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This reverts commit 676560c948.
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Nuno Sempere 2023-05-15 03:48:19 +00:00
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blog/2020/11/22/predicting-the-value-of-small-altruistic-projects-a-proof-of/index.md
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@ -73,7 +73,7 @@ I also had a payout for insightful comments, such that the nth most upvoted comm
Note that the projects were _not_ chosen so as to maximize impact, but rather as to maximize information about whether their value could be predicted.
![](https://images.nunosempere.com/blog/2020/11/10/incentive-problems-with-current-forecasting-competitions/.f736a63590b98d329a456b5ff1cc055da86d416c.png/0e2bfcbc0fa993098421b08b67af411ec30e8ffb.png)
![](.images/0e2bfcbc0fa993098421b08b67af411ec30e8ffb.png)
We observe that:
@ -96,7 +96,7 @@ Predictions:
* Centered 50% confidence interval: 33 to 74
* Centered 95% confidence interval: 11 to 111
![](https://images.nunosempere.com/blog/2020/11/10/incentive-problems-with-current-forecasting-competitions/.f736a63590b98d329a456b5ff1cc055da86d416c.png/4a4419c6711561edc7b61a8c0633da2717c0913f.png)
![](.images/4a4419c6711561edc7b61a8c0633da2717c0913f.png)
Actual upvotes after one month: 31
@ -114,7 +114,7 @@ Predictions:
* Centered 50% confidence interval: 28 to 68
* Centered 95% confidence interval: 9 to 106
![](https://images.nunosempere.com/blog/2020/11/10/incentive-problems-with-current-forecasting-competitions/.f736a63590b98d329a456b5ff1cc055da86d416c.png/a71da8f5dd6340d4f81828cb1cb5b20b292c3188.png)
![](.images/a71da8f5dd6340d4f81828cb1cb5b20b292c3188.png)
Actual upvotes after one month: 20 for the [first post](https://www.lesswrong.com/posts/yWmmYLCJft7u7XL5o/some-examples-of-technology-timelines), 49 for the [second one](https://www.lesswrong.com/posts/FaCqw2x59ZFhMXJr9/a-prior-for-technological-discontinuities). I'm taking 49 as the resolution.
@ -132,7 +132,7 @@ Predictions:
* Centered 50% confidence interval: 15 to 57
* Centered 95% confidence interval: 4 to 91
![](https://images.nunosempere.com/blog/2020/11/10/incentive-problems-with-current-forecasting-competitions/.f736a63590b98d329a456b5ff1cc055da86d416c.png/e1d6f9b8bfd27b8f9102143b112b9d9c7fc75fb7.png)
![](.images/e1d6f9b8bfd27b8f9102143b112b9d9c7fc75fb7.png)
Actual upvotes after one month: 22
@ -150,7 +150,7 @@ Predictions:
* Centered 50% confidence interval: 17 to 60
* Centered 95% confidence interval: 6 to 102
![](https://images.nunosempere.com/blog/2020/11/10/incentive-problems-with-current-forecasting-competitions/.f736a63590b98d329a456b5ff1cc055da86d416c.png/7da9d104143c060272f96cbd12bcc27e2c71dbf9.png)
![](.images/7da9d104143c060272f96cbd12bcc27e2c71dbf9.png)
Actual upvotes after one month: 20
@ -167,7 +167,7 @@ Predictions:
* Centered 50% confidence interval: 19 to 59
* Centered 95% confidence interval: 7 to 92
![](https://images.nunosempere.com/blog/2020/11/10/incentive-problems-with-current-forecasting-competitions/.f736a63590b98d329a456b5ff1cc055da86d416c.png/89ff6294dfe357bfebc3640584d42060934103c4.png)
![](.images/89ff6294dfe357bfebc3640584d42060934103c4.png)
Actual upvotes after one month: 27
@ -182,7 +182,7 @@ A further idea was my proposal for my Summer Research Fellowship at FHI, though
* Centered 50% confidence interval: 24 to 70
* Centered 95% confidence interval: 10 to 103
![](https://images.nunosempere.com/blog/2020/11/10/incentive-problems-with-current-forecasting-competitions/.f736a63590b98d329a456b5ff1cc055da86d416c.png/9e6a4434c603e9fd94e9a6819fff247011a5ab93.png)
![](.images/9e6a4434c603e9fd94e9a6819fff247011a5ab93.png)
I take these data-points as further evidence that this setup is interesting or worth it; arguably a major take-away for this project is “a fairly simple forecasting system is able to produce a project which gets accepted to the FHI summer fellowship.” Because the program got ~300 [applications](https://forum.effectivealtruism.org/posts/EPGdwe6vsCY7A9HPa/review-of-fhi-s-summer-research-fellowship-2020), but only 27 participants were accepted, this puts this forecasting setup on the top 9% of applicants in terms of some fuzzy “optimization power” (though this is a simplification, because the project proposal was probably one of many factors.)