0:00 Paul, while you're getting mic'd up, maybe Phil would have a question or two just to 0:18 get started on the boiling the oceans question. 0:22 And I think it's kind of a special opportunity that we shouldn't pass up. 0:28 I don't know, I can introduce basically, because Phil said this to me over the phone, 0:33 that the energy efficiency of Bitcoin is often in the news. 0:38 And go ahead, you can add to that. 0:42 Yeah. 0:43 I need to go home soon, so I can't stay for your whole thing. 0:45 But if you front load it with the anti-ocean boiling ideas, that would be nice. 0:51 Well, I wrote an essay called, Nothing is cheaper than proof of work. 0:57 And so the long story short is, I think you should actually, to be an apples to apples 1:03 comparison, you should really look at all of the energy wasted in ATMs and point of 1:08 sale machines. 1:09 And actually, people have done this, and it's several orders of magnitude lower than is 1:15 currently used. 1:15 The other thing that is often not explained well in Bitcoin is that it's a fixed cost 1:20 for a two week period. 1:22 So it doesn't matter how many transactions you end up fitting in there. 1:25 So even though a tremendous amount of energy is used, as the technology improves and more 1:31 and more transactions can be fit, and theoretically, an infinite number of transactions, not infinite, 1:36 but a very high number of transactions can be fit into each block. 1:40 And there are many blocks in each two week period. 1:44 The energy used per transaction can actually fall even more, many orders of magnitude. 1:50 But yeah, the issue with these other systems is that so far, no one has designed a system 1:56 that has yet to regress to consuming resources in some form or another. 2:02 But I wrote kind of a giant essay about that, which I'd be happy to email. 2:05 I think you may find this talk, the first 10 minutes of this talk, more interesting 2:10 though than the essay that you could read. 2:12 But it's, nothing is cheaper than proof of work. 2:14 And if you just Google that phrase, you'll find it because it's right at the top. 2:22 Or at least it was the last time I checked. 2:24 So, I mean, I wish we had time to talk about so many things. 2:27 But should we just get right into this thing here? 2:30 Because, oh, yeah, where's my note? 2:31 Let's give Fred an applause here. 2:33 Okay. 2:39 So I keep, I constantly refine this talk and I've been messing with it for the first, yes. 2:44 Sure, no problem. 2:45 The first few, you know, we just met each other. 2:48 Okay. 2:49 Okay. 2:50 Okay, thanks. 2:51 So yeah, I made this presentation in January and I've changed it around so many times. 2:59 So you have to just bear with me as I keep refining it. 3:03 But basically, okay, here we go. 3:08 So this, I wrote a project about blockchain prediction markets and I wrote a paper behind 3:13 it and the code, but I don't have anywhere near enough time to talk about the whole thing. 3:19 So I'm just going to talk about my favorite thing that motivated me to create the project 3:23 in the first place. 3:24 So here we go. 3:25 So then I, this is part of the presentation I changed, I have to read it. 3:28 So in modern times, a vast portion of our wealth and the welfare of billions of lives 3:34 depend crucially on the outcome of institutions that we call elections. 3:39 So okay, yes. 3:47 And bad public policy can ruin just about everything. 3:50 So unnecessary wars, poverty, you know, people, miserable social lives as people obsess over 3:58 conspiracy theories, right? 4:01 Slower economic growth, meaning that lives in the future will be much worse than they 4:06 otherwise would. 4:07 And then since most people who will live will live in the future, assuming that the species 4:11 doesn't go extinct, which is generous maybe, but most people will live in the future. 4:18 And so we should care a little bit about them. 4:21 Obviously though, we're talking, today we're talking percentage points of global GDP growth 4:26 and millions of people who are alive today. 4:29 So that's just part that I haven't tried. 4:31 Okay, yes. 4:32 So during the Enlightenment, people came up with this basic kind of structure here. 4:38 And you know, political thinkers used what they had learned from the Roman Empire over 4:43 years of tinkering and from Athenian democracy, and they came up with this thing here. 4:48 And a lot of it is pretty cool and worth talking about. 4:52 But the most important thing is that we have these secret ballots. 4:57 And when their errors inevitably show up, we fire someone using the secret ballot and 5:03 we say, I didn't like this, so it's time for you to get lost. 5:08 And so a lot of things, basically all this stuff hinges on this thing here. 5:16 Now when it was designed, or what I mean by that is like in the 1800s when the US Constitution 5:23 was written, things were a little different and it sort of worked, I think, a little bit 5:27 better than it works today. 5:28 But now it does require, we'll get to that in a second, but it does require the voter 5:35 to do a lot of counterfactual thinking. 5:37 So like, would this have been better under this other person versus, you know, is what 5:41 we have just the best that we can do? 5:43 And maybe a new person will make it worse. 5:45 And they have to do a lot of thinking, basically. 5:48 You also have to do some game theoretic reasoning, thanks to something called electability that 5:53 I'm going to explain in tremendous detail that ruins elections to a tremendous degree. 6:03 So the thing that I was mentioning before is that while it was sort of working, I think, 6:09 much better in the 1800s, now it doesn't work as well, I think. 6:13 And so some of the impacts here are that as society has progressed, there are more 6:20 people living here, and that just means you have a smaller impact per vote. 6:24 So if you have three people voting, it's virtually guaranteed that, you know, your vote will 6:29 really count. 6:32 But if you make a simple model, which I have done, and you just assume that you don't know 6:37 other people are voting with a coin flip on whether or not they vote up or down or just 6:41 abstain, then at around eight other voters, your probability of affecting the outcome 6:47 at all drops below 50%. 6:49 And at 41 other voters, it drops basically to 0%. 6:52 So in the United States, like 115 million people vote, so it's kind of a lost cause. 6:58 But the other thing is this point about media ecology, which I'd love to make in more detail, 7:03 but when I do, it just drags the presentation on. 7:05 But everyone should read this book, Neil Postman's Amusing Ourselves to Death. 7:09 It's a really wonderful book. 7:11 And in the past, 95% of Americans, this is a very American-centered part of the talk, 7:17 I'm sorry about that, but when Thomas Jefferson aligned all this stuff, almost everyone was 7:23 a literate farmer, and so they had a lot of free time to read, and you had an over 95% 7:29 of the population of the United States at that time was people who were literate farmers. 7:35 Almost all the media that was consumed was typography, it wasn't even handwriting, it 7:39 was the printed word. 7:41 So it had these qualities of being very abstract and even anonymous, because it would look 7:48 the same no matter who wrote it, and you had Thomas Paine and these other famously anonymous 7:54 pamphlets that were circulated. 7:56 So again, I could talk about this point for a very, very long time, but the short version 8:00 is that today, we're bombarded with, another interesting point, two more, is that people 8:07 were very famous, people like Charles Dickens who wrote these giant, giant long-winded books, 8:12 but they were as famous as the Beatles or movie stars or something, and people really 8:16 liked this stuff, this long-form content. 8:20 And one of the Lincoln-Douglas debates in the middle of the 1800s between President 8:27 Abraham, well, then candidate Abraham Lincoln and the guy he was running against, one of 8:32 those debates, they closed the town for the whole day. 8:36 The first person spoke for three uninterrupted hours, just speaking, no visual aids. 8:41 Then they took intermission, everyone went home and had dinner with their families and 8:46 came back for the rebuttal, which was four hours of uninterrupted speaking. 8:50 And that's like, no, today, this is unthinkable, because we're bombarded constantly with information, 8:56 and some of that information is just entertaining, so there's not enough. 8:59 In the past, there was kind of this free bandwidth for people to just think about what they should 9:04 do or who they should elect or how to solve their collective problems, but today, there's 9:09 just this attention economy, and you can't even get people to fill out surveys to try 9:15 and improve their hotel experience or whatever. 9:18 And then my third point here is that society is a lot more complicated now. 9:24 In the past, I think society was pretty complicated, but it was like, how complicated can it really 9:31 be in an era where, so now, stuff can happen very, very quickly, and you have whole teams 9:36 of specialists, people go to school, they train their entire lives to be what, like 9:41 a jet fighter, and they know everything about how very quickly you could take off and bomb 9:46 some facility 800 miles away or something, and there's no way, something like Brexit 9:51 or say, like, this is just like outside of the scope of, you know, should we build more 9:56 walls or something, so it's like, you know, a more simple thing, okay. 10:01 And again, I've done this presentation a lot, and there's so many things I want to talk 10:05 a lot about, but I'll just touch a little bit briefly on this one here. 10:10 You have to know a lot of things if you want to vote well. 10:13 One of them is how what your, not only what your existing option is, but what the, who 10:18 the challenger is, and that's, that seems like a low bar, but we'll see that at the 10:21 bottom, or over here, we're not even at that stage one, because 71% of Americans cannot 10:27 even name the one congressional representative that is their own congressional representative, 10:32 but you also need to know the challenger and both of their plans, and also whether or not 10:37 they're lying about what their plans really are, and even if they're earnest, you need 10:41 to then figure out what would happen if they actually introduced those plans, and if it 10:45 would be maybe a giant disaster. 