How might I combine these two datasets? One is a binary market, the other is a date market. So for any date point, one is a percentage P(turing test before 2030) the other is a cdf across a range of dates P(weakly general AI publicly known before that date).

Here are the two datasets. 

Suggestions:

• Fit a normal distribution to the turing test market such that the 1% is at the current day and the P(X<2030) matches the probability for that data point
• Mirror the second data set but for each data point elevate the probabilities before 2030 such that P(X<2030) matches the probability for the first dataset

Thoughts:

Overall the problem is that one doesn't know what distribution to fit the second single datapoint to. The second suggestion just uses the distribution of the second data set for the first, but that seems quite complext.

"Why would you want to combine these datasets?"

Well they are two different views when something like AGI will appear. Seems good to combine them.

Suggested market. Happy to take suggestions on how to improve it:

https://manifold.markets/NathanpmYoung/will-o3-perform-as-well-on-the-fron?play=true 

I guess I frame this as "vibes are signals too". Like if my body doesn't like someone, that's a signal. And it might be they smell or have an asymmetric face, but also they might have some distrustworthy trait that my body recognises (because figuring out lying is really important evolutionarily). 

I think it's good to analyse vibes and figure out if unfair judgemental things are enough to account for most of the bad vibes or if there is a missing component that may be fair.

Seems fine, though this doesn't seem like the central crux. 

Currently:

• Prediction markets are used
• Argument maps tend not to be.

My bird flu risk dashboard is here:
 

http://birdflurisk.com 

If you find it valuable, you could upvote it on HackerNews:

https://news.ycombinator.com/item?id=42632552 

Yeah I wish someone would write a condensed and less onanistic version of Planecrash. I think one could get much of the benefit in a much shorter package. 

Error checking in important works is moderately valuable. 

I recall thinking this article got a lot right. 

I remain confused about the non-linear stuff, but I have updated to thinking that norms should be that stories are accurate not merely informative with caveats given. 

I am glad people come into this community to give critique like this. 

Solid story. I like it. Contains a few useful frames and is memorable as a story. 

I have listened to this essay about 3 times and I imagine I might do so again. Has been a valuable addition to my thinking about whether people have contact with reality and what their social goals might be.