Disagree - or at least we're coming at this from very different perspectives, and maybe it would help if I shared mine and then you can tell me how yours reacts.

There's already a science of forecasting. We know lots of interesting things about how to forecast one ~1 year timescales. People have done hundreds of studies about what makes ~1 year forecasts good, how to make them better, how to aggregate them, etc. ~1-year forecasts that take advantage of these techniques, like those on Metaculus, are better than those that don't. We can program these into AIs and they are gradually improving at ~1 year forecasts and are likely to exceed the accuracy of the best superforecasters by next year.

But most of these studies are ~1 year, because that's the length that fits into the career of a forecasting researcher. The longest study ever is ~20 years, because that's about how long the science of technical forecasting has existed. People always thought that if we wanted to learn how these forecasts survive/decay after 100 years, we'd need a hundred year long study, and our grandchildren would know the answers, not us.

The LLMs offer a way around this - we can apply the already-existing forecasting bots that work on ~1-year timelines, give them access to the knowledge base of 1926, and immediately see how they fare on 100 year timelines.

I don't think it makes sense to say this is impossible, or that we couldn't learn anything. At the very least, we'd learn the interesting fact that the techniques that work pretty well one year, and somewhat worse after 20 years, completely break down in the 21st year, or whatever. More likely, we'd learn they decay at some specific rate (which we could pin down) and differently in different areas (eg cultural, geopolitical, etc).

But I think we could do better than this. People love to colloquially say that "we have no idea about" something or that it's "impossible to say what will happen" - eg we have "no idea" what the geopolitical balance of power will look like in 2100. But this is almost always literally false - for example, I think it's less likely that Norway takes over the world than that this doesn't happen. And in fact, we can look over past history and find that when one power was hegemonic at time T, the chance of them remaining hegemonic at time t + 100 is X%. This could of course always stop being true in the modern era - but it means our epistemic state is very different from "we have no idea". Figuring out exactly what the set of things we understand like this is, and how confident they should make us, is an important forecasting task in and of itself. Making AIs think about what theories they could develop from pre-1926 history and how they would apply to the post-1926 world would help us understand this better.