Robin Hanson

My first reaction as well. His bio [1] does seem to support the assertion, and I've heard of his work on prediction markets and the term the Great Filter, but that same bio is also all sorts of red-flaggy to me. He has "1100 media mentions?" You need to put that in your university bio page? 1. https://mason.gmu.edu/~rhanson/bio.html

It's not necessarily far away. It's diffuse. Unless you are educated about climate or ecosystem dynamics to contextualize your lived experience in a wider (space/time) scope many will use faulty heuristics and faulty memory to rationalize or ignore it any way they want. This might be an issue that's ingrained deeply into our limited biological computing machinery/wetware. And this is also Great Filter material... http://mason.gmu.edu/~rhanson/greatfilter.html

The closing is a choice quote: So is Robin Hanson America’s creepiest economist? I’m not saying he is. But it is certainly a striking question. and the slate bio is worth contrasting against his academic bio: http://mason.gmu.edu/~rhanson/bio.html The charitable summary might be Numerically ept, Socially inept.

I'm surprised that nobody links to the best proposed solution to this problem, so I will: https://mason.gmu.edu/~rhanson/dumpceo.html The US could, if it was inclined, legalise prediction markets & investors could subsidise markets for stock price conditional on the CEO stepping down, thus revealing in the strongest possible wisdom-of-the-market sense whether the CEO is going a good job. This would solve the problem modulo short term inneficiencies and be much better than the status quo.

It seems some people in this thread need a reminder of what the Great Filter is: https://mason.gmu.edu/~rhanson/greatfilter.html

That passage is something of an afterthought, from the epilogue of his book, but it's still disappointing he doesn't credit Robin Hanson for coming up with the Great Filter concept[1], or mention the x-risk[2] community which contemplates this stuff. [1] http://mason.gmu.edu/~rhanson/greatfilter.html [2] https://nickbostrom.com/existential/risks.html / https://wiki.lesswrong.com/wiki/Existential_risk

The rapid emergence of single-celled life on Earth is not necessarily evidence that it was an easy step for evolution. See the discussion surrounding “conditional on success, all the hard steps, no matter how hard, take about the same time” in this article: http://mason.gmu.edu/~rhanson/greatfilter.html

> My understanding is that current life developed about as quickly as it possibly could have, at least on a geological scale. This is commonly quoted, but actually not at all implied by the data, at least as long as you allow for the very real possibility that the road from inert matter to conscious observers required multiple improbable steps. For counter-intuitive probabilistic reasons, you can't infer the "improbableness" of a step from the amount of time it took to occur when several such steps occur. http://mason.gmu.edu/~rhanson/greatfilter.html

Is there anything revelatory in this article? I didn't see any links or references to new papers/ideas, but some Googling returned this 2016 PDF[1] titled 'The Case for a Gaian Bottleneck' by Aditya Chopra from ANU. There's been discussion in the past[2][3] about these 'Great Filters' that prevent life from occurring everywhere in the universe. [1]http://adi.life/pubs/ChopraLineweaver2016.pdf [2]http://mason.gmu.edu/~rhanson/greatfilter.html [3]http://waitbutwhy.com/2014/05/fermi-paradox.html

To take this suggestion a step further, it would be great if this new nation was run as a Futarchy [1]. The basic idea is we use prediction markets to determine if certain policies would raise GDP, and those that do become law. Projects like Augur [2] are trying to make ubiquitous prediction markets possible by relying on Blockchain-like decentralization. [1] http://mason.gmu.edu/~rhanson/futarchy.html [2] http://www.augur.net/

http://mason.gmu.edu/~rhanson/greatfilter.html "Humanity seems to have a bright future, i.e., a non-trivial chance of expanding to fill the universe with lasting life. But the fact that space near us seems dead now tells us that any given piece of dead matter faces an astronomically low chance of begating such a future. There thus exists a great filter between death and expanding lasting life, and humanity faces the ominous question: how far along this filter are we? "Combining standard stories of biologists, astronomers, physicists, and social scientists would lead us to expect a much smaller filter than we observe. Thus one of these stories must be wrong. To find out who is wrong, and to inform our choices, we should study and reconsider all these areas."

