“Note also that while we’re looking at such large pools of funding, the EA community will hardly be able to affect the funding ratio substantially. Therefore, this type of exercise will often just show us which single cause should be prioritised by the EA community and thereby act additive after all. This is different if we look at questions with multiplicative factors in which the decisions by the EA community can affect the input ratios like whether we should add more talent to the EA community or focus on improving existing talent.”
I agree that multiplicative factors are a big deal for areas where we collectively have strong control over key variables, rather than trying to move big global aggregates. But I think it’s the latter that we have in mind when talking about ‘causes’ rather than interventions or inputs working in particular causes (e.g. investment in hiring vs activities of current employees). For example:
“Should the EA community focus to add its resources on the efforts to reduce GCRs or to add them to efforts to help humanity flourish?”
If you’re looking at global variables like world poverty rates, or total risk of extinction it requires quite a lot of absolute impact before you make much of a proportional change.
E.g. if you reduce the prospective risk of existential catastrophe from 10% to 9%, you might increase the benefits of saving lives through AMF by a fraction of a percent, as it would be more likely that civilization would survive to see benefits of the AMF donations. But a 1% change would be unlikely to drastically alter allocations between catastrophic risks and AMF. And a 1% change in existential risk is an enormous impact: even in terms of current humans (relevant for comparison to AMF) that could represent tens of millions of expected current lives (depending on the timeline of catastrophe), and immense considering other kinds of beings and generations. If one were having such amazing impact in a scalable fashion it would seem worth going further at that point.
Diminishing returns of our interventions on each of these variables seems a much more important consideration that multiplicative effects between these variables: cost per percentage point of existential risk reduced is likely to grow many times as one moves along the diminishing returns curve.
“We could also think of the technical ideas to improve institutional decision making like improving forecasting abilities as multiplying with those institution’s willingness to implement those ideas.”
If we’re thinking about institutions like national governments changing willingness to implement the ideas seems much less elastic than improving the methods. If we look at a much narrower space, e.g. the EA community or a few actors in some core areas, the multiplicative factors key fields and questions.
If I was going to look for cross-cause multiplicative effects it would likely be for their effects on the EA community (e.g. people working on cause A generate some knowledge or reputation that helps improve the efficiency of work on cause B, which has more impact if cause B efforts are larger).
Great comment, thank you. I actually agree with you. Perhaps I should have focussed less on discussing the cause-level and more the interventions level, but I think it is still good to encourage more careful thinking on a cause-wide level even if it won’t affect the actual outcome of the decision-making. I think people rarely think about e.g. reducing extinction risks benefiting AMF donations as you describe it.
Let’s hope people will be careful to consider multiplicative effects if we can affect the distribution between key variables.
“Note also that while we’re looking at such large pools of funding, the EA community will hardly be able to affect the funding ratio substantially. Therefore, this type of exercise will often just show us which single cause should be prioritised by the EA community and thereby act additive after all. This is different if we look at questions with multiplicative factors in which the decisions by the EA community can affect the input ratios like whether we should add more talent to the EA community or focus on improving existing talent.”
I agree that multiplicative factors are a big deal for areas where we collectively have strong control over key variables, rather than trying to move big global aggregates. But I think it’s the latter that we have in mind when talking about ‘causes’ rather than interventions or inputs working in particular causes (e.g. investment in hiring vs activities of current employees). For example:
“Should the EA community focus to add its resources on the efforts to reduce GCRs or to add them to efforts to help humanity flourish?”
If you’re looking at global variables like world poverty rates, or total risk of extinction it requires quite a lot of absolute impact before you make much of a proportional change.
E.g. if you reduce the prospective risk of existential catastrophe from 10% to 9%, you might increase the benefits of saving lives through AMF by a fraction of a percent, as it would be more likely that civilization would survive to see benefits of the AMF donations. But a 1% change would be unlikely to drastically alter allocations between catastrophic risks and AMF. And a 1% change in existential risk is an enormous impact: even in terms of current humans (relevant for comparison to AMF) that could represent tens of millions of expected current lives (depending on the timeline of catastrophe), and immense considering other kinds of beings and generations. If one were having such amazing impact in a scalable fashion it would seem worth going further at that point.
Diminishing returns of our interventions on each of these variables seems a much more important consideration that multiplicative effects between these variables: cost per percentage point of existential risk reduced is likely to grow many times as one moves along the diminishing returns curve.
“We could also think of the technical ideas to improve institutional decision making like improving forecasting abilities as multiplying with those institution’s willingness to implement those ideas.”
If we’re thinking about institutions like national governments changing willingness to implement the ideas seems much less elastic than improving the methods. If we look at a much narrower space, e.g. the EA community or a few actors in some core areas, the multiplicative factors key fields and questions.
If I was going to look for cross-cause multiplicative effects it would likely be for their effects on the EA community (e.g. people working on cause A generate some knowledge or reputation that helps improve the efficiency of work on cause B, which has more impact if cause B efforts are larger).
Great comment, thank you. I actually agree with you. Perhaps I should have focussed less on discussing the cause-level and more the interventions level, but I think it is still good to encourage more careful thinking on a cause-wide level even if it won’t affect the actual outcome of the decision-making. I think people rarely think about e.g. reducing extinction risks benefiting AMF donations as you describe it.
Let’s hope people will be careful to consider multiplicative effects if we can affect the distribution between key variables.