Thank you very much Dan for your comments and for looking into the ins and outs of the work and highlighting various threads that could improve it.
There are two quite separate issues that you brought up here. First about infinite value, which can be recovered with new scenarios and, second, the specific parameter defaults used. The parameters the report used could be reasonable but also might seem over-optimistic or over-pessimistic, depending on your background views.
I totally agree that we should not anchor on any particular set of parameters, including the default ones. I think this is a good opportunity to emphasise one of the limitations in the concluding remarks saying that “we should be especially cautious about over-updating from specific quantitative conclusions”. As you hinted, one important reason for this is that the chosen parameters do not have enough data behind them and are not puzzles-free.
Some thoughts sparked by the comments in this thread:
You’re totally right to point out that the longer we survive in expectation the longer the simulation needs to be run for us to observe convergence.
I agree that risk is unlikely to be time-invariant for long eras, and I’m really excited about bringing in more realistic structures, like the one you suggest: an enriched Time of Perils with decaying risk. I’m hoping WIT or other interested researchers do more to spell out what these structures imply about the value of risk mitigation.
On the flip side of the default r_low seeming too high, if seen from the point of view of the start of a century, it’d imply a (1−0.0001)100≈0.99004933869 probability of surviving each century.
A tiny r_low might be more realistic, though I confess lacking strong intuitions either way about how risk will behave in the coming centuries, let alone millennia. In my mind, risk could decay or increase, and I do hope the patterns so far, for example these last 500 years, are nothing to go by.
Your point about conditional probabilities is a good way to introduce and think about thought experiments on risk profiles. It made me think that a civilisation like the one you describe surviving different hurdles could be modelled under Great Filters where you indeed use an r_low orders of magnitude smaller than the current default and you’d get something that fits the picture you’d suggest much better, even without introducing any modifications like the decaying risk. Let me know if you play around with the code to visualise this.
Thank you very much Dan for your comments and for looking into the ins and outs of the work and highlighting various threads that could improve it.
There are two quite separate issues that you brought up here. First about infinite value, which can be recovered with new scenarios and, second, the specific parameter defaults used. The parameters the report used could be reasonable but also might seem over-optimistic or over-pessimistic, depending on your background views.
I totally agree that we should not anchor on any particular set of parameters, including the default ones. I think this is a good opportunity to emphasise one of the limitations in the concluding remarks saying that “we should be especially cautious about over-updating from specific quantitative conclusions”. As you hinted, one important reason for this is that the chosen parameters do not have enough data behind them and are not puzzles-free.
Some thoughts sparked by the comments in this thread:
You’re totally right to point out that the longer we survive in expectation the longer the simulation needs to be run for us to observe convergence.
I agree that risk is unlikely to be time-invariant for long eras, and I’m really excited about bringing in more realistic structures, like the one you suggest: an enriched Time of Perils with decaying risk. I’m hoping WIT or other interested researchers do more to spell out what these structures imply about the value of risk mitigation.
On the flip side of the default r_low seeming too high, if seen from the point of view of the start of a century, it’d imply a (1−0.0001)100≈0.99004933869 probability of surviving each century.
A tiny r_low might be more realistic, though I confess lacking strong intuitions either way about how risk will behave in the coming centuries, let alone millennia. In my mind, risk could decay or increase, and I do hope the patterns so far, for example these last 500 years, are nothing to go by.
Your point about conditional probabilities is a good way to introduce and think about thought experiments on risk profiles. It made me think that a civilisation like the one you describe surviving different hurdles could be modelled under Great Filters where you indeed use an r_low orders of magnitude smaller than the current default and you’d get something that fits the picture you’d suggest much better, even without introducing any modifications like the decaying risk. Let me know if you play around with the code to visualise this.