I wonder if getting the chatbot to roleplay survey taker, and having it categorize responses of collect them, would help?
With the goal of actually trying to use the chatbot to better understand what views are common and what people's objections are. Don't just try to make the chatbot curious, figure out what would motivate true curiosity.
Have you considered looking at the old Foresight Exchange / Ideosphere data? It should be available, and it's old enough that there might be a useful number of long-term forecasts there.
Yep, those are extremely different drugs with very different effects. They do in fact take a while and the effects can be much more subtle.
having read a few books about ADHD, my best guess is that I have (and had) a moderate case of it.
when I'm behind the wheel of a car and X = "the stoplight in front of me" and Y = "that new Indian restaurant", it is bad
Which is one of the reasons why I don't drive.
If your ADHD is interfering with your driving, that does not sound like a moderate case!
But option #3 is much better: take medication for six weeks and see what happens.
My expectation is that you will likely get a lot of information from trying the meds for 6 days; 6 weeks sounds like a very long experiment. Quite possibly even 2-3 days or just 1 day. 6 weeks sounds like enough time to test out a few doses and types (time release vs not, for example) and form opinions. And possibly get an understanding of whether you want to take it every day or only some days and maybe even how to figure out which is which.
All of which is to say: yes, perform cheap experiments! They're great! This one is probably far faster (if not much cheaper in dollar terms) than you're predicting.
Bitcoin Hivemind (nee Truthcoin) is the authority on doing this in a truly decentralized fashion. The original whitepaper is well worth a read. The fundamental insight: it's easier to coordinate on the truth than on something else; incentivizing defection to the truth works well.
Judges have reputation. If you judge against the consensus, you lose reputation, and the other (consensus) judges gain it. The amount you lose depends on the consensus: being the lone dissenter has a very small cost (mistakes have costs, but small ones), but being part of a near-majority is very costly. So if your conspiracy is almost but not quite winning, the gain from defecting against the conspiracy is very high.
Adaptations to a non-blockchain context should be fairly easy. In that case, you have a central algorithmic resolver that tracks reputation, but defers to its users for resolution of a particular market (and applies the reputation algorithm).
Thank you!
I went ahead and created the 2024 version of one of the questions. If you're looking for high-liquidity questions to include, which seems like a good way to avoid false alarms / pranks, this one seems like a good inclusion.
There are a bunch of lower-liquidity questions; including a mix of those with some majority-rule type logic might or might not be worth it.
Thank you! Much to think about, but later...
If there are a large number of true-but-not-publicly-proven statements, does that impose a large computational cost on the market making mechanism?
I expect that the computers running this system might have to be fairly beefy, but they're only checking proofs.
They're not, though. They're making markets on all the interrelated statements. How do they know when they're done exhausting the standing limit orders and AMM liquidity pools? My working assumption is that this is equivalent to a full Bayesian network and explodes exponentially for all the same reasons. In practice it's not maximally intractable, but you don't avoid the exponential explosion either -- it's just slower than the theoretical worst case.
If every new order placed has to be checked against the limit orders on every existing market, you have a problem.
For thickly traded propositions, I can make money by investing in a proposition first, then publishing a proof. That sends the price to $1 and I can make money off the difference. Usually, it would be more lucrative to keep my proof secret, though.
The problem I'm imaging comes when the market is trading at .999, but life would really be simplified for the market maker if it was at actually, provably 1. So it could stop tracking that price as something interesting, and stop worrying about the combinatorial explosion.
So you'd really like to find a world where once everyone has bothered to run the SAT-solver trick and figure out what route someone is minting free shares through, that just becomes common knowledge and everyone's computational costs stop growing exponentially in that particular direction. And furthermore, the first person to figure out the exact route is actually rewarded for publishing it, rather than being able to extract money at slowly declining rates of return.
In other words: at what point does a random observer start turning "probably true, the market said so" into "definitely true, I can download the Coq proof"? And after that point, is the market maker still pretending to be ignorant?
