I hate to do this, especially at the start, but I want to point out for you and others who have jobs related to forecasting that itās difficult to convince someone of something when their job relies on them not believing it. I think you should assume that you will think forecasting is more useful than it is.
As for your points, Iāll respond to some of them.
If you want to DM me, I can sign an NDA, and I may update my opinion depending on what these non-public uses of forecasting are.
I donāt think this is all that relevant. Iām not sure what forecasting research has really elicited on AI timelines. I agree that talk about timelines creates a lot of ābuzzā around AI but depending on your views, this is good or bad.
I agree that the impact of measurement-oriented research is difficult to measure, but importantly, not impossible. OWID for example should count how much their work is being cited and looked up. Conversely, I think it would be good to estimate, for FRI, how much $$ the change of the decision was worth and by what amount/āpercentage did FRI make that change more likely. I donāt think you really gave a good reason that FRI should be funded over anything else that simply has very diffuse benefits.
When do you think itās reasonable, if ever, for the EA community to āgive upā on funding more forecasting work?
If Iām being cynical, almost every field can say āAI will transform the fieldā though Iām not sure how much this is worth debating.
Not Josh, and also conflicted through the Social Science Prediction Platform (though we had pretty minimal funding from EA sources), but I wonder if it would be worth pooling non-public projects we know of and making BOTE estimates of hypothetical impact. Itās tricky because I donāt know of any RCTs (though Iām working on one now). But Iām extremely confident that across us we would think of some combination of orgs/āgovernments that collectively spend over $100 billion per year (ā¦ I can think of that alone) that are interested in forecasts in different ways. Now, imo the vast majority of places interested in forecasting are not going to do anything substantive with it, and itās hard to know what it means for one of these places to integrate forecastsāfor example, for an org spending $X, do forecasts inform 1% of their funding or what? Of the share they inform, how much do they move the needle? If estimates from people who work on forecasts may be optimistic (Iām not paid at all for it, but I choose to work on it because I think itās useful), happy to describe the situation to an outside observer privately.
I think the Social Science Prediction Platform (alongside a friend of mine who is doing something similar for clinical trials) are among the more interesting uses of forecasting/āPMs but Iām skeptical they will be uptaken to the degree/āimpact you might hope for.
do forecasts inform 1% of their funding or what?
Iām skeptical of things of the form āsmall percentage chance * big numberā. I think humans are really bad at estimating small percentages.
Would be happy to talk privately about any situations you are thinking of.
Thanks! I agree, Iām also generally skeptical of small chance * big number thingsāI was not intending 1% as an anchor but as an open questionāand not as a probability but as a concrete percent of the funding. For example, a big org uses forecasts, but perhaps they only use them in particular workstreams responsible for X% of funding, and those workstreams could be tracked. Then out of X%, how much do they move the needle?
Hi Josh, thanks for the response.
I hate to do this, especially at the start, but I want to point out for you and others who have jobs related to forecasting that itās difficult to convince someone of something when their job relies on them not believing it. I think you should assume that you will think forecasting is more useful than it is.
As for your points, Iāll respond to some of them.
If you want to DM me, I can sign an NDA, and I may update my opinion depending on what these non-public uses of forecasting are.
I donāt think this is all that relevant. Iām not sure what forecasting research has really elicited on AI timelines. I agree that talk about timelines creates a lot of ābuzzā around AI but depending on your views, this is good or bad.
I agree that the impact of measurement-oriented research is difficult to measure, but importantly, not impossible. OWID for example should count how much their work is being cited and looked up. Conversely, I think it would be good to estimate, for FRI, how much $$ the change of the decision was worth and by what amount/āpercentage did FRI make that change more likely. I donāt think you really gave a good reason that FRI should be funded over anything else that simply has very diffuse benefits.
When do you think itās reasonable, if ever, for the EA community to āgive upā on funding more forecasting work?
If Iām being cynical, almost every field can say āAI will transform the fieldā though Iām not sure how much this is worth debating.
Not Josh, and also conflicted through the Social Science Prediction Platform (though we had pretty minimal funding from EA sources), but I wonder if it would be worth pooling non-public projects we know of and making BOTE estimates of hypothetical impact. Itās tricky because I donāt know of any RCTs (though Iām working on one now). But Iām extremely confident that across us we would think of some combination of orgs/āgovernments that collectively spend over $100 billion per year (ā¦ I can think of that alone) that are interested in forecasts in different ways. Now, imo the vast majority of places interested in forecasting are not going to do anything substantive with it, and itās hard to know what it means for one of these places to integrate forecastsāfor example, for an org spending $X, do forecasts inform 1% of their funding or what? Of the share they inform, how much do they move the needle? If estimates from people who work on forecasts may be optimistic (Iām not paid at all for it, but I choose to work on it because I think itās useful), happy to describe the situation to an outside observer privately.
Hi Eva,
I think the Social Science Prediction Platform (alongside a friend of mine who is doing something similar for clinical trials) are among the more interesting uses of forecasting/āPMs but Iām skeptical they will be uptaken to the degree/āimpact you might hope for.
Iām skeptical of things of the form āsmall percentage chance * big numberā. I think humans are really bad at estimating small percentages.
Would be happy to talk privately about any situations you are thinking of.
Thanks! I agree, Iām also generally skeptical of small chance * big number thingsāI was not intending 1% as an anchor but as an open questionāand not as a probability but as a concrete percent of the funding. For example, a big org uses forecasts, but perhaps they only use them in particular workstreams responsible for X% of funding, and those workstreams could be tracked. Then out of X%, how much do they move the needle?
Anyway, happy to chat sometime!