Agreed that it's unfeasible for now, of course, but I'm a little amazed people aren't seeing the uses of this. We can edit, directly observe, and record/playback simulated brains. We can test ten million different models on top of a recorded simulation and see which one fits best. Eero doesn't think we could learn about how the brain works by simulating a trillion slightly different permutations on a brain, or (maybe more ethically) small subsystems of a brain, and observing how each behaves? Sweet god, the economic implications! http://mason.gmu.edu/~rhanson/uploads.html Horrifying, maybe, but I don't see how people can get away with suggesting this will never be valuable to anyone.

>Someone in the prediction market might agree that free higher education reduces inequality but might also think that it will increase the government’s cost of financing its spending. The latter is what usually gives politicians trouble with financial markets. How would a prediction market resolve this issue? One approach would be to have multiple markets, that track endpoints like inequality and interest rates separately for any given candidate policy. In the best case, prediction markets could give you accurate forecasts on a large number of candidate policies, and you could select a policy that the market thinks does a pretty good job according to lots of relevant endpoints. (My hunch is that our current system is bad at searching for such win/win policies, preferring instead the drama that comes from clashing over win/lose policies. For example, you mention free higher education, but how much does the average college grad really use or remember from their degree? I'd argue there is a lot of territory in apprenticeships that is currently unexplored, and smart policy could facilitate this -- especially if we start with small-scale experimentation.) You're absolutely correct that the market can't help with moral questions such as how much government spending is justifiable in pursuit of reduced inequality. Robin Hanson proposes eventually moving to a system where the job of elected officials is to manage metrics related to what voters want out of government policies,…

I don’t think so. In fact there is actual theory about all this. - https://en.m.wikipedia.org/wiki/Aumann%27s_agreement_theorem - https://www.scottaaronson.com/papers/agree-econ.pdf and in particular, - https://mason.gmu.edu/~rhanson/prior.pdf If your goal is just to manipulate someone else into doing what you want, regardless of what the facts say nor what their beliefs say about the facts or about your beliefs, then sure, that is pure manipulation and not related to strategies for effective disagreement resolution. It’s also not relevant or useful to bring up the fact that humans are not rational Bayesian actors, again because we’re talking about how best to achieve unified shared understanding of the true facts and to ensure we only derive beliefs from that (anything else can only be manipulation, not decision resolution, by definition). We may fall short of the best solution due to our flaws and limitations, but that doesn’t render the best solution any less the best, not make some other seemingly more attainable solution better or more worthwhile.

Lets consider a game. A coin will be flipped, and we can bet as much money as we want that either heads or tails will win. You will win $100 if the price in this market stays >75% chance of heads for 7 days continuously. So you keep buying up shares of heads, moving the price from 50 -> 60 -> 70 -> 80. by the end you are betting $4 for the chance to win $1. I know that the result is 50-50, so if I bet $1 against you, and have the chance to win $4, then that means my expected profit of taking this bet is %200. Which makes this one of the best investments available on earth. Which means many people will want to participate. Every bet you make at the price 80-20 costs you $1, but is only worth $0.40. you are losing 60% of however much money you bet. So if you bet $200, then your expected loss would be $120. which is even bigger than the $100 you could potentially win by manipulating the market. It doesn't matter if I bribe a manipulator with $100, or with $1 billion. The same logic holds. Having a vested interest in the outcome of a decision does not give you any ability to manipulate us into making that decision. http://mason.gmu.edu/~rhanson/biashelp.pdf

Living in VR, and the implications thereof, have been written about in SF for decades. The earliest work is "Simulacron 3", from 1964. It's been done to death in anime. "Sword Art Online" is probably the best known stuck-in-VR anime, but "Log Horizon" deals with the philosophical aspects in more depth. Hanson is not breaking new ground; he's recycling SF as economics. Read Hanson's list of "wild ideas".[1] "By 2100, the vast majority of "people" will be immortal computers running brain simulations." (And the rest will be keeping the server farms going?) "If we keep writing down common sense datums until 2100, we can make computers as smart as people." (After 30 years of Cyc trying that, that's probably a no.) "If we allowed complete freedom of contract, law could be privatized, to our common benefit." (He's at George Mason University, which is a right-wing think tank, and has to say stuff like that to get tenure.) [1] http://mason.gmu.edu/~rhanson/wildideas.html

