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Not exactly - all the forecast questions get scored so we know how accurate the AI is and how calibrated it is. It's no different than asking a large crowd of humans on Good Judgment Open or Metaculus these same types of questions. Everything we ask eventually happens or it doesn't, and we can score it all.

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Ok, so in an ML system you can calculate things like cross entropy loss, which penalizes your model for making confident, inaccurate predictions.

It doesn’t care whether your system is made of LLMs, decision trees, or bananas.

However, the problem is that unlike something like a neural net, you can’t exactly use backprop to improve.

On the flip side if the quality of the prediction doesn’t matter, I might as well have Claude spin up something shiny that does the same thing faster, cheaper, and with 10x the magic sparkles.

Okay. So how accurate is it?

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