A couple of comments that might help readers of the thread separate problems and solutions:
1) If you’re aiming to do good in the short-term, I think this framework is useful:
expected impact = problem effectiveness x solution effectiveness x personal fit
I think problem effectiveness varies more than solution effectiveness, and is also far less commonly discussed in normal doing good discourse, so it makes sense for EA to emphasise it a lot.
However, solution effectiveness also matters a lot too. It seems plausible that EAs neglect it too much.
If you can find a great solution to a second tier problem area, that could be more effective than working on the average solution in a top tier area.
This circumstance could arise if you’re comparing a cause with a lot of effectiveness-focused people working on it (where all the top solutions are taken already) vs. a large cause with lots of neglected pockets; or due to personal fit considerations.
Personally, I don’t think solution effectiveness varies enough to make climate change the top thing to work on for people focused on existential risk, but I’d be keen to see 1-5% focused on the highest-upside and most neglected solutions to climate change.
2) If you’re doing longer-term career planning, however, then I think thinking in terms of specific solutions is often too narrow.
A cause is broad enough that you can set out to work on one in 5, 10 or even 20 years, and usefully aim towards it. But which solutions are most effective is normally going to change too much.
For longer-term planning, 80k uses the framework: problem effectiveness x size of contribution x fit
Size of contribution includes solution effectiveness, but we don’t emphasise it – the emphasise is on finding a good role or aptitude instead.
3) Causes or problem areas can just be thought of as clusters of solutions.
Causes are just defined instrumentally, as whatever clusters of solutions are useful for the particular type of planning you’re doing (because require common knowledge and connections).
E.g. 80k chooses causes that seem useful for career planning; OP chooses causes based on what it’s useful for their grantmakers to specialise in.
You can divide up the space into however many levels you like e.g.
International development → global health → malaria → malaria nets → malaria nets in a particular village.
Normally we call the things on the left ‘problem areas’ and on the left ‘solutions’ or ‘interventions’, but you can draw the line in different places.
Narrower groups let you be more targeted, but are more fragile for longer-term planning.
4) For similar reasons, you can compare solutions with similar frameworks to cause areas, including by using INT.
A couple of comments that might help readers of the thread separate problems and solutions:
1) If you’re aiming to do good in the short-term, I think this framework is useful:
I think problem effectiveness varies more than solution effectiveness, and is also far less commonly discussed in normal doing good discourse, so it makes sense for EA to emphasise it a lot.
However, solution effectiveness also matters a lot too. It seems plausible that EAs neglect it too much.
80k covers both in the key ideas series: https://80000hours.org/articles/solutions/
If you can find a great solution to a second tier problem area, that could be more effective than working on the average solution in a top tier area.
This circumstance could arise if you’re comparing a cause with a lot of effectiveness-focused people working on it (where all the top solutions are taken already) vs. a large cause with lots of neglected pockets; or due to personal fit considerations.
Personally, I don’t think solution effectiveness varies enough to make climate change the top thing to work on for people focused on existential risk, but I’d be keen to see 1-5% focused on the highest-upside and most neglected solutions to climate change.
2) If you’re doing longer-term career planning, however, then I think thinking in terms of specific solutions is often too narrow.
A cause is broad enough that you can set out to work on one in 5, 10 or even 20 years, and usefully aim towards it. But which solutions are most effective is normally going to change too much.
For longer-term planning, 80k uses the framework: problem effectiveness x size of contribution x fit
Size of contribution includes solution effectiveness, but we don’t emphasise it – the emphasise is on finding a good role or aptitude instead.
3) Causes or problem areas can just be thought of as clusters of solutions.
Causes are just defined instrumentally, as whatever clusters of solutions are useful for the particular type of planning you’re doing (because require common knowledge and connections).
E.g. 80k chooses causes that seem useful for career planning; OP chooses causes based on what it’s useful for their grantmakers to specialise in.
You can divide up the space into however many levels you like e.g.
International development → global health → malaria → malaria nets → malaria nets in a particular village.
Normally we call the things on the left ‘problem areas’ and on the left ‘solutions’ or ‘interventions’, but you can draw the line in different places.
Narrower groups let you be more targeted, but are more fragile for longer-term planning.
4) For similar reasons, you can compare solutions with similar frameworks to cause areas, including by using INT.
I talk more about that here: https://80000hours.org/articles/solutions/