This was a good catch! I did actually mean world GDP, not world GDP growth. Because people have already predicted on this, I added the correct questions above as new questions, and am leaving the previous questions here for reference:
Amandango
Karma: 776
Will there be a 4 year interval in which world GDP growth doubles before the first 1 year interval in which world GDP growth doubles? Will there be a 4 year interval in which world GDP growth doubles before the first 1 year interval in which world GDP growth doubles? Will AGI cause existential catastrophe conditional on there being a 4 year period of doubling of world GDP growth before a 1 year period of doubling? Will AGI cause existential catastrophe conditional on there being a 4 year period of doubling of world GDP growth before a 1 year period of doubling? Will AGI cause existential catastrophe conditional on there being a 1 year period of doubling of world GDP growth without there first being a 4 year period of doubling? Will AGI cause existential catastrophe conditional on there being a 1 year period of doubling of world GDP growth without there first being a 4 year period of doubling?
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I’m counting using this to express credence on claims as a non-prediction use!
Thanks!! It’s primarily intended for prediction, but I feel excited about people experimenting with different ways of using this and seeing which are most useful & how they change discussions, so am interested to see what happens if you use it for other purposes too.
Thanks Jacob!!
This is a really good point, thanks for bringing this up! We’ll look into how to improve this.
Yeah this seems pretty reasonable. It’s actually stark looking at the Our World in Data – that seems really high per year. Do you have your model somewhere? I’d be interested to see it.
A rough distribution (on a log scale) based on the two points you estimated for wars (95% < 1B people die in wars, 85% < 10M people die in wars) gives a median of ~2,600 people dying. Does that seem right?
I noticed that your prediction and jmh’s prediction are almost the exact opposite:
Teerth: 80%: No human being would be living on another celestial object (Moon, another planet or asteroid) (by 2030)
jmh: 90%: Humans living on the moon (by 2030)
(I plotted this here to show the difference, although this makes the assumption that you think the probability is ~uniformly distributed from 2030 – 2100). Curious why you think these differ so much? Especially jmh, since 90% by 2030 is more surprising—the Metaculus prediction for when the next human being will walk on the moon has a median of 2031.
Thank you for putting this spreadsheet database together! This seemed like a non-trivial amount of work, and it’s pretty useful to have it all in one place. Seeing this spreadsheet made me want:
More consistent questions such that all these people can make comparable predictions
Ability to search and aggregate across these so we can see what the general consensus is on various questions
I thought the 2008 GCR questions were really interesting, and plotted the median estimates here. I was surprised by / interested in:
How many more deaths were expected from wars than other disaster scenarios
For superintelligent AI, most of the probability mass was < 1M deaths, but there was a high probability (5%) on extinction
A natural pandemic was seen as more likely to cause > 1M deaths than an engineered pandemic (although less likely to cause > 1B deaths)
FYI, this is on a log scale. I plotted extinction as > 8B deaths.
(posted a similar comment on the EA forum link, since it seems like people are engaging more with this post there)
This is a really great conditional question! I’m curious what probability everyone puts on the assumption (GPT-N gets us to TAI) being true (i.e. do these predictions have a lot of weight in your overall TAI timelines)?
I plotted human_generated_text and sairjy’s answers:
I also just discovered BERI’s x-risk prediction market question set and Jacobjacob & bgold’s AI forecasting database, which seem really helpful for this!
Here’s a colab you can use to do this! I used it to make these aggregations:
The Ethan + Datscilly distribution is a calculation of:
- 25% * Your inside view of prosaic AGI
- 60% * Datscilly’s prediction (renormalized so that all the probability < 2100)
- 15% * We get AGI > 2100 or never
This has an earlier median (2040) than your original distribution (2046).(Note for the colab: You can use this to run your own aggregations by plugging in Elicit snapshots of the distributions you want to aggregate. We’re actively working on the Elicit API, so if the notebook breaks lmk so we can update it).
This links to a uniform distribution, guessing you didn’t mean that! To link to your distribution, take a snapshot of your distribution, and then copy the snapshot url (which appears as a timestamp at the bottom of the page) and link that.
Daniel and SDM, what do you think of a bet with 78:22 odds (roughly 4:1) based on the differences in your distributions, i.e: If AGI happens before 2030, SDM owes Daniel $78. If AGI doesn’t happen before 2030, Daniel owes SDM $22.
This was calculated by:
Identifying the earliest possible date with substantial disagreement (in this case, 2030)
Finding the probability each person assigns to the date range of now to 2030:
Finding a fair bet
According to this post, a bet based on the arithmetic mean of 2 differing probability estimates yields the same expected value for each participant. In this case, the mean is (5%+39%)/2=22% chance of AGI before 2030, equivalent to 22:78 odds.
$78 and $22 can be scaled appropriately for whatever size bet you’re comfortable with
The blue distribution labeled “Your distribution” in this snapshot is Alex’s updated 2020 prediction.
An update: We’ve set up a way to link your LessWrong account to your Elicit account. By default, all your LessWrong predictions will show up in Elicit’s binary database but you can’t add notes or filter for your predictions.
If you link your accounts, you can:
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If you want us to link your accounts, send me an email (amanda@ought.org) with your LessWrong username and your Elicit account email!