The original startup analogy might be a useful intuition pump here. Most attempts to displace entrenched incumbents fail, even when those incumbents aren’t good and ultimately are displaced. The challengers aren’t random in the monkeys-using-keyboard sense, but if you sample the space of challengers you will probably pick a loser. This is especially true of the challengers who don’t have a concrete, specific thesis of what their competitors are doing wrong and how they’ll improve on it—without that, VCs mostly won’t even talk to you.
But this isn’t a general argument against startups, just an argument against your ability to figure out in advance which ones will work. The standard solution, which I expect will apply to transhumanism as to everything else, is to try lots of different things, compare them, and keep the winners. If you are upstream of that process, deciding which projects to fund, then you are out of luck: you are going to fund a bunch of losers, and you can’t do anything about it.
If you can’t do that, the other common strategy is to generate a detailed model of both the problem space and your proposed improvement, and use those models to iterate in hypothesis space instead of in real life. Sometimes this is relatively straightforward: if you want the slaves to be free, you can issue a proclamation that frees them and have high confidence that they won’t be slaves afterward (though note that the real plan was much more detailed than that, and didn’t really work out as expected). Other times it looks straightforward but isn’t: sparrows are pests, but you can’t improve your rice yields by getting rid of them. Here, to me the plan does not even look straightforward: the Pentagon does a lot of different things and some of them are existentially important to keep around. If we draw one sample from the space of possible successors, as Cummings suggests, I don’t think we’ll get what we want.
The original startup analogy might be a useful intuition pump here. Most attempts to displace entrenched incumbents fail, even when those incumbents aren’t good and ultimately are displaced. The challengers aren’t random in the monkeys-using-keyboard sense, but if you sample the space of challengers you will probably pick a loser. This is especially true of the challengers who don’t have a concrete, specific thesis of what their competitors are doing wrong and how they’ll improve on it—without that, VCs mostly won’t even talk to you.
But this isn’t a general argument against startups, just an argument against your ability to figure out in advance which ones will work. The standard solution, which I expect will apply to transhumanism as to everything else, is to try lots of different things, compare them, and keep the winners. If you are upstream of that process, deciding which projects to fund, then you are out of luck: you are going to fund a bunch of losers, and you can’t do anything about it.
If you can’t do that, the other common strategy is to generate a detailed model of both the problem space and your proposed improvement, and use those models to iterate in hypothesis space instead of in real life. Sometimes this is relatively straightforward: if you want the slaves to be free, you can issue a proclamation that frees them and have high confidence that they won’t be slaves afterward (though note that the real plan was much more detailed than that, and didn’t really work out as expected). Other times it looks straightforward but isn’t: sparrows are pests, but you can’t improve your rice yields by getting rid of them. Here, to me the plan does not even look straightforward: the Pentagon does a lot of different things and some of them are existentially important to keep around. If we draw one sample from the space of possible successors, as Cummings suggests, I don’t think we’ll get what we want.