One criteria in the 80,000 Hours problem framework is ‘solvability’. All else equal, it is more effective to dedicate yourself to a problem if a larger percentage of the problem will be solved by each additional person working on it. So far so good.
However, this can lead to something counterintuitive. Here is an extreme example to demonstrate the problem:
Humanity faces ‘risk X’, that unless we invest resources in tackling it, will result in human extinction in 2030, with near certainty.
Person A believes that ‘risk X’ is easy to solve. 100 people working until 2030 will be able to reduce the risk of extinction to 0%.
Person B believes that ‘risk X’ is hard to solve. 100 people working until 2030 will only reduce the risk to 90%. Person B believes that only 1 million people working until 2030 is what will reduce the risk to 0%.
The strange thing here is that person A believes that each additional person working to prevent risk X is 10 times as impactful as person B believes them to be. But person B likely believes we should invest ~10,000 times as much in preventing risk X.
There is no real paradox here.
Person A believes that additional people on the current ‘margin’ are incredibly useful, but that by the time we put the 101st additional person on the case, they will be redundant and not accomplish anything more. Person B believes that each additional person on the current margin is less useful, but the 101st will still be almost as useful, so we should keep throwing more people at the problem.
Given the importance of what’s at stake, we should put as many people as necessary to bring ‘risk X’ close to zero, even if it takes a million of them (rather than save our resources to do other things).
This weirdness can be important to keep in mind when communicating prioritisation results to people.
When coaching people for 80,000 Hours I sometimes say that we expect additional progress on a problem (e.g. climate change) will be slower, for each additional person who works on it, than the person I’m speaking to does. They may then respond “doesn’t that mean we should put even more effort into the problem?” And they’re potentially right!
But the paradox is that this doesn’t meant it’s more useful for them individually to work on it, if the global distribution of effort between problems remains what it is now. In fact, the opposite is true.
However, if effort on other problems increases, then the fact that progress on e.g. climate change has been slow, would be a reason to switch back to it because it will remain unsolved.
One way to incorporate this into long-term career planning is to be less enthusiastic about developing problem-specific career capital for issues you expect to be largely taken care of by the time you reach the middle of your career.
In some cases, if a problem is harder humanity should invest more in it, but you should be less inclined to work on it
One criteria in the 80,000 Hours problem framework is ‘solvability’. All else equal, it is more effective to dedicate yourself to a problem if a larger percentage of the problem will be solved by each additional person working on it. So far so good.
However, this can lead to something counterintuitive. Here is an extreme example to demonstrate the problem:
Humanity faces ‘risk X’, that unless we invest resources in tackling it, will result in human extinction in 2030, with near certainty.
Person A believes that ‘risk X’ is easy to solve. 100 people working until 2030 will be able to reduce the risk of extinction to 0%.
Person B believes that ‘risk X’ is hard to solve. 100 people working until 2030 will only reduce the risk to 90%. Person B believes that only 1 million people working until 2030 is what will reduce the risk to 0%.
The strange thing here is that person A believes that each additional person working to prevent risk X is 10 times as impactful as person B believes them to be. But person B likely believes we should invest ~10,000 times as much in preventing risk X.
There is no real paradox here.
Person A believes that additional people on the current ‘margin’ are incredibly useful, but that by the time we put the 101st additional person on the case, they will be redundant and not accomplish anything more. Person B believes that each additional person on the current margin is less useful, but the 101st will still be almost as useful, so we should keep throwing more people at the problem.
Given the importance of what’s at stake, we should put as many people as necessary to bring ‘risk X’ close to zero, even if it takes a million of them (rather than save our resources to do other things).
This weirdness can be important to keep in mind when communicating prioritisation results to people.
When coaching people for 80,000 Hours I sometimes say that we expect additional progress on a problem (e.g. climate change) will be slower, for each additional person who works on it, than the person I’m speaking to does. They may then respond “doesn’t that mean we should put even more effort into the problem?” And they’re potentially right!
But the paradox is that this doesn’t meant it’s more useful for them individually to work on it, if the global distribution of effort between problems remains what it is now. In fact, the opposite is true.
However, if effort on other problems increases, then the fact that progress on e.g. climate change has been slow, would be a reason to switch back to it because it will remain unsolved.
One way to incorporate this into long-term career planning is to be less enthusiastic about developing problem-specific career capital for issues you expect to be largely taken care of by the time you reach the middle of your career.