10:47 So you need to know quite a bit, and usually only a few specialists know that for some 10:52 crucial decisions. 10:54 And as I just mentioned, basically no one even knows who they, who it is that they elected 10:59 in the United States, let alone the challenger or any of the policies, like you can go down 11:05 the line. 11:06 Sometimes I, for fun, I ask people to name their congressperson, or I name the, who they 11:10 ran against. 11:11 No one can remember anything. 11:12 I bet, sometimes I do already, people can't even remember like who Hillary Clinton's running 11:16 mate was and things. 11:17 That was like just a very short time ago. 11:21 And I have a funny story about these lobbyists who are on a plane, but I think I probably 11:25 won't tell it unless we have time. 11:26 I was looking at that on the slider. 11:27 Do you want it? 11:28 I'll tell it to you. 11:29 What is that? 11:30 Okay, so I happen to know someone, I don't want to out this person, but this person was 11:38 a congresswoman, and she gave this story, which is very funny, and she was on, she is 11:45 from, she is a member of the House of Representatives from State A, and she was in State B flying 11:53 to Washington, D.C. 11:55 And lo and behold, next to her on the plane are a bunch of lobbyists, and they were flying 12:01 also from State B to Washington, D.C., so that they could lobby someone. 12:07 And the person that they were lobbying was from a different state, State C, and the lobbyists, 12:15 they had literally studied this person, I think it's not even a joke, they had literally 12:18 studied them down to their shoe sizes, that's a phrase in English, but I think they literally 12:23 were like buying this person like some shoes or something crazy like that, or they had 12:26 like done some of this stuff. 12:28 So they had all this pages and pages on this one person, the target of their lobbying, 12:36 and then she asked them if they knew who their own representative was in State B, and they 12:42 didn't know. 12:43 So they're professional lobbyists, it's their job to influence the congresspeople, but they 12:48 only know the one that they're paid to know, even if they work in the space, they can't 12:53 be bothered to look it up. 12:55 And this is a shock, if you pair it with something else, I just think this is unbelievable, and 13:00 there's no possible way that this is what people had in mind in ancient Athens. 13:04 I just think that like there's no possible way that these are the re-election rates, 13:09 and this is zero, and this is 100% for the United States Senate and the House of Representatives, 13:15 and almost always the same people get re-elected, even though no one really knows who they are, 13:20 and the congressional approval rate is always very low, and for the last 20 years or so, 13:26 I think it's even been in the single digits, the September 11th, 2001 era, notwithstanding, 13:34 that it's just been like below 40% forever, and then just falling, and then below 10%. 13:39 So definitely this is this rational ignorance component here that people just, they can't 13:46 be bothered to look into this, like who they should vote for, it's just too much work. 13:51 And now I have this thing about electability, so there's this joke, and I actually, I researched 13:56 this on a plane, and I'm wondering if anyone knows what I'm talking about here, because 14:00 I looked this up, and there's a very famous episode of the American television comedy 14:05 South Park, and I looked up, and I was like, does anyone in Amsterdam watch this, and apparently 14:09 it is very popular in Amsterdam, and this is from a bunch of years ago, and someone 14:15 said they know what this is, and so this is a joke, and you can see I censored some of 14:19 the letters here, but do you want to like just shout out, or explain what's going on 14:23 in this, I guess you don't have the microphone, but yeah, exactly. 14:27 So this joke is that, it's done very well, as only South Park can do with these funny 14:32 cartoons, so that it's just cleverly hidden enough, the parallels to the real world, but 14:38 basically this joke kind of spirals out of control, and everyone at this fourth grade 14:43 class is forced to vote between two candidates for mascot, and one of them is a giant douche, 14:49 and the other one is a turd sandwich, and then the child goes home to complain about 14:53 how inane this is, and his parents tell him that in every election, it's always a choice 14:59 between a giant douche and a turd sandwich, so that's a very funny thing, so I'll be back 15:06 with more about rational ignorance, and I'm going to talk more about electability right 15:12 after this, but both of the solutions are really, can be solved using the same, or I 15:17 think they, my guess is that they, my theory is that they can be solved with these things 15:22 called conditional prediction markets, so I hope that you have an open mind to that. 15:28 Now I'm going to talk about this electability thing for a second, because it's amazing how 15:32 much this one concept ruins not only elections, but lots of other things, so why don't we 15:38 just, if we don't like Congress or something, in the United States, again I apologize that 15:44 I didn't want to look up, I did look up a bunch of things about the government here 15:50 in Amsterdam, but I just thought it would be too much work and too contrived, too much 15:54 of a put-up job to kind of pretend that I know anything about what's going on here politically, 15:59 but if you don't like the people in charge, and it's a very common thing to complain about, 16:03 I actually have other slides that I took out about like the mayor from the Simpsons, because 16:07 I wasn't sure if anyone here would get that, but it's like every time politicians are portrayed 16:13 in popular media, like everyone kind of doesn't like them, and so it's like, well, why not, 16:17 because we can just get rid of them at any time, and there is an answer to this question, 16:21 which is that why is it always between two unlikable candidates, and that is what I'm 16:28 about to explain, something called multi-factor competition, so competition is great, and 16:34 it works really, really well, but it doesn't work, you have to compete on one thing at 16:38 a time, so my example here is going to involve one person choosing where he eats for dinner 16:44 alone, but then he's going to choose where he eats with a group of people, and the group 16:51 is going to ruin everything, even though everyone involved is individually rational and all 16:56 that, so you want to spend up to $20 on dinner, you're choosing and dining alone, and so then 17:02 all you have to do is compare restaurant A, restaurant B, restaurant C, and what your 17:07 expected satisfaction is, and then you just decide, well, I think my satisfaction will 17:12 be highest with restaurant B, and then you pick restaurant B, and it's very easy for 17:16 you, you get the highest satisfaction possible when you have competition on one dimension, 17:21 always, but the secondary effect is that the restaurants are induced to compete on this 17:26 metric here of satisfaction per dollar, so there's a natural corrective force here, you 17:32 can veto people and find the place that you like the most, and the restaurant that's vetoed 17:38 too much goes out of business, and their capital is freed up for other things, which 17:43 is desirable. 17:44 Okay, so now, this is the part where everything is ruined and why we always have unlikable 17:49 candidates. In the United States, it also, there's a different thing, you guys have proportional 17:53 representation here, which is, I think, worse, and you should read, Karl Popper wrote an 17:58 essay about this in The Economist, that you should read, called The Open Society and Its 18:03 Enemies. So, it's even worse, but the solution I'm going to describe actually works for both 18:09 situations, but you guys have different problems, you have a dictatorship of the third largest 18:14 party or weird party coalitions and other things that I'd also be happy to talk about, 18:21 but it's a much stronger... 