I’ve been thinking a lot about the lack of non-EA interest or focus on forecasting or related tools. I was very surprised when I made Guesstimate and there was both excitement from several people, but not that much excitement from most businesses or governments.
I think that forecasting of the GJP sort is still highly niche. Almost no one knows of it or understands the value. You can look at this as similar to specific advances in, say, type theory or information theory.
The really smart groups that have interests in improving their long term judgement seem to be financial institutions and similar. These are both highly secretive, and not interested in spending extra effort helping outside groups.
So to really advance a field like judgemental forecasting would require a combination of expertise, funding, and interest in helping the broad public, and this is a highly unusual combination. I imagine that if IARPA wasn’t around in time to both be interested in and able to fund GJP’s efforts, much less would have happened there. I’d also personally point out that I’d expect that IARPA’s funding of it was around 1/3rd or maybe 1/20th as efficient as it would have been if OpenPhil would have organized a more directed effort, in terms of global benefit.
This makes me think that there are probably many other very specific technology and research efforts that also be exciting for us to focus on, but we don’t have the expertise to recognize them. May may have gotten lucky with forecasting/estimation tech, as that was something we had to get close to anyway for other reasons.
Also worth noting that the managing director of IARPA’s forecasting program was Jason Matheny, who previously founded New Harvest (which does cultured meat research, and was the first such org AFAIK) and did x-risk research at FHI.
I’ve been thinking a lot about the lack of non-EA interest or focus on forecasting or related tools. I was very surprised when I made Guesstimate and there was both excitement from several people, but not that much excitement from most businesses or governments.
I think that forecasting of the GJP sort is still highly niche. Almost no one knows of it or understands the value. You can look at this as similar to specific advances in, say, type theory or information theory.
The really smart groups that have interests in improving their long term judgement seem to be financial institutions and similar. These are both highly secretive, and not interested in spending extra effort helping outside groups.
So to really advance a field like judgemental forecasting would require a combination of expertise, funding, and interest in helping the broad public, and this is a highly unusual combination. I imagine that if IARPA wasn’t around in time to both be interested in and able to fund GJP’s efforts, much less would have happened there. I’d also personally point out that I’d expect that IARPA’s funding of it was around 1/3rd or maybe 1/20th as efficient as it would have been if OpenPhil would have organized a more directed effort, in terms of global benefit.
This makes me think that there are probably many other very specific technology and research efforts that also be exciting for us to focus on, but we don’t have the expertise to recognize them. May may have gotten lucky with forecasting/estimation tech, as that was something we had to get close to anyway for other reasons.
Also worth noting that the managing director of IARPA’s forecasting program was Jason Matheny, who previously founded New Harvest (which does cultured meat research, and was the first such org AFAIK) and did x-risk research at FHI.
Yep, and a few others at IARPA who worked around the forecasting stuff were also EAs or close.