Default
Door Remote - 16 Oct 2026
To be fair to OpenAI, it allowed the testing in the first place. But it shows how much rides on what a company chooses to share.
A trained AI model is essentially a very large file of numbers, often costing more than $100 million to produce, and whoever has a copy has the model. Handing copies to outsiders is a security risk. Until recently, that left testers with an awkward choice, which Google DeepMind has described well: either the testers hand over their questions, so the company sees the exam in advance, or the company hands over its model.
In August, DeepMind showed a way around that. Working with Singapore's AI Safety Institute and three other outside groups, it ran what it called the world's first double-blind test of an AI model, on the same principle as a double-blind drug trial. The test ran on sealed computer hardware, so the outside testers never saw the model and Google never saw their questions. Google says each side can check mathematically that its material stayed private.
It also moves the trust onto the hardware. Last year, researchers broke into this kind of sealed hardware with less than $1,000 of equipment, although they needed physical access to the server to do it. That's worth taking seriously. But it's a much smaller problem than "we can't let anyone near the model," and it can be managed by being careful about who controls the machines.
A trained AI model is essentially a very large file of numbers, often costing more than $100 million to produce, and whoever has a copy has the model. Handing copies to outsiders is a security risk. Until recently, that left testers with an awkward choice, which Google DeepMind has described well: either the testers hand over their questions, so the company sees the exam in advance, or the company hands over its model.
In August, DeepMind showed a way around that. Working with Singapore's AI Safety Institute and three other outside groups, it ran what it called the world's first double-blind test of an AI model, on the same principle as a double-blind drug trial. The test ran on sealed computer hardware, so the outside testers never saw the model and Google never saw their questions. Google says each side can check mathematically that its material stayed private.
It also moves the trust onto the hardware. Last year, researchers broke into this kind of sealed hardware with less than $1,000 of equipment, although they needed physical access to the server to do it. That's worth taking seriously. But it's a much smaller problem than "we can't let anyone near the model," and it can be managed by being careful about who controls the machines.