18:22 Yeah. 18:23 Yeah. 18:24 Well, okay, we'll see, but it doesn't matter, the solution I'm going to pitch will work 18:32 for both, just as a kind of happy coincidence, maybe. But anyway, here's what's going on 18:37 here, is that a lot of people are choosing to go somewhere and they want to have the 18:42 best meal possible, but they also want to show up at the same place that everyone else 18:48 is showing up. And now, your decision depends not only on what you prefer, this is, excuse 18:54 me, sorry, this is the little graphic from the previous slide, depends not only on what 19:00 you prefer, but it also depends on where other people might go, and that is in itself 19:08 a function of what they might prefer. Now, I'm going to be very nice here and assume 19:12 that they have the exact same preferences as you, although Kenneth Arrow won a Nobel 19:16 Prize for describing that, if these are different at all, we're all doomed and we'll never be 19:21 able to figure out which restaurant to go to, using math. But I'm going to say, even 19:26 though they're the same, because your decision depends on where you think they will go, but 19:34 that's a function of what they, what you think they prefer, but also where you think they 19:38 might go. And they, if you think, and so this actually is an infinite, like, recursing thing 19:44 here, it just recurses forever, so I could have just put a bunch of things, but instead 19:49 I just say, well, that's a function of everyone's collective best guess on where most people 19:54 currently plan on going, which I'm going to call the status quo, even though that's 19:58 a very kind of free use of that term. But then also, since time and attention and communication 20:06 and just information processing in general is not free, especially in the human brain, 20:11 it also depends on how open to communication and negotiation everyone is. So, what I'm 20:17 saying is, everyone hates restaurant C, but they think everyone else is going there, so 20:21 this is kind of like a family reunion dinner or something where everyone just, they don't 20:26 want to, they don't know each other kind of well enough to say that they hate restaurant 20:31 C and it might be misconstrued as impolitely saying that you don't like the family gathering 20:37 or something. So, this crazy family just ends up going to restaurant C year after year after 20:42 year until someone finally reveals that they actually, they all hate restaurant, they all 20:47 hate restaurant C. So, you have four criteria here, but you have to make one selection and 20:54 you end up choosing based on where you think other people might go because that's more 20:58 important to you than some other things, which basically the analog for this is that, you 21:03 know, no one wants anarchy, so we put up with this dumb process that gives us unlikable 21:08 candidates, but. So, I have a little bit more of a, yes. So, there's, excuse me, yes. 21:23 How far away the restaurant is, is that what you're saying? Yeah, yeah. Yes, well that 21:29 is, that would help in this case because what I'm saying is that there's some information 21:33 that you'd have to process, but if there's something everyone should be able to, if everyone's 21:38 in a group and they're walking around and they have yet to determine the restaurant, 21:42 they would rely on commonly available signals like what everyone can see right now and, 21:49 you know, the fact that everyone prefers to walk. Everyone prefers less walking to more 21:53 walking. So, yeah, that would help, but yes. 21:56 Okay. So, there's a self-fulfilling prophecy on this last one here, which is that there 22:10 are some people will become cynical, kind of Tyrian Lannister types, and they will decide 22:16 that negotiating to pick a better restaurant is a lost cause, and so there's no point to 22:19 voting or no point to participating, and then you have all the smartest people dropping 22:23 out at which point it becomes even more horrible. So, and this becomes worse when there's lots 22:30 of people and many alternatives. So, in the United States, there's 250 million adults, 22:34 the near infinite number of policies. So, instead, you, you have, you have this issue 22:41 where since you prefer to meet at the same place as everyone else, this is the so-called 22:45 wasted votes problem where you, if you vote for some, the third party candidate, you just 22:49 throw your vote away, and as a result, everyone has to think strategically. That was that 22:55 second thing about electability, the red part, is that in, when you're doing the primaries 23:01 in the United States and in other, this, a version of this tick crops up in every form 23:08 of democracy, but when you are whittling down the choices that will be on the ballot in 23:14 like the pre-ballot phase, you have to know that your... 23:19 you, you may, you may end up hurting your own side by voting for it, because you need to have, you need to pool all of your votes. 23:28 It depends a little bit on the voting scheme that's used, but you need to pool all of your votes so that you have enough to actually win the election. 23:35 And this has happened numerous times in election history where someone has split the vote and caused the side to lose. 23:44 I think I explained this already, that you want to stay in sync with others, so that's kind of what's driving all of this here, 23:52 and then you can compare what it would be like if you wanted to start up a new barbershop versus if you wanted to start up a new Facebook, 24:00 and I think I put some blue text up here, yeah, okay. 24:03 So, a lot of people don't like Facebook, and they find that it drives them, makes them miserable and forces them, compels them to pretend that their life is better than it is 24:11 and post weird pictures, and they kind of don't understand what's happening to themselves, and they don't like the fact that some weird corporation has all their... 24:19 You know, a lot of people really don't like Facebook, if you ask them, but they put up with it anyway, 24:25 because the alternative is not having any Facebook at all and having basically social isolation in this one narrow sense, 24:35 but the alternative is this problem that I've been describing, which is endless and ultimately futile, 24:40 because you will lose negotiation with unmotivated friends and family to switch to one particular alternative among many, 24:48 so I don't say we should switch to Freebook or whatever, but you've got to get all of your friends and family to switch over, 24:56 and they know, when you're talking to them about switching over, they know that they need to convince their own friends, 25:03 who in turn need to convince their own friends and so on and so forth, 25:07 since everyone knows that just a little bit of intractability is enough to stall this whole process out, 25:14 there's the self-fulfilling prophecy that I mentioned before, and as I say at the bottom part of this text, 25:19 that it's the same way that we put up with governments, even though it's a very commonly believed, 25:24 and I think pretty accurately believed, that they are less than optimally competent, 25:30 which is because the alternatives are no government at all, or some weird, giant, violent revolution that may not work, 25:37 but I think we have a question. 25:38 Just quickly on the Facebook thing, I don't use Facebook anymore. 25:42 No, I haven't used it in five years. 25:43 Exactly. 25:44 But we're like the weird guys. 25:46 And in fact, I was literally planning on bringing it, I'm literally planning to go back, 25:51 because now that everyone knows how bad it is, I'm a little bit more okay with bringing it back to them. 25:55 So here's the thing, is that you may be tempted to use it because you're a social friend and family, 26:01 but if you don't use it, they have less incentive to use it. 26:04 Correct, yes. 26:05 No, but that's my point, is that it is... 26:07 It becomes a self-fulfilling prophecy if everyone stops using it. 26:10 Right, if everyone stopped using it, it would make it easier, 26:12 but that's my point, is that there is a kind of gravity to this, 26:15 where if the Earth were somewhere else, there would be more gravity keeping it there. 26:19 But it's the same with governments. 26:21 Yeah. 26:22 No, it is the same, yes. 26:23 If we get to a new peak, or a new something, a new local optimum. 26:29 Yes, it is the same, I think, yes. 26:31 The problem is getting there, that's what I'm trying to explain. 26:35 Okay. 26:36 So I hinted before, Ken Arrow won the Nobel Prize for this. 26:40 If you have some rules, then basically, mathematically, 26:43 it's impossible for preferences to be aggregated, 26:47 and some of them are just so simple that you almost feel like you can't even 26:51 state them like having more than one person involved, 26:55 so that there's at least two people, 26:56 and some deterministic way of fusing those preferences, 27:00 then you can only have one of these two things, mathematically, 27:04 which is that you can't hurt an option when everyone ranks it higher. 27:07 So when people are persuaded of something, 27:10 you can't have the group be persuaded in the same direction, 27:14 which is, again, these seem like they should all be no-brainers, 27:17 but mathematically, you have to omit one, 27:20 and the second one is irrelevant alternatives are really irrelevant. 27:24 So if someone, you had a preference for A or B, 27:29 I shouldn't say that, because that's no good. 27:31 I should say something like, let's say, Churchill versus, I don't know, FDR. 27:36 So let's say you're electing Churchill, and you prefer Churchill to FDR, 27:39 and then you have Stalin and Hitler. 27:41 If you prefer Churchill to FDR, and then society runs this algorithm, 27:46 and it says, okay, Churchill wins, 27:48 and then if you reran it again with everyone swapping 27:51 how they voted for Stalin versus Hitler in place three and four, 27:55 it shouldn't then give you the answer of FDR instead of Churchill, 28:01 because the ones at the top didn't change. 28:04 But unfortunately, you have to break one of these, 28:07 because for math reasons. 28:09 So it's an unsolvable problem. 28:12 That's why in the United States, 28:16 we have this problem with splitting the vote, 28:18 and where you have this thing where votes cast for a lost cause 28:22 do not contribute at all. 28:24 But you guys have proportional representation, 28:26 which is a slightly different conversation, 28:28 but there is still a version of this theorem 28:31 that applies to proportional representation, 28:33 because it applies to all preference aggregation. 