(1) Unfortunately, we didn’t record any predictions beforehand. It would be interesting to compare. That said, the process of constructing the model is instructive in thinking about how to frame the main cruxes, and I’m not sure what questions we would have thought were most important in advance.
(2) Monte Carlo methods have the advantage of flexibility. A direct analytic approach will work until it doesn’t, and then it won’t work at all. Running a lot of simulations is slower and has more variance, but it doesn’t constrain the kind of models you can develop. Models change over time, and we didn’t want to limit ourselves at the outset.
As for whether such an approach would work with the model we ended up with: perhaps, but I think it would have been very complicated. There are some aspects of the model that seem to me like they would be difficult to assess analytically—such as the breakdown of time until extinction across risk eras with and without the intervention, or the distinction between catastrophic and extinction-level risks.
We are currently working on incorporating some more direct approaches into our model where possible in order to make it more efficient.
Great you are looking at more direct implementations for increased efficiency, I think my intuition is it would be less hard than you make out, but of course I haven’t seen the codebase so your intuition is more reliable. For the different eras, this would make it a bit harder, but the pmf is piecewise continuous over time, so I think it should still be fine. Keen to see future versions of this! :)
(1) Unfortunately, we didn’t record any predictions beforehand. It would be interesting to compare. That said, the process of constructing the model is instructive in thinking about how to frame the main cruxes, and I’m not sure what questions we would have thought were most important in advance.
(2) Monte Carlo methods have the advantage of flexibility. A direct analytic approach will work until it doesn’t, and then it won’t work at all. Running a lot of simulations is slower and has more variance, but it doesn’t constrain the kind of models you can develop. Models change over time, and we didn’t want to limit ourselves at the outset.
As for whether such an approach would work with the model we ended up with: perhaps, but I think it would have been very complicated. There are some aspects of the model that seem to me like they would be difficult to assess analytically—such as the breakdown of time until extinction across risk eras with and without the intervention, or the distinction between catastrophic and extinction-level risks.
We are currently working on incorporating some more direct approaches into our model where possible in order to make it more efficient.
Great you are looking at more direct implementations for increased efficiency, I think my intuition is it would be less hard than you make out, but of course I haven’t seen the codebase so your intuition is more reliable. For the different eras, this would make it a bit harder, but the pmf is piecewise continuous over time, so I think it should still be fine. Keen to see future versions of this! :)