This is very neat work, thank you. One of those delightful things that seems obvious in retrospect, but that I've never seen expressed like this before. A few questions, or maybe implementation details that aren't obvious:
For complicated proofs, the fully formally verified statement all the way back to axioms might be very long. In practice, do we end up with markets for all of those? Do they each need liquidity from an automated market maker? Presumably not if you're starting from axioms and building a full proof, and that applies to implications and conjunctions and so on as well, because the market doesn't need to keep tracking things that are proven. However:
First Alice, who can prove , produces many many shares of for free. This is doable if you have a proof for by starting from a bunch of free shares and using equivalent exchange. She sells these for $0.2 each to Bob, pure profit.
In order for this to work, the market must be willing to maintain a price for these shares in the face of a proof that they're equivalent to . Presumably the proof is not yet public, and if Alice has secret knowledge she can sell with a profit-maximizing strategy.
She could simply not provide the proof to the exchange, generating and pairs and selling only the latter, equivalent to just investing in A, but that requires capital. It's far more interesting if she can do it without tying up the capital.
So how does the market work for shares of proven things, and how does the proof eventually become public? Is there any way to incentivize publishing proofs, or do we simply get a weird world where everyone is pretty sure some things are true but the only "proof" is the market price?
If there are a large number of true-but-not-publicly-proven statements, does that impose a large computational cost on the market making mechanism?
Second question: how does this work in different axiom systems? Do we need separate markets, or can they be tied together well? How does the market deal with "provable from ZFC but not Peano"? "Theorem X implies corollary Y" is a thing we can prove, and if there's a price on shares of "Theorem X" then that makes perfect sense, but does it make sense to put a "price" on the "truth" of the ZFC axioms?
Presumably if we have a functional market that distinguishes Peano proofs from ZFC proofs, we'd like to distinguish more axiom sets. What happens if someone sets up an inconsistent axiom set, and that inconsistency is found? Presumably all dependent markets become a mess and there's a race to the exits that extracts all the liquidity from the AMMs; that seems basically fine. But can that be contained to only those markets, without causing weird problems in Peano-only markets?
Probably some of this would be clearer if I knew a bit more about modern proof formalisms.
My background: educated amateur. I can design simple to not-quite-simple analog circuits and have taken ordinary but fiddly material property measurements with electronics test equipment and gotten industrially-useful results.
One person alleges an online rumor that poorly connected electrical leads can produce the same graph. Is that a conventional view?
I'm not seeing it. With a bad enough setup, poor technique can do almost anything. I'm not seeing the authors as that awful, though. I don't think they're immune from mistakes, but I give low odds on the arbitrarily-awful end of mistakes.
You can model electrical mistakes as some mix of resistors and switches. Fiddly loose contacts are switches, actuated by forces. Those can be magnetic, thermal expansion, unknown gremlins, etc. So "critical magnetic field" could be "magnetic field adequate to move the thing". Ditto temperature. But managing both problems at the same time in a way that looks like a plausible superconductor critical curve is... weird. The gremlins could be anything, but gremlins highly correlated with interesting properties demand explanation.
Materials with grains can have conducting and not-conducting regions. Those would likely have different thermal expansion behaviors. Complex oxides with grain boundaries are ripe for diode-like behavior. So you could have a fairly complex circuit with fairly complex temperature dependence.
I think this piece basically comes down to two things:
If the noise floor doesn't rule out copper, you can get the curves with adequately well chosen thermal and magnetic switches from loose contacts. But there are enough graphs that those errors have to be remarkably precisely targeted, if the graphs aren't fraud.
Another thing I'd love to see on this front: multiple graphs of the same sort from the same sample (take it apart and put it back together), from different locations on the sample, from multiple samples. Bad measurement setups don't repeat cleanly.
My question for the NO side: what does the schematic of the bad measurement look like? Where do you put the diodes? How do you manage the sharp transition out of the zero-resistance regime without arbitrarily-fine-tuned switches?
Do any other results from the 6-person or journal-submitted LK papers stand out as having the property, "This is either superconductivity or fraud?"
The field-cooled vs zero-field-cooled magnetization graph (1d in the 3-author paper, 4a in the 6-author paper). I'm far less confident in this than the above; I understand the physics much less well. I mostly mention it because it seems under-discussed from what I've seen on twitter and such. This is an extremely specific form of thermal/magnetic hysteresis that I don't know of an alternate explanation for. I suspect this says more about my ignorance than anything else, but I'm surprised I haven't seen a proposed explanation from the NO camp.
Why would this be misleading?