28:37 So that is part of why we always have these two people, 28:42 because you need to vote for someone that you think other people will vote for. 28:45 Yes? 28:46 There are several voting algorithms, like instant runoff. 28:50 Yes. 28:51 That go along with that problem. 28:54 No, they go some way, but they do not actually go. 28:57 Yeah, the question was about instant runoff and these other things. 29:00 You rank a bunch of people. 29:02 But there are still incentives to put the electable people 29:07 to misrepresent your own vote. 29:09 So even though it does help you with the votes ranked 29:14 like two, three, four, five, six, 29:16 it does not actually help with the person that you put number one, 29:19 because if the other people break with the scheme, 29:22 or the intended scheme, and lie and put all theirs number one, 29:25 then the other people, the other team, 29:27 will still win by breaking the scheme. 29:32 So actually it is unsolvable in this direction, I think. 29:38 Okay. 29:39 Do you have to go to decidability before you can have a fair election? 29:43 Yeah. 29:44 The issue is that we want to make it one-dimensional, 29:50 one dimension of competition, 29:52 so that it is more like the restaurant case before. 29:56 So we are going to need a way to get all this information out 30:00 because of rational ignorance, 30:02 and then we are going to need to get rid of this electability problem 30:07 that someone can split the vote 30:09 and screw with the preference aggregation process of the ballot system itself, 30:15 and then we need a way to stop this from being captured 30:19 by anyone who is not a voter. 30:23 So we want only the voters to be able to influence this process. 30:27 And that third thing is going to be the blockchain and Bitcoin 30:31 and all that other stuff. 30:33 So what this brings me to what the solution is, 30:36 and it is these conditional prediction markets. 30:39 This is Hal Finney. 30:40 He wrote this on Robin Hanson's blog, overcomingbias.com. 30:45 And this is Ralph Merkle, 30:48 and he said there are only a few people alive today worth listening to. 30:51 Robin Hanson is one of them. 30:52 So this is Robin Hanson's blog, 30:53 and this is Hal Finney posting in July 29, 2008 on this topic. 30:59 So that's just some social proof and appeal to authority 31:04 to just kind of maybe liven the mood. 31:06 It's kind of a long talk. 31:08 You have to ignore that. 31:09 Okay, so I'm going to explain what a normal prediction market is, 31:14 and then I'm going to explain what these conditional prediction markets are. 31:17 So a normal prediction market is this thing. 31:20 It's often called an event derivative. 31:22 So it pays some amount if the event happens, 31:25 and it pays nothing otherwise. 31:27 And this particular example, which I got from Intrade before I was closed down, 31:32 is about whether or not 2012 will be the warmest year on record. 31:38 And when this was created, it was January 2011. 31:42 So this was a long time ago. 31:44 This slide is from the past. 31:46 And the market was created in January 11, 31:49 and then it traded at these prices until the end of 2012, of course, 31:54 when it settled in January 13, which is the end there. 31:59 It was worth $100 if 2012 was the warmest year on record. 32:04 So you could bet on this before 2012 even started, 32:07 which is this first half here on the horizontal axis. 32:10 And then in 2012, it became slowly clear that it was not in the cards, 32:15 and that even though 2014 was the warmest year on record at the time, 32:19 2012 was not going to be. 32:22 And so it ended up being worth zero, 32:24 because it's worth zero if it doesn't happen, 32:26 and it's worth $100 if it does happen. 32:28 Now the issue here is that you can reference the current price 32:33 as a kind of probability, 32:35 a society's aggregated knowledge about the likelihood of the event. 32:40 So it traded from this initial price, which is about $40, 32:45 for something that's worth $100 if the thing happens. 32:48 And then the price went up to $50, and then it went all the way down. 32:54 To $0 when it ultimately did not happen. 33:02 A lot of people take issue with this. 33:04 Some people have some hang-ups when it comes to markets. 33:09 Some free market people say that free markets not only make people rich, 33:13 but they're also really good for society, 33:16 and people have a hang-up about that. 33:18 And now I'm kind of also saying that they're also smart, 33:20 which is almost too much for some people. 33:23 But the issue here is that it's a kind of proof by contradiction, 33:28 which is that if this price were not really truly representative 33:33 of the objective knowledge that was existing in society, 33:36 then someone or some fund or something, 33:40 some group of people or some kind of co-op or something, 33:43 there's some feedback process in place to correct that error. 33:48 If this market were on something that everyone thought 33:51 was definitely going to happen in 2012, 33:54 then the prices would not have started at $40, 33:56 and then they would not have declined to $0. 33:59 They would have started at $70 or $80, 34:02 and they would have gone up to $100. 34:04 So nothing is perfect, and nothing can see the future, 34:07 which is another hang-up I think people have on prediction markets. 34:12 They're like, you know, what kind of magic is this 34:16 that you're telling me you know everything 34:18 about society's knowledge or something? 34:20 So if you did a coin flip, 34:23 the prices would have to be 50-50 until the coin landed 34:27 because these only allow you to aggregate knowledge 34:30 that actually exists in society. 34:33 And so they're not like some magical perfect thing. 34:36 Another last hang-up before I go on to the next slide 34:39 is that there's a lot of ignorance of probability. 34:42 So something is trading at $0.25 on the dollar. 34:47 It should happen exactly one out of every four times, 34:50 but I have a million friends. 34:53 Something is trading at $0.25 on the dollar 34:56 in a prediction market world, 34:58 and I say, well, it's probably not going to happen. 35:01 It's only got a 25% chance of happening. 35:03 And then most of the time, three out of four times, 35:06 it doesn't happen, but then when the fourth time happens, 35:08 you get a bunch of e-mails from people telling you 35:10 that the market was wrong or something, 35:12 when in reality it was 100% perfectly calibrated. 35:16 But this is kind of the pitch, 35:18 that there's a tight connection here 35:22 between the price and the likelihood of the event, 35:26 and if you can soup this up, 35:28 if you can soup this up, 35:30 then by adding some more anonymity 35:32 and making sure the costs are very low 35:34 and making sure there's not a lot of friction, 35:36 you can try to get a greater fine-tuning of this feedback 35:42 so that the connection is more and more tight. 35:44 And unlike the voting I mentioned before, 35:47 the scaling is very good 35:50 because the more people who know about a market, 35:52 the more people will kind of glance at it 35:54 and see if it looks totally wrong to them, 35:56 and the more liquidity will be in the market, 35:58 and so the transaction frictions will be even lower. 36:03 And so, I mean, I already explained this. It's okay. 36:05 Now, the interesting thing about this is that 36:07 not only is this information very accurate, 36:09 but it's common, 36:11 so not only everyone gets the same information, 36:14 but everyone knows that everyone else got it, 36:16 so it's very much unlike the example 36:18 where everyone hated the restaurant 36:20 but didn't know that everyone hated the restaurant. 36:23 With this, everyone knows the exact same information, 36:26 and so you have this, it's what's called 36:28 common knowledge in the field of game theory. 36:31 It's like private knowledge is something that only you know, 36:34 mutual knowledge is like a very dramatic kind of knowledge 36:37 that two people know something, 36:39 but they don't know that the other knows it, 36:41 so like if you oversaw someone murder someone, 36:44 and they know they murdered the person, and you know, 36:47 but you saw from far away, 36:49 and then you see them later getting coffee or something, 36:51 and it's a very dramatic kind of, 36:53 because you're just both, you're pretending, 36:55 and he doesn't know that you saw, and all this other stuff. 36:57 But common knowledge is when everyone knows. 36:59 It's like this presentation right here 37:01 where you are all watching, and you all know 37:03 that everyone else can see it. 37:05 So these kind of do all the research, 37:08 and they do all the persuading, 37:10 which is my, you know, 37:12 it's kind of a tough sell to say this one little thing 37:15 just gets you up on these little estimates for things. 37:18 Something very hotly debated in the United States 37:21 is global warming, and a lot of people don't, 37:24 you know, they're not ready to 37:27 leave whatever trench they're in, 37:29 of which there are many, but 37:31 this is kind of the pitch for this part of it. 37:34 But as I said, there's more to it, 37:37 the conditional aspect that I'll get to later. 37:40 But yeah, I think, okay, 37:42 the other thing, I'll mention this, 37:44 this forces a clear definition, 37:46 so actually the example that I used over here is, 37:49 there was this, you could click into like a little thing 37:51 and see what the fine print was, and it said, 37:53 okay, we're going to look at this NASA satellite, 37:55 and it's going to do global surface temperature anomaly, 37:58 and NASA is going to publish this on this URL or whatever. 