Yeah, I think you make good points. I think that forecasts are useful on balance, and then people should investigate them. Do you think that forecasting like this will hurt the information landscape on average?
Personally, to me, people engaged in this forecasting generally seem more capable of changing their minds. I think the AI2027 folks would probably be pretty capable of acknowledging they were wrong, which seems like a healthy thing. Probably more so than the media and academic?
Seems like a lot of specific, quite technical criticisms.
Sure, so we agree?
(Maybe you think I’m being derogatory, but no, I’m just allowing people who scroll down to the comments to see that I think this article contains a lot of specific, quite technical criticisms. If in doubt, I say things I think are true.)
Do you think that forecasting like this will hurt the information landscape on average?
I’m a big fan of the development e.g. QRI’s process of making tools that make it increasingly easy to translate natural thoughts into more usable forms. In my dream world, if you told me your beliefs it would be in the form of a set of distributions that I could run a monte carlo sim on, having potentially substituted my own opinions if I felt differently confident than you (and maybe beyond that there’s still neater ways of unpacking my credences that even better tools could reveal).
Absent that, I’m a fan of forecasting, but I worry that overnormalising the naive I-say-a-number-and-you-have-no-idea-how-I-reached-it-or-how-confident-I-am-in-it form of it might get in the way of developing it into something better.
I dunno, I think that sounds galaxy-brained to me. I think that giving numbers is better than not giving them and that thinking carefully about the numbers is better than that. I don’t really buy your second order concerns (or think they could easily go in the opposite direction)
Yeah, I think you make good points. I think that forecasts are useful on balance, and then people should investigate them. Do you think that forecasting like this will hurt the information landscape on average?
Personally, to me, people engaged in this forecasting generally seem more capable of changing their minds. I think the AI2027 folks would probably be pretty capable of acknowledging they were wrong, which seems like a healthy thing. Probably more so than the media and academic?
Sure, so we agree?
(Maybe you think I’m being derogatory, but no, I’m just allowing people who scroll down to the comments to see that I think this article contains a lot of specific, quite technical criticisms. If in doubt, I say things I think are true.)
Ah, sorry, I misunderstood that as criticism.
I’m a big fan of the development e.g. QRI’s process of making tools that make it increasingly easy to translate natural thoughts into more usable forms. In my dream world, if you told me your beliefs it would be in the form of a set of distributions that I could run a monte carlo sim on, having potentially substituted my own opinions if I felt differently confident than you (and maybe beyond that there’s still neater ways of unpacking my credences that even better tools could reveal).
Absent that, I’m a fan of forecasting, but I worry that overnormalising the naive I-say-a-number-and-you-have-no-idea-how-I-reached-it-or-how-confident-I-am-in-it form of it might get in the way of developing it into something better.
I dunno, I think that sounds galaxy-brained to me. I think that giving numbers is better than not giving them and that thinking carefully about the numbers is better than that. I don’t really buy your second order concerns (or think they could easily go in the opposite direction)