You seem unfamiliar with the long and extremely formal research and experimental evidence supporting the use of prediction markets. It might be interesting to read a more detailed popular account [0] and then dive from there into some of the more specific discussions about what happened in the DARPA experiments. > Prediction markets failed spectacularly to predict the outcome of the recent UK referendum despite an abundance of polling data and the only major uncertainty being statistical (not many people were changing their minds at the last moment, I guess). Well, you are right that markets are not perfect and are susceptible to aggregated biases of the participants, for example just as how mispricing persists in the stock market. I don't see how this offers a reason to feel that markets aren't the best that can be done, however. If you can propose a better mechanism by which to get info ahead of time, I (and millions of people) would be very interested. > Most obviously because prediction markets tend to be quite shallow, and the types of people who use them bring their own mental baggage to the table. Why would a project leader be willing to submit to such a flaky and moreover gameable scheme? This is bizarre and unsubstantiated. What are you talking about "mental baggage" -- it sounds like you have a personal grudge against market thinking and prefer to attack it, but without basis. > Why would a project leader be willing to submit to such a flaky and moreover…

Making insider/true expert information public more quickly in the form of influencing prices in a toy market is THE ENTIRE POINT of prediction markets. Read the original papers on them. http://li.mit.edu/Stuff/CNSE/Paper/Hanson90.pdf https://www.jstor.org/stable/3216893 https://mason.gmu.edu/~rhanson/insiderbet.pdf

He wrote a whole paper on this. https://mason.gmu.edu/~rhanson/insiderbet.pdf

Hanson's idea (https://mason.gmu.edu/~rhanson/gamble.html) of a betting market for science could be an interesting model for journalism. Probably easier said than done.

> Congress ... worried "The media storm hit on July 28, 2003, when two senators (falsely) complained that we were planning to let people bet on individual terrorist attacks. The next morning the secretary of defense announced that FutureMAP was cancelled. In the intervening day, no one from Congress asked us if the accusations were correct, or if the more offending aspects could be cut from the project. DARPA said nothing. The next day, John Poindexter resigned, and two months later all IAO research was cancelled." https://mason.gmu.edu/~rhanson/policyanalysismarket.html Another fun story of Congress and prediction markets: https://nymag.com/movies/theindustry/67275/

Perhaps you are familiar with (or would support) the idea behind futarchy, which is sometimes expressed as "Vote on Values, Bet on Beliefs": http://mason.gmu.edu/~rhanson/futarchy.html

I'm surprised that no one has mentioned prediction market(PM) as the alternative. This is old paper but IMO it is still persuasive. https://mason.gmu.edu/~rhanson/gamble.html

For specifically the doctor version of the principle-agent problem, Robin Hanson published an incentive-compatible solution over 25 years ago: http://mason.gmu.edu/~rhanson/buyhealth.html

If two people have the same priors, and their posteriors for an event A are common knowledge, then these posteriors are equal. - Robert Aumann http://mason.gmu.edu/~rhanson/deceive.pdf

From Philip Tetlock's Superforecasting [0] to Robin Hanson's Futarchy [1], there's a strong argument that predictions are entirely valueless without "skin in the game", be it in reputation score, or dollars. [0] https://en.wikipedia.org/wiki/Superforecasting:_The_Art_and_Science_of… [1] http://mason.gmu.edu/~rhanson/futarchy.html

For an interesting/insane/revolutionary application of this technology, check out Robin Hanson's futarchy[1], a theoretical governance structure which would use prediction markets to make decisions. [1] http://mason.gmu.edu/~rhanson/futarchy.html

i dont endorse this, but there is also ”futarchy” http://mason.gmu.edu/~rhanson/futarchy.html it would probably not work because of Goodhart's law, and be generally rejected for being too weird. something for vulkans to try out, maybe.

Note that if your gambling laws are too restrictive/expansive you lose the social benefit of prediction markets, which enable society to have a well calibrated understanding of the likelihood of various events. http://mason.gmu.edu/~rhanson/ideafutures.html https://en.wikipedia.org/wiki/Prediction_market

Except the rich and poor spend pretty similarly in the US and elsewhere. The income elasticity > 1 occurs at a national level.... http://mason.gmu.edu/~rhanson/EC496/SOURCES/LUXURY.PDF And the better data on price suggests US actually isn't unusually expensive for a high income country and so on and so forth. Much data points to higher volumes of health goods and services as we chase diminishing returns as a society.