Clarification: The GJO coronavirus questions are not funded by Open Phil. The thing funded by Open Phil is this dashboard (linked from our blog post) put together by Good Judgment Inc. (GJI), which runs both GJO (where anyone can sign up and make forecasts) and their Superforecaster Analytics service (where only superforecasters can make forecasts). The dashboard Open Phil funded uses the Superforecaster Analytics service, not GJO. Also, I don’t think Tetlock is involved in GJO (or GJI in general) much at all these days, but GJI is indeed the commercial spinoff from the Good Judgment Project (GJP) that Tetlock & Mellers led and which won the IARPA ACE forecasting competition and resulted in the research covered in Tetlock’s book Superforecasting.
Note that the headline (“Good Judgement Project: gjopen.com”) is still confusing, since it seems to be saying GJP = GJO. The thing that ties the items under that headline is that they are all projects of GJI. Also, “Of the questions which have been added recently” is misleading since it seems to be about the previous paragraph (the superforecasters-only questions), but in fact all the links go to GJO.
Edited again. If you want, throw me a bone: what’s the last explicit probabilistic prediction you’ve made? Also, I liked your review on How to Measure Anything, which feels relevant to the topic at hand. NNTR.
The last explicit probabilistic prediction I made was probably a series of forecasts on my most recent internal Open Phil grant writeup, since it’s part of our internal writeup template to prompt the grant investigator for explicit probabilistic forecasts about the grant. But it could’ve easily been elsewhere; I do somewhat-often make probabilistic forecasts just in conversation, or in GDoc/Slack comments, though for those I usually spend less time pinning down a totally precise formulation of the forecasting statement, since it’s more about quickly indicating to others roughly what my views are rather than about establishing my calibration across a large number of precisely stated forecasts.
Nice to see a newsletter on this topic!
Clarification: The GJO coronavirus questions are not funded by Open Phil. The thing funded by Open Phil is this dashboard (linked from our blog post) put together by Good Judgment Inc. (GJI), which runs both GJO (where anyone can sign up and make forecasts) and their Superforecaster Analytics service (where only superforecasters can make forecasts). The dashboard Open Phil funded uses the Superforecaster Analytics service, not GJO. Also, I don’t think Tetlock is involved in GJO (or GJI in general) much at all these days, but GJI is indeed the commercial spinoff from the Good Judgment Project (GJP) that Tetlock & Mellers led and which won the IARPA ACE forecasting competition and resulted in the research covered in Tetlock’s book Superforecasting.
Thanks for the correction; edited.
Note that the headline (“Good Judgement Project: gjopen.com”) is still confusing, since it seems to be saying GJP = GJO. The thing that ties the items under that headline is that they are all projects of GJI. Also, “Of the questions which have been added recently” is misleading since it seems to be about the previous paragraph (the superforecasters-only questions), but in fact all the links go to GJO.
Edited again. If you want, throw me a bone: what’s the last explicit probabilistic prediction you’ve made? Also, I liked your review on How to Measure Anything, which feels relevant to the topic at hand. NNTR.
The headline looks broken in my browser. It looks like this:
/(Good Judgement?[^]*)|(Superforecast(ing|er))/gi
The last explicit probabilistic prediction I made was probably a series of forecasts on my most recent internal Open Phil grant writeup, since it’s part of our internal writeup template to prompt the grant investigator for explicit probabilistic forecasts about the grant. But it could’ve easily been elsewhere; I do somewhat-often make probabilistic forecasts just in conversation, or in GDoc/Slack comments, though for those I usually spend less time pinning down a totally precise formulation of the forecasting statement, since it’s more about quickly indicating to others roughly what my views are rather than about establishing my calibration across a large number of precisely stated forecasts.