In response to Open Thread #38
Comment author: WillPearson 22 August 2017 10:19:04AM 3 points [-]

I've been reading Superforecasting and my take away is that to have good predictions at the world you need to have a multiplicity of view points and quantify and breakdown the estimates fermi-style.

So my question is, has there been any collective attempts at model building for prediction purposes? Try and get all the hedgehogs together with their big ideas and synthesize them to form a collective fox-y model?

I know there are prediction markets, but you don't know what information that a price has synthesized so it is hard to bet on them, if you only have a small bit of information and do not think you know better than the market as a whole.

It would seem that if we could share a pool of predictive power between us we could make better decisions about how to intervene in the world.

Comment author: poppingtonic 23 August 2017 12:12:49PM 1 point [-]

I think that the Good Judgment Project (founded by Philip Tetlock, the author of Superforecasting) is trying to build this with their experiments.

Comment author: poppingtonic 24 July 2017 01:36:04PM 2 points [-]

A complication: Whole-brain emulation seeks to instantiate human minds, which are conscious by default, in virtual worlds. Any suffering involved in that can presumably be edited away if I go by what Robin Hanson wrote in Age of Em. Hanson also thinks that this might be a more likely first route for HLAI, which suggests that may be the "lazy solution", compared to mathematically-based AGI. However, in the S-risks talk at EAG Boston, an example of s-risk was something like this.

Analogizing like this isn't my idea of a first-principle argument, and therefore what I'm saying is not airtight either, considering the levels of uncertainty for paths to AGI.

Comment author: poppingtonic 11 October 2016 09:04:24PM *  7 points [-]

Quoting Nate's supplement from OpenPhil's review of "Proof-producing reflection for HOL" (PPRHOL) :

there are basic gaps in our models of what it means to do good reasoning (especially when it comes to things like long-running computations, and doubly so when those computations are the reasoner’s source code)

How far along the way are you towards narrowing these gaps, now that "Logical Induction" is a thing people can talk about? Are there variants of it that narrow these gaps, or are there planned follow-ups to PPRHOL that might improve our models? What kinds of experiments seem valuable for this subgoal?

Comment author: poppingtonic 11 October 2016 08:39:51PM 7 points [-]

Thanks for doing this AMA! Which of the points in your strategy have you seen a need to update on, based on the unexpected progress of having published the "Logical Induction" paper (which I'm currently perusing)?