38:02 So that's a lot better, 38:04 because a lot of people use disagreements 38:06 just for social reasons, just to posture, 38:08 and just to kind of like have a lot of fun, 38:10 and they don't, they're not, 38:12 caring about the issue a lot is not really the point. 38:15 It's just like, you know, being loyal to your, 38:18 you know, tribe or party or whatever, 38:21 and so definitely in the United States, 38:23 global warming is just kind of a flag 38:25 for people to join their respective camps, 38:28 and no one has really even given any thought 38:31 to like defining exactly what would it mean, 38:33 which is in this case, specific satellite, 38:35 specific website, specific everything, 38:37 specific metric, global surface temperature anomaly, 38:40 and a very specific thing here, 38:43 2012 being the warmest year on record, 38:45 and so you can argue about 38:47 whether or not that represents global warming, 38:49 which is a good conversation to have, 38:51 but then you sidestep a lot of this stuff 38:53 where people are just talking on and on and on 38:55 about abstractions, you know, 38:57 abstractions like global warming 38:59 or gun control or whatever, 39:01 stuff that's very vague, 39:03 which you don't want at all. 39:05 Okay, so yes, I say at all times 39:07 everyone agrees with the price, 39:09 which is again a very extreme claim, 39:11 but the proof is by contradiction 39:13 because you can make expected profits 39:15 if you don't agree with it. 39:17 Now there's a lot of, you know, risk aversion, 39:19 and if the transaction costs are low, 39:21 and if people really trust that this software works, 39:23 and blah, blah, blah, blah, blah. 39:25 But I think those problems are very fixable over time. 39:27 You can accumulate trust in the institution 39:29 and make it more user-friendly 39:31 and all these other things. 39:33 So this is the, you know, kind of a claim 39:35 that this price is society's aggregated knowledge, 39:37 and so that's kind of a neat thing here. 39:39 Okay, so now I have to talk about 39:41 how does this end up actually solving any problems 39:43 we're trying to solve, 39:45 and how does this end up 39:47 because so far we've only been able to do 39:49 like one little thing 39:51 with one little market that's yes or no, 39:53 and this is not, you know, 39:55 how Finney wrote the blog post 39:57 about conditional markets. 39:59 Conditional markets are where the magic really happens 40:01 because we don't just want to know, like, 40:03 will someone win some sporting game 40:05 or will someone win an election? 40:07 We really want to know, like, 40:09 we want relationships between things. 40:11 So, you know, we have to think about 40:13 how does this end up actually solving any problems 40:15 between things. 40:17 So this is probably too confusing 40:19 because it's an earlier version, 40:21 but I have a cool example here 40:23 that I will now attempt 40:25 because I constantly refine this talk 40:27 and I'm very unhappy with it, to be honest with you, 40:29 but I think it's getting better. 40:31 So now I'm trying to teach. 40:33 There's no probability. 40:35 So here's the thing is that 40:37 before we had a market 40:39 that had a state 40:41 and it was worth $100 40:43 if global warming were worth zero otherwise. 40:45 And that chart, 40:47 there was only one price that was plotted 40:49 because it would have been a total waste 40:51 of chart space to plot both of the lines 40:53 because they would have been 40:55 a perfect mirror of each other. 40:57 So that would have been a total waste of time. 40:59 You could have said the opposite one 41:01 would have been worth $100 41:03 if global warming was not the warmest year on record 41:05 and that one would have started at $60 41:07 and it would have gone up to $100. 41:09 But that would have been a total waste of ink. 41:11 But now it's not going to be a perfect mirror 41:13 because we're going to add lots more states 41:15 and it's going to be very complicated. 41:17 So it'll make for cooler graphs 41:19 that you'll see in a second. 41:21 But I first have to explain 41:23 what on earth is going on in these graphs. 41:25 So what I have first is an example 41:27 where you flip two coins 41:29 and you are betting on 41:31 the total outcome of what happened there. 41:33 And you say one coin could be heads 41:35 and one coin could be tails 41:37 and the second coin could be heads 41:39 and the third coin could be tails. 41:41 And as a result 41:43 they should all be trading 41:45 at 25 percentage points 41:47 because each state is equally likely. 41:49 The first coin could be heads 41:51 the second coin could be heads or tails 41:53 or the first coin could be tails 41:55 and the second could be heads or tails. 41:57 Now I want to imagine 41:59 something really weird 42:01 that would never happen in the real world 42:03 but will probably maybe help me explain this concept 42:05 which is that 42:07 what happens if you accidentally 42:09 when you were setting this market up or something 42:11 like you register all the coins 42:13 as different like coin number 3 42:15 coin toss number 4, coin toss number 5 42:17 and you accidentally have the market be set up 42:19 so that both of these axes 42:21 are the same coin. 42:23 And I would like 42:25 this is ask the audience time 42:27 because this part is confusing 42:29 and I get questions about it later 42:31 because I don't explain it very well. 42:33 But the question is 42:35 if it's the same coin 42:37 what should the prices end up being? 42:39 Very quickly, yes. 42:41 0.15, 0, 0, 0.15 42:43 Yes, exactly. 42:45 I didn't set up this thing yet 42:47 but I'll advance to the next slide. 42:49 Maybe you could say this is two dice 42:51 and you roll the two dice 42:53 and let's say accidentally someone sets it up 42:55 so it's the same dice 42:57 and whatever the green dice is, is this 42:59 and whatever the green dice is, is this 43:01 as a mistake. 43:03 This would never happen in the real world 43:05 but if that did happen 43:07 this is just slightly more advanced version of this 43:09 but what do you think 43:11 these prices would be 43:13 moments after you set up 43:15 the market. 43:17 Zeros on the diagonal. 43:19 Yes, precisely, yes. 43:21 So what I'm trying to explain here 43:23 is that 43:25 as the events become more 43:27 objectively related to each other 43:29 these prices kind of do this weird thing 43:31 where they kind of bunch up 43:33 in these observable ways 43:35 and this is a cool thing 43:37 and if you do this 43:39 you get everything that you had before 43:41 you get what's called the marginal probability 43:43 just by adding 43:45 so you get just from addition 43:47 let me put this back up 43:49 you can see that if you just add across the rows 43:51 that it's 50-50 for the first coin 43:53 and 50-50 for the second coin 43:55 and 50-50 for the first coin 43:57 and 50-50 for the first coin 43:59 and 50-50 by the other dimension 44:01 so you get everything 44:03 you don't lose a single thing 44:05 you get everything you got before 44:07 but you get even more 44:09 you get these conditional probabilities 44:11 that reveal the relationship between things 44:13 so you have professional speculators 44:15 who research these issues 44:17 and become specialists 44:19 on whether or not Brexit 44:21 would affect whatever 44:23 so this is no surrender of sovereignty here 44:25 this is just giving advice to the voter 44:27 so the voter can still decide what they want 44:29 but we're getting very very very high 44:31 manipulation resistant 44:33 knowledge emerging here 44:35 so this is again an old slide 44:37 because I made it before 44:39 believe it or not I've been doing this 44:41 project for a while and this image is very old 44:43 in particular but 44:45 this is, if you passed 44:47 so I'm imagining, you have to imagine that we're in like 44:49 2014 or something for this 44:51 and so I'm saying next year if we pass some law 44:53 will it actually affect 44:55 our odds of getting 44:57 will the law actually 44:59 change our likelihood of getting 45:01 the warmest year on record and you do that by just 45:03 comparing the ratio of the prices 45:05 when you don't do the law 45:07 to the ratio of the prices 45:09 if you do pass the law 45:11 and I have an even more 45:13 crazy example here 45:15 so this is the guy who's the CEO 45:17 of General Electric 45:19 a gigantic corporation 45:21 in the United States and 45:23 I just want to kind of quickly just try to get 45:25 through to what's going on because this problem 45:27 is not just 45:29 you know, the problems I've 45:31 mentioned apply equally to actually 45:33 CEOs because they're also elected 45:35 the board of directors is elected 45:37 or at least the bylaws 45:39 can determine how that exactly happens but 45:41 mostly the shareholders 45:43 vote and elect the board of directors 45:45 who hires the CEO so this problem 45:47 is present in corporations as well 45:49 as in the public 45:51 sector it's the same voting problem 45:53 so I wanted to kind of make that 45:55 with this example and it's easier 45:57 in the corporation case because you have a clear 45:59 metric determining the metric is a little 46:01 difficult like what is good 46:03 should we reorganize society based on how 46:05 likely it is to get global warming down like 46:07 probably not reorganize 46:09 everything in society you know there's things that 46:11 are more important than that like you know 46:13 not dying or something so 46:15 but with the corporation it's easier 46:17 because the stock price 46:19 inclusive of any 46:21 lawsuits or any kind of 46:23 you know being sued for fraud or something 46:25 inclusive of all that 46:27 is really just the metric and so 46:29 I have here this example of this mirroring 46:31 