Who Decides What AI Calls True

In June the White House restricted two of Anthropic’s models and Anthropic just shut them down rather than risk a foreign national touching them. Arthur Mensch at Mistral had spent a year warning this would happen: run your bank or your hospital on an American model and you’ve handed Washington a switch. He was right, and that became the story.

It’s the least interesting part of the story. An off-switch is the most visible kind of power there is — you see it, you know the day it happens, you can sue or build a backup. The control that matters over the next ten years is the kind you can’t see and can’t route around. Some of it is obvious once you say it: data, product, reach. Some of it is barely discussed. And the most important piece, especially for the part of the world I come from, isn’t who owns the model at all. It’s which truth the model serves, to whom, first.

Data. People think the model is the prize. It isn’t — models are commoditizing, a handful do most jobs and the gaps close every few months. What doesn’t commoditize is data nobody else has. BMW runs thousands of simulated crashes a week on more than a petabyte of crash history and is training “Large Industry Models” on it with Mistral; Airbus signed the same kind of deal across aviation, defence and space. The leverage there isn’t the model — BMW could swap models tomorrow. It’s that BMW’s data exists in one place on earth. Same in a literal war: Mistral chasing Ukraine’s DELTA battlefield system isn’t after a model, it’s after combat data that exists nowhere else.

Product. The frontier model isn’t the product, and the money knows it. Anthropic is worth around $965 billion, Mistral about $13.6 billion — seventy to one — and Mistral is still winning the industrial deals, because those aren’t decided on a benchmark but on who’s embedded and who you can run on your own hardware. Mistral’s newest release is an OCR tool: reads documents, 170 languages, four or five dollars a thousand pages. Plumbing, not genius. The plumbing is the point.

Reach. Which is where language comes in, and not as culture. Language is reach, and reach compounds. Around 93% of the text these models trained on is English, so the labs default to the biggest market and let everyone else pay more, wait longer, and use the worse build. 170 languages isn’t a values statement, it’s a list of who you can sell to. Whoever can actually serve a language gets that user base, and a user base wired into a workflow doesn’t move.

Mood. And the off-switch isn’t a fixed lever in a steady hand — it’s wired to a mood. The same month Washington pulled Anthropic’s models, Trump threatened a 100% tariff on any country taxing US tech, France’s digital levy in the crosshairs; Brussels moved to tag Microsoft’s and Amazon’s clouds as “gatekeepers”; Musk’s in the room with his own model and his own grudges. The rules flip on a Tuesday because somebody read something at breakfast. We’re about to run hospitals, courts, and a chunk of the economy on a layer whose terms get set by the moods of a few men.

That’s the European version of the argument, and Europe has at least built itself an answer — a Tech Sovereignty Package, procurement rules written so US firms can’t qualify under the CLOUD Act. It can: American companies hold roughly 80% of Europe’s professional cloud spend, and Europe’s own share fell from about 29% to 15% in five years, so the dependency is measurable and the politics are there. Europe can do this because Europe is the EU — twenty-seven states that have spent decades learning to pool sovereignty and mostly trust each other’s institutions. Even then it’s no guarantee: it blinked on its own AI Act, quietly pushing the hardest parts out to 2027 and 2028 the moment industry pushed back, and when it does build, the result isn’t automatically good — an Estonian study put Europe’s champion, Mistral, 47th of 60 at catching Russian disinformation. But a “European AI” at least means something, because there’s a Europe to own it.

The Middle East has none of that, and this is where the sovereignty story stops translating.

There is no Arab EU. No pooled anything. So when people say the answer is a “Middle Eastern” or “Arab” AI, they’re importing a European fix into a region with none of the European preconditions. A model built in Abu Dhabi or Doha is not neutrally “Arab” the way Mistral can stand in for “Europe.” It’s Emirati, or Qatari — states with very specific views about what may and may not be said. The Gulf has built real models: Falcon and Jais in the UAE, ALLaM in Saudi, Fanar in Qatar, native Arabic, serious money. But “Arab-made” guarantees nothing, including competence — on one benchmark of Saudi cultural norms, the Emirati model Jais scored 21.9% while GPT-4 scored 83%. And it certainly doesn’t guarantee neutrality. These states will shape what their models say; if they don’t enforce it heavily yet, they will, because no government builds a national AI and leaves its politics to chance. This isn’t to call the UAE or Qatar untrustworthy. It’s that, with no shared institutions, an Egyptian has no particular reason to trust a model governed from Doha over one governed from San Francisco. Different capital, same dependency.

And that’s the rich version of the problem. For most of the region it isn’t about trust at all — it’s capability and access. Syria and Lebanon are not going to build a model. Their states are broke; they have power cuts, not data centers. A Syrian would probably rather run a Gulf-made Arabic model than an American one, and “build your own native Syrian model” isn’t hard, it’s impossible — and it isn’t a priority, nor should it be. A bankrupt country doesn’t get to spend its way to a sovereign LLM while it can’t keep the lights on. Sovereignty in AI is a luxury good. Most of the world doesn’t choose whose values it runs on; it chooses which landlord.

Even “Arabic” doesn’t hold still. There is no Arabic — there’s Modern Standard, which nobody speaks at home, and then Egyptian, Levantine, Gulf, Maghrebi, each effectively its own language. A model trained mostly on MSA and Gulf text isn’t native to a Damascene or a Moroccan; it’s a foreign accent that happens to share a script. So “a native Arabic AI” quietly means “a native some-Arabic AI,” and the some is a political choice before it’s a technical one.

Which raises the real question: what’s the point? If every state fears every other state’s switch, do we end up with everyone building their own — a model that speaks the national language, tells the national story, runs with no foreign hand on the button? Mensch frames it as survival — “if you don’t have artificial intelligence in your systems, you actually don’t have an army,” he says. Maybe he’s right that it’s becoming a must-have. But the analogy breaks where it matters. A tank has no opinion about your history. A model does. You can buy an army and it’s just force; you can build your own AI and it still has to decide which version of your past to tell you — and that doesn’t get easier because the data center is on home soil. It gets sharper, because now the choice is yours, or your government’s.

And that’s the lever I’d watch above all the others. Not data — states already understand data, they hoard it like territory. Information. Information is basically free; nothing stops anyone anywhere from reaching it. The whole game is which information arrives first, and in what words. When an Egyptian asks Google’s AI Mode about Rabaa, does it come back a “massacre,” a “dispersal,” a piece of a “coup,” or a footnote to a “revolution”? Asked about the territory where the settlements sit, does the model say “the West Bank” or “Judea and Samaria”? Does it say “judicial reform” or “judicial coup”? These aren’t edge cases — they’re the daily substance of politics where I’m from, and a model answers them every time it opens its mouth, in one phrasing, with no visible seam where the choice was made. You don’t even need AI to see it: the Wikipedia article still says “judicial reform”. Whoever sets that default — American, European, Gulf, or one day a national model of your own — holds the most durable kind of control there is. Not turning your information off. Deciding which version of it loads first.

So the off-switch was never the thing to watch. Control in AI is data you don’t have, products you don’t own, languages you can’t serve, a mood you can’t read — and under all of it, which reality the machine serves before you’ve finished asking. Building your own model doesn’t escape that last part; it only moves the choice indoors, to your own state or your richer neighbor’s. And for most of the Middle East the choice isn’t even on offer — it’s which landlord, not whether to have one. The fear pushing everyone toward a national AI is real. But a flag on the data center doesn’t answer the actual question, which was never who can switch the model off. It’s who gets to decide what it calls true.