outside the government’s reach simply because a private corporation collected it first.

The OpenAI proposal is useful because it makes that arrangement easier to see, and increasing regulations such as Anthropic rolling out a soft launch of biometrics and ID verification on July 8, makes it even messier for people who care about protecting themselves.

Centralized platforms collect enormous volumes of information first and explain the boundaries later.

By the time a lawsuit settles, the data has already been collected. The models may already have been trained. The information may already have moved through third-party systems. A payment years later does not reverse the transfer. A settlement can punish a company. It cannot pull your information back out of every system that already received it.

Locally Owned, Privately Controlled AI

Now, you do not need to abandon AI entirely for a solution here. Some people will, and that's a totally fine choice, but others want to leverage the advantage, but on their terms, and safely.

While local AI is increasingly common in deeper tech niches, the general public at large has no idea of it, yet.

A capable local AI machine sits in your house or business, runs on your electricity, stores your information locally, and answers to you.

Local AI is not perfect security by default. A badly configured local system can still be exposed. A compromised machine can still leak data. Ownership does not remove the need for discipline, but that's why we wrote what we wrote: so that people can do this properly.

The catch, and the reason most people have never done it, is that the path to ownership currently involves too many decisions. What hardware. What model. What runtime. What security configuration. Whether an existing computer is enough. We collapse them all so that you can do it in one weekend, without a tech headache.

That is exactly the problem the manuals were written to solve. You will hear many terms: local AI, private AI. People are talking about the same thing, but most people teaching it don't focus on the things that will burn you if you overlook them.

The manuals.

The Field Guide To Private AI is the starter: 332 pages on how to own your AI end to end, from sourcing hardware to running a real model with real security. Written for people who have never opened a computer case and never want to feel dependent on a rented tool again.

The Complete Owner's Manual For Private AI is the companion work: over 300 pages on custom builds, long-term maintenance, and running this properly for years. For readers who want the whole picture. Both books are in print. Both are ours. Both were built to age.

Read more at www.theaimanual.org.

A note on spreading it.

If you are the kind of person who wants to help others own their AI, not just yourself, a group we work with called Local AI Integrators runs a network for that. It is how the readers who care about getting this material into more hands end up doing so. Not required. Not part of the book. Just there if you want it.

The bottom line.

The OpenAI proposal is a reminder on where this all is probably going.

Your cloud AI data was never truly under your control. The jurisdiction lines were already blurred. The commercial incentives were already present. The legal access points already existed. Third-party data ecosystems were already operating.

The durable answer is not finding a cloud company you trust more.

It is reducing how much trust the system requires.

If you are going to use AI, own the machine. If you are going to depend on it, control the architecture. If the information matters, stop treating someone else’s server like a private room.