that I brought up before so if you just start 46:33 with one dimension 46:35 and you say will this guy stay as 46:37 the CEO and you can see 46:39 something weird is happening but these are 46:41 the no and the yes are a mirror image 46:43 which is why it's pointless to plot it 46:45 because it's a waste 46:47 of space because there's only one degree of freedom here 46:49 so you should only have one line 46:51 but then below I have a 46:53 second separate market 46:55 so it's completely separate and then I'm going to 46:57 combine them later and that's the 46:59 stock price of GE in the future 47:01 so this market is created today 47:03 and I'm saying what's the price going to be on 47:05 whatever this is May 2nd next 47:07 year so and then we're going to 47:09 move through time so you have to actually 47:11 I think you know kind of 47:13 turn your brain to the attention mode 47:15 to kind of figure out this asset is 47:17 going to be pay out something 47:19 based on something that happens in the future 47:21 and it's going to be created here 47:23 and then we're moving through time 47:25 to the present and this 47:27 is the present moment which is 47:29 after whatever this is 26 47:31 weeks after this was created but still 47:33 before this 47:35 event has happened 47:37 but it's a basic law of 47:39 finance that whatever 47:41 the future value of something should equal the present 47:43 value of something minus modulo 47:45 the interest rate the time value of money 47:47 and so this thing should 47:49 your guess at what the stock price will be 47:51 next year should really just be 47:53 the stock price today so they're 47:55 kind of similar 47:57 I hope that wasn't confusing because I actually can't 47:59 remember why I brought it up at all but the point 48:01 is the corporation 48:03 stock price is going down and 48:05 the CEO may stay or he may 48:07 leave seems like there's tremendous 48:09 uncertainty there 48:11 and we're wondering like is the CEO 48:13 jumping ship or should we fire him 48:15 because things aren't going very well 48:18 and this is a totally contrived example of course I just invented all these numbers for the example but what I say now is you take the two separate markets and you combine them and after you combine them you can then re-separate them by just adding like I did with the coins and if you add this is 1 plus 3 the price of 1 plus 3 and then it is the green line that you saw before and then it's mirror is the red which is 1 minus that and then you can 48:45 add 1 and 2 here and you get this blue line that you had before so you get everything that you had before as I said but you get this cool thing where you get these you get all the dimensions at once and then without making it too kind of like you know I can explain the details but I think you know I'm worried about losing people here but long story short this you just do some basic arithmetic you have here the stock price if the CEO stays in 49:15 red and the stock price if the CEO leaves in blue so you can just see as clear as day that it's higher if he if he stays so in this contrived example that I just invented you can see that the CEO is sort of doing a better job than whoever the expected replacement is so I don't want to go into that but yes okay so you can use this for basically everything that's a slide that I that I removed but it's a kind of funny one but so 49:45 it's like which CEO bakes the stock price the best and again this is the same is a collective action problem that the shareholders face if you own shares of anything you get stuff in the mail where it's like should I should you vote for this and I just you throw it away in the trash immediately because you have no idea what they're talking about and you have like no 0% of the company but this would actually be helpful for you to know oh okay should I get rid of these board of director people or should we take 50:14 XYZ action or something and then you say oh which president would make the 50:18 unemployment rate the lowest because we don't like unemployment or you could say 50:23 which Fed policy helps GDP the most or will this law you know change crime or 50:28 will any of these things happen so that's that's the cool thing and now I 50:32 have to explain the multi-factor part which is really the same thing but and 50:38 again I do apologize I planned on changing these two more European things 50:41 but then I decided that that would be just too absurd for me to try to do and 50:45 then I would probably say something like embarrassing or something like that so I 50:48 kept the Democrat and the Republican are the two major parties in the United 50:53 States and Elon Musk is a guy who makes electric cars and giant spaceships so 50:58 hopefully you know who that is but I'm saying now that with this multi-dimensional 51:04 trick you can erase this this this pernicious effect of why you always have 51:09 the two terrible candidates because what you are going to do is condition it 51:15 on the likelihood that they win to cancel out all of the the the badness 51:20 associated with the fact that some people are unelectable for some mundane 51:25 trivial reason like they misspoke or they they tripped or something it's so 51:29 funny right like if someone trips something you imagine someone like 51:32 walking out into a presidential debate and if you have like a primary debate 51:35 and if someone like just tripped and fell over like even if they were the most 51:38 even if they're the most the best person for the job on planet Earth they 51:42 tripped and fell over and it was on camera it would probably just be that 51:45 would be the end of it you know it kind of blows it boggles the mind that how 51:49 do we even run society when the best person can be you know you wouldn't do 51:53 that if you were hiring someone you're trying to hire someone to like head up 51:57 the new division for your corporation or it is for your nonprofit or something 52:02 just because they trip you would still probably offer them the job you just be 52:06 like oh no you know you trip but in the in the when it comes to voting it's like 52:10 if someone does any gaffe it's just over you know it doesn't make any sense to me 52:13 but that's okay so the issue is we're going to say what is the okay will 52:21 someone win is this dimension and it's split into four states instead of two 52:27 just like I split the dice thing into six instead of two and then I'm gonna 52:32 say is there a good economy in the United States where I defined it as 52:35 less than 5% unemployment as measured by whatever you three years reported by 52:39 the Fed so yeah you can have conversations about whether or not those 52:42 I'm gonna get to that in a second which is like are those numbers coming in and 52:46 he is a garbage in garbage out like what do we do with this these metrics coming 52:50 in because that's it's just more again as I mentioned this this topic is very 52:54 big and I can only talk about so many aspects of it at once but you know here 52:59 we're gonna say does someone win and does or is the economy good and we see 53:05 there's almost certainly going to be a terrible economy 0.99 and Elon Musk is 53:10 almost almost certainly not going to be elected 0.009 but he's of the 0.009 53:15 and of the 0.0095 we've got of being a good economy it all is kind of on the 53:21 Elon Musk tile so to speak and so even though Elon Musk is the lost cause you 53:28 can do some division here and display this to the user and again I'm gonna 53:32 explain like as the user friendliness is obviously terrible at first but I 53:37 think it will get there but you can say okay what's if you elect this person 53:44 conditional on electing Elon Musk how likely is it that the economy will be 53:48 good and then it will be 100% versus 0 and and then I have here that you can 53:55 yes so now even though someone so you know that Elon Musk's it's kind of 54:01 paradoxical because you measured the electability of Elon Musk and 54:04 determined it to be very low but because you have measured it explicitly you can 54:09 actually factor it out of the good economy thing just by dividing by it and 54:14 so since the election these are all you know prices of stuff that hasn't happened 54:19 yet in the future so you're the vision I have is that you people are lining up to 54:24 vote and they've done no research and then they log on with their phone and 54:27 they see something like two-week moving averages of these prices or something 54:31 and they just think well you know I've done no research at all but I really 54:34 should vote and I kind of just look up this blue section and they're just like 54:38 well you know so that's the vision is that people would stop caring because 54:43 they'd be like well you know it says the Elon Musk probably won't win but these 54:47 guys are not helping me out at all and you know what the heck does this does 54:51 this system know anyway because you know we've elected unelectable people 54:57 before you know Donald Trump etc so so then you I would get the voter you the 55:03 voter would be like you know come on like who cares about that it says .009 55:08 you know I've got nothing to lose this is my vote and then they just say well 55:12 uh-huh let's you know all the voters waiting in line are like okay well you 55:16 know why not let's just throw let's put the vote on this guy because we know 55:20 that he's got the 100 he's actually got the highest number so he actually kind 55:24 of becomes electable again and so this is better for all the people who are 55:28 uninformed or angry because the less they know the better because they they 55:33 should ignore all the weird media campaigns and all of the other attempts 55:39 to kind