I think this is a very important question. In case you haven’t seen it, here’s Luke Muehlhauser’s overview of his post How Feasible Is Long-range Forecasting? (I’d also highly recommend reading the whole post):
How accurate do long-range (≥10yr) forecasts tend to be, and how much should we rely on them?
As an initial exploration of this question, I sought to study the track record of long-range forecasting exercises from the past. Unfortunately, my key finding so far is that it is difficult to learn much of value from those exercises, for the following reasons:
Long-range forecasts are often stated too imprecisely to be judged for accuracy. [More]
Even if a forecast is stated precisely, it might be difficult to find the information needed to check the forecast for accuracy. [More]
Degrees of confidence for long-range forecasts are rarely quantified. [More]
In most cases, no comparison to a “baseline method” or “null model” is possible, which makes it difficult to assess how easy or difficult the original forecasts were. [More]
Incentives for forecaster accuracy are usually unclear or weak. [More]
Very few studies have been designed so as to allow confident inference about which factors contributed to forecasting accuracy. [More]
It’s difficult to know how comparable past forecasting exercises are to the forecasting we do for grantmaking purposes, e.g. because the forecasts we make are of a different type, and because the forecasting training and methods we use are different. [More]
We plan to continue to make long-range quantified forecasts about our work so that, in the long run, we might learn something about the feasibility of long-range forecasting, at least for our own case.
Yeah, I don’t blame Linch for passing on this question since I think the answer is basically “We don’t know and it seems really hard to find out.”
That said, it seems that forecasting research has legitimately helped us get better at sussing out nonsense and improving predictions about geopolitical events. Maybe it can improve our epistemic status on ex risks too. Given that there don’t seem to be too many other promising candidates in this space, more work to gauge the feasibility of longterm forecasting and test different techniques for improving it seems like it would be valuable.
Yeah, I share the view that that sort of research could be very useful and seems worth trying to do, despite the challenges. (Though I hold that view with relatively low confidence, due to having relatively little relevant expertise.)
Some potentially useful links: I discussed the importance and challenges of estimating existential risk in my EAGx lightning talk and Unconference talk, provide some other useful links (including to papers and to a database of all x-risk estimates I know of) in this post, and quote from and comment on a great recent paper here.
I think there are at least two approaches to investigating this topic: solicit new forecasts about the future and then see how calibrated they are, or find past forecasts and see how calibrated they were. The latter is what Muehlhauser did, and he found it very difficult to get useful results. But it still seems possible there’d be room for further work taking that general approach, so in a list of history topics it might be very valuable to investigate I mention:
6. The history of predictions (especially long-range predictions and predictions of things like extinction), millenarianism, and how often people have been right vs wrong about these and other things.
Hopefully some historically minded EA has a crack at researching that someday! (Though of course that depends on whether it’d be more valuable than other things they could be doing.)
(One could also perhaps solicit new forecasts about what’ll happen in some actual historical scenario, from people who don’t know what ended up happening. I seem to recall Tetlock discussing this idea on 80k, but I’m not sure.)
I think this is a very important question. In case you haven’t seen it, here’s Luke Muehlhauser’s overview of his post How Feasible Is Long-range Forecasting? (I’d also highly recommend reading the whole post):
(See also the comments on the EA Forum link post.)
Yeah, I don’t blame Linch for passing on this question since I think the answer is basically “We don’t know and it seems really hard to find out.”
That said, it seems that forecasting research has legitimately helped us get better at sussing out nonsense and improving predictions about geopolitical events. Maybe it can improve our epistemic status on ex risks too. Given that there don’t seem to be too many other promising candidates in this space, more work to gauge the feasibility of longterm forecasting and test different techniques for improving it seems like it would be valuable.
I agree with what you said at a high-level! Both that it’s hard and that I’m bullish on it being plausibly useful.
FWIW, I still intend to answer this question eventually, hopefully before the question becomes moot!
Yeah, I share the view that that sort of research could be very useful and seems worth trying to do, despite the challenges. (Though I hold that view with relatively low confidence, due to having relatively little relevant expertise.)
Some potentially useful links: I discussed the importance and challenges of estimating existential risk in my EAGx lightning talk and Unconference talk, provide some other useful links (including to papers and to a database of all x-risk estimates I know of) in this post, and quote from and comment on a great recent paper here.
I think there are at least two approaches to investigating this topic: solicit new forecasts about the future and then see how calibrated they are, or find past forecasts and see how calibrated they were. The latter is what Muehlhauser did, and he found it very difficult to get useful results. But it still seems possible there’d be room for further work taking that general approach, so in a list of history topics it might be very valuable to investigate I mention:
Hopefully some historically minded EA has a crack at researching that someday! (Though of course that depends on whether it’d be more valuable than other things they could be doing.)
(One could also perhaps solicit new forecasts about what’ll happen in some actual historical scenario, from people who don’t know what ended up happening. I seem to recall Tetlock discussing this idea on 80k, but I’m not sure.)