Fwiw, when I've tried it, it has tended to suck in a whole lot of my time.
For me, other projects seem more meaningful. E.g., right now I'm setting up this: https://alert-team.org, another member is behind https://theaidigest.org/progress-and-dangers, a third works at https://forecastingresearch.org/, etc. Maybe we're an idealistic bunch, but also maybe we're making a bad judgment call, and still yet it's possible we couldn't cut it.
I mean, it makes me quite happy that y'all apparently use your skills for wholesome, humanitarian things instead of just focusing on making $$$.
fwiw, it appears you'd have a decent chance. You guys seem to have an extreme level of objectivity and rationality. There is a lot of domain knowledge required to bet on say, healthcare stocks or whatever, but maybe too much domain knowledge harms rather than hurts.
Naively, if any of the predictions could be made +EV accounting for time preference, the boffins' predictions should have been mirrored into the market to someone's profit.
I remain unconvinced that they're not merely very lucky, the same way that some hedge fund operators or day traders are lucky.
For climate change, there's already a lot of existing models out there calculated by much more rigorous metrics than "the Laplace rule" or just naively adding together averages.
We know that every species consumes all available resources until an external force, whether it's predators or environmental collapse checks its growth. Humans are no different - any time a poor person uses a paper straw, a rich one will fly their private jet. Muh backyard arguments on nuclear means we will continue to burn coal and gas as fast as possible, even while renewables help drive up more demand.
So I think it's safe to assume that emissions will continue growing.
[0]: https://cei.org/blog/wrong-again-50-years-of-failed-eco-poca...
FWIW, I'm very much NOT endorsing cei.org, nor saying climate change is not a big problem. Just saying that the track record of climate scientists is not great. Climate change is important enough to warrant the attention of people who can actually predict things.
Forecasting in general is a silly affair. As a data scientist I get all kinds of requests for all kinds of predictions, and my only real job is to part those requesting parties from their money.
The party relies on divide and conquer of uniformed fools. But the fools are in the minority by now - and the divide and conquer is one sneaky trustfall decentralized communication platform away from never working again.
Or in other words, if you want to say "this time is different" and deviate from the base rate, you actually need to look at the previous times to find out whether it really is different this time, and if so, by how much.
If the information is entirely new (ie, what impact does aliens taking over the Moon have on China/Taiwan) then there'll always be difficulty estimating that impact
Also, as the article notes, scholars like Tetlock have studied the the track record of scholars and experts and found them to be less accurate than this type of approach.
It’s a literary sleight of hand but useful to note as it undermines the entire premise of the article. That’s because these predictions are bunk because these techniques don’t work with the stock market which uses far more rigorous statistical methods for pricing (which happened 60s-90s with the rise of quants).
It can be hard to convince people with math alone.
I particularly liked the idea of base rates and averaging them. [1] I can see here that the idea of them is not to be on their own accurate (some of the methodologies individually are dumb), but do get an idea for the scales of numbers to talk about (the difference between a 5% event and a 10% event is very hard to notice as a human)
[1] "One was the rate at which provinces claimed by China (like Hong Kong, Macau, and Tibet) have eventually been absorbed, peacefully or by force; another was how often control of Taiwan has changed over the last few hundred years (twice; once when Japan took over from the Qing Empire in 1895 and once when the Chinese Nationalists did in 1945); the third base rate used Laplace’s rule. Laplace’s rule states that the probability of something that hasn’t happened before happening is 1 divided by N+2, where N is the number of times it hasn’t happened in the past. So the odds of the People’s Republic of China invading Taiwan this year is 1 divided by 75 (the number of years since 1949 when this has not happened) plus 2, or 1/77, or 1.3 percent.
Sempere averaged his three base rates to get his initial prediction: 8 percent"