of influence their vote and just focus on things like this we can have a 55:43 conversation about manipulation but you know yeah the more the more everything 55:48 is just confusing for them the more they might just fall back on relying to this 55:51 and again I want to remind you that 71% of Americans don't even have a clue who 55:57 their representative is and most of them don't vote at all especially in the 56:01 House of Representatives legislation kind of section so almost no one is 56:06 voting and almost no one cares about this so those people are like a raw 56:10 material like a resource you just get this uninformed vote to become informed 56:14 and so it's just like that mentioned before at the restaurant where you had 56:20 the three blue bars and one of them became green as the selection but I'd 56:26 like to explain a little bit in more detail how we yes so here's the thing is 56:31 what if you don't know if Elon Musk and or Peter Thiel is the best because you 56:35 think they're both pretty great and maybe they're both unelectable but maybe 56:40 and maybe Elon Musk is even more unelectable than Peter Thiel who was 56:43 someone who is vaguely he was like a delegate in California and but also a 56:49 kind of engineer type or something and then you know I never like Oprah you 56:53 know and this is Kim Kardashian you know it's like whatever so you have all 56:57 these up and then you think oh no the vote is going to be split between Elon 57:00 Musk and Peter Thiel you know the smart person vote is going to be split and so 57:05 then I have to go back to voting for the lesser of two evils because the vote is 57:09 going to be split but you actually don't because only one of them has the highest 57:13 number so the smart people will just say well you know I was pushing for 57:17 Peter Thiel but 100% is bigger than 99% so so there it is and then you have the 57:23 so then you've escaped electability and then just two more slides about yeah so 57:29 there was my plan for like actually making this happen other than you know 57:32 writing the code and everything I think you have to kind of ramp it up using 57:36 things that people already care about like sports and whatever if you love 57:41 sports betting you know probability of someone winning conditional on them 57:45 being whatever two on-site kicks or something I don't know this is probably 57:48 even the wrong I don't know anything about what would interest people but and 57:53 then you just kind of need to do it for a couple years along a variety of things 57:57 and this has already been done and the accuracy has been proven and so you just 58:04 have to show it to people it's a little bit more of letting them experience kind 58:08 of what's going on and again I think people hate the existing system so much 58:14 in the United States and most don't vote at all so I think that you know 58:18 there's kind of a there's a little niche here for it just kind of work its way in 58:23 in fact on CNBC they now I remember 2004 they mentioned it once or twice and 58:29 interviewed John Delaney the CEO of in trade where I got that slide I got that 58:33 image from those prices and then he died on an unrelated Mount Everest accident 58:39 which is real and threw the company into chaos long story but CNBC has done 58:46 more and more America television network has done more and more coverage of these 58:51 betting market prices even after in trade closed down after 2012 and they the 58:56 new website election betting odds showed up and then they do bet fair bet fair 59:00 here in Europe on them so I think actually people are kind of getting in 59:04 more yeah this is again the thing is topic is so broad that you can't 59:08 possibly talk about all of it at once but it's like what on earth are we 59:11 gonna actually measure is it gonna be all unemployment rate what should it be 59:14 it could be land value I think that's a good one or it could be anything that 59:18 humans can measure kind of with a random poll of their kind of jurisdiction or 59:24 something this is a very complicated topic and in itself without how to get 59:29 that not captured but there are these ways sortition is like randomly picking 59:35 names out of a hat and then you can you could have people you could call people 59:40 the way we in the United States we do jury duty you just call people over and 59:43 say force them to report on you know what their salary is with that what 59:48 they were unemployed you know how much they like their government or whatever 59:51 just kind of and then there are all these clever tricks random response and 59:55 things to like force some noise but yeah this is a whole topic in itself and we 59:59 don't have time for it so that that is just a crazy introduction to my project 1:00:03 and it's super weird but it is actually relatively so you can go to this the 1:00:08 site Bitcoin Hivemind calm and I had a bunch of people look at it including a 1:00:13 little bit you know including Adam back Peter Todd Andrew Paul straw Roger Ver so 1:00:19 a lot of people like this idea and it's sort of old so it's time for it to come 1:00:25 back you saw those the how Finney posts from like 2000 whatever doesn't for 1:00:28 doesn't eat or whatever that was so it's a it's kind of a cool idea so 1:00:33 that's the talk and if anyone has any ideas on how to improve the talk please 1:00:36 come up to me later because it's a very a lot to get across and I'm not sure 1:00:41 what the best way is so anyway so that is the talk so thank you very much 1:00:48 oh yes okay so if you go to the site you'll see we don't exactly have because 1:01:00 the weird thing is I designed it to be a sidechain of Bitcoin and sidechains of 1:01:03 Bitcoin are also held up but we have a kind of test net that it not only has it 1:01:09 has like a little GUI with a little little graphs but yeah there's a lot of 1:01:13 improvements still to be done but there is actually a there is actually a yeah 1:01:20 there's a version of this on the site and everyone should check it out and we 1:01:23 did rebase it to a recent Bitcoin core version like I don't know like eight 1:01:29 months ago so it's not hopelessly obsolete and I've been trying to keep 1:01:34 all these things synchronized so yeah there is some some stuff there's lots to 1:01:38 do still but we do there's like a minimum viable thing there that you can 1:01:43 run on testnet yes so we should we wait for the should we do the thing or should 1:01:50 we know oh there we go okay I think you made a very persuasive argument for the 1:01:58 use of prediction markets and I have a kind of philosophical question so I 1:02:02 think the general argument is that you know we can do this sort of collective 1:02:05 market mechanism and that humans are good sort of transducers of information 1:02:11 from the environment in this market mechanism which you then optimize the 1:02:16 decision so so I guess my question is like do you really just need humans at 1:02:21 all for the system what if you just had sensors or other other information like 1:02:27 there's no good questions just since this this can only give advice you know 1:02:32 it so it will optimize so what it what this will do is attempt to aggregate 1:02:36 society's information on whether or not someone elected will have some will 1:02:41 move some metric up or down more than someone else but there's no it says 1:02:45 nothing about values so maybe you want the unemployment rate to go up for some 1:02:50 reason you know it's like it says nothing at all about values and you could 1:02:55 have several different markets all on different things and people could 1:02:58 aggregate those values in different ways like someone might say oh I don't know 1:03:02 you know I really don't want someone could say brexit is gonna cost us a lot 1:03:06 of money as estimated by this market but someone else could say oh brexit is 1:03:10 going to result in XYZ immigration or something and everyone could be in 1:03:15 perfect agreement about all those numbers and then just say well I care 1:03:19 about immigration more than I care about how much money it will cost because the 1:03:24 UK is a rich whatever blah blah blah country so we can afford it so it says 1:03:28 nothing about values whatsoever have you read the book brave new world yes think 1:03:34 about it yes it's a good book in fact Adolphe Huxley's book partially 1:03:41 inspired Neil Postman's book I'm using ourselves to death which is the book 1:03:46 that I mentioned before which is about how media ecology has shaped the way we 1:03:54 run society including the elections where instead of having the three hour 1:03:59 four hour super debate I've just uninterrupted talking we have like 1:04:03 televised 30-second rebuttal or something like that but yeah it's good I 1:04:08 I think I'm more worried about 1984 the thesis of part of the ending of Neil 1:04:16 Postman's book was that 1984 threat was overemphasized and that the brave new 1:04:23 world threat was under emphasized and that we should have worried more about 1:04:26 brave new world but I don't know there may be a tie or something it's not it's 1:04:31 not looking very good but the 1984 ones is looking especially bad that stuff in 1:04:35 that stuff in China is just like that's just exactly as Phil Zimmerman said it's 1:04:40 just a lot just pure stasis forever and that is horrible I mean it's just that 1:04:45 will those people will be trapped until something it'll be exactly like the 1:04:49 Great Wall of China really where they'll be trapped into some other technological 1:04:53 force it's just just like I don't know what I know exactly how to describe what 1:04:58 I'm saying but until they are disrupted by the the fact that they are they've 1:05:03 been held back on new ideas forever so that's a sad thought yes does your 1:05:10 system deal with the fact that like unemployment like you say that these are 1:05:15 like factors which have long they have like delayed effects on society is that 1:05:21 calculated in there somehow yeah as I say yes that's a good question it it goes 1:05:27 into the what I said before about values so it's true that in the world of 1:05:31 economics it's often said like the stock market is like a leading indicator and 1:05:35 then there are these other things that are present indicators and then the 1:05:39 unemployment rate is a lagging indicator and so the economy goes bad the stock 1:05:43 market crashes immediately but then people don't start getting laid off for 1:05:46 like a couple months or something but this is just I mean if you wanted to 1:05:50 account for that you could just put the unemployment rate on different dates you 1:05:54 could say well what's the unemployment rate what's the stock market gonna be in 1:05:58 March and what's the unemployment rate going to be in September and try to do 1:06:03 harmonize them but there's no need for this project to take that type of thing 1:06:08 that the topic what the the topic of the market like what is it about that is 1:06:16 there's nothing to do with what exactly how the project works because you can 1:06:19 change that to try to do anything that you anything you like that it would be a 1:06:25 waste of time to do something that wasn't measurable like you know what is 1:06:28 your favorite color and I have to have things in there to kind of jam that 1:06:33 halfway through so make it impossible to work but if but yeah it's there is this 1:06:41 takes this project takes no position on what you would want to know so you may 1:06:46 want to know the unemployment rate or you may or you may not or you may not 1:06:49 think that the unemployment rate is interesting thoughts on selling your 1:06:54 vote so if somebody doesn't have like a like they don't value their vote but 1:06:59 maybe somebody else values I vote for a dollar yes there is a Robin Hansen the 1:07:04 blog that I quoted earlier that how Finney posted on he wrote something 1:07:08 about a quadratic voting which I think is unfortunately too complicated for 1:07:12 anyone to any to anyone to realistically switch from a current mode of voting to 1:07:17 that but there was a is a kind of weird thing where you could accumulate your 1:07:22 vote and it would square and then you could sell it or something but again 1:07:25 this is not this takes no position also on whatever society is really using 1:07:30 because this is about getting the equal amount of knowledge to everyone at once 1:07:36 in the form of the price so it's everyone sees they everyone sees the 1:07:39 same price so it kind of doesn't really matter as I said if you use proportional 1:07:44 representation or some other kind of voting this should work in all those 1:07:49 situations and in all those situations you still have the problem that the Ken 1:07:54 arrow Nobel Prize problem of that whatever you come up with it will 1:07:59 probably not really work because the idea there are two conflicting ideas 1:08:04 embedded in voting one is that everyone should be represented and the other is 1:08:08 that the outcome should be rational and you actually can only have one in the 1:08:13 mathematics of aggregating the vote so the one that most people pick is that 1:08:17 the outcome should be rational and that some people should but that's not what 1:08:21 you picked it with proportional representation but again it's a 1:08:24 different conversation but you the the idea is that the vote should be a guess 1:08:32 at what everyone will ultimately agree on they'll ultimately find to be 1:08:36 non-controversial so if you vote to get rid of slavery or you vote to establish 1:08:42 women's rights or something that you should that should what's really going 1:08:46 on is that you're kind of guessing at what everyone will agree was always the 1:08:50 right answer in the future so these schemes about changing the voting 1:08:56 mechanism or not I think they're not also not what this project is about 1:09:00 because this should work for just about any weird voting any weird aggregating 1:09:03 thing yes sorry that's okay I have a few questions but I have to pick one 1:09:11 right yeah okay I'm gonna pick one there's issues with liquidity because 1:09:16 the Elon Musk market would obviously have low liquidity yes liquidity yes 1:09:21 excellent question so that one that you want me to take them one at a time you 1:09:24 can probably like say a shit ton yes well there is okay so the answer is 1:09:29 probably just gonna be you try and get as much liquidity as you can no no no 1:09:33 you're right that but no that's not you're wrong about the answer but I can 1:09:38 talk a lot about how that's done because you are completely correct that why 1:09:42 would anyone buy this weird state in this giant dimensional thing and the 1:09:45 answer is that in this the market is done in a different way using something 1:09:50 called a market scoring rule that Robin Hanson actually invented for this for 1:09:54 this purpose and he's a physicist and I don't know why I brought that up because 1:09:58 that's a you know appeal to authority but and so is this but but he Robin 1:10:05 Hanson is the guy who runs his blog and he's over down here and he invented this 1:10:09 thing where actually no matter how many states the market has you can always 1:10:12 trade against the market itself and all you don't actually need a counterparty 1:10:16 so someone gives me someone when the person who creates the market puts a 1:10:23 little bit of money up as a kind of sacrifice and then it's kind of like you 1:10:27 have a dish and you have it on balanced on a needle and people put money on and 1:10:32 the dish kind of tilts around and the angle of the dish is actually what 1:10:36 determines the prices and how many different marbles people get me one 1:10:39 state is fixed we only need one underwriting yeah you only need is a 1:10:44 little bit of money in the center at first and then everyone can show up and 1:10:47 make trades even without any counterparty at all so the liquidity can 1:10:51 never fall to zero so it will always be possible to update the market price 1:10:55 which means it will always be possible for someone who notices an error in the 1:10:59 entire array of prices to update it so it's actually 100% solved and more to 1:11:04 the point it's actually much easier in blockchain technology to just have this 1:11:07 thing just be a sequence of atomic updates in a line so it's actually 1:11:12 solves several different problems at once but as I mentioned the projects 1:11:15 kind of big and you can only talk about so many things at a time but you're 1:11:18 correct that would be fixes it really well so that's cool 1:11:22 does I'll look into that that is very cool the other question was about that 1:11:28 efficient market efficiency arguments depend upon bad mark bad money 1:11:33 eventually leaving the market fully or it's like significantly yeah that's 1:11:37 another coming in faster than it's leaving and because even though this 1:11:44 system is like quite you know cyberspace and quite purist and so it 1:11:48 can hardly be uneconomical it can persist in being uneconomical but the 1:11:54 money that it's set in could still be secretly not performing the economic 1:12:00 function yes this is the manipulated prices question right yes I think so no 1:12:07 okay what was it then I didn't understand so if the general if the rest 1:12:14 of the world is not economically minded and efficient enough it there is no 1:12:20 guarantee that your prediction markets will have more good than bad money in it 1:12:24 and they'll consistently produce bad results due to the inefficiencies of 1:12:28 actual market like in practice okay so the the question is does I don't not 1:12:36 sure like what do you know I'm not sure what really good or bad money means but 1:12:40 I assume that you mean that yes okay well this again another thing I didn't 1:12:46 explain is how I solved the Oracle problem which is how this technology 1:12:51 becomes aware of actually what the unemployment rate is or who was actually 1:12:55 elected which is itself a document that I wrote and is on the front page of the 1:12:59 website Bitcoin hide my calm and is very long and filled with lots of you know 1:13:05 writing and math and things in there but I did not explain that at all because I 1:13:09 tried to give that talk and it's hopelessly boring and no one can I mean 1:13:13 I don't do a good job of explaining it I guess but in the software I have a 1:13:16 little simulator you can open it up and click on this little beaker 1:13:20 thing icon and it will show up and you can say oh what if the people try to 1:13:24 resolve the outcomes this way or that way and you can see if you can if you 1:13:28 can try to break any of my security assumptions but I don't think was that 1:13:32 what you were asking about is how does the protocol figure out what actually 1:13:34 happened or you're saying that people will bet and they will be bad people who 1:13:39 will just bet randomly or something oh yes so this is the low knowledge I think 1:13:46 you're saying okay I think yes so yeah the market can only aggregate knowledge 1:13:51 that is present in in the minds of the traders so the traders don't know 1:13:57 anything it's useless so as I explained with the okay we'll get well let me 1:14:02 finish this one in a sec so it's like if you have a market prediction market on 1:14:04 the outcome of a fair coin toss then you cannot like gain any you it would be 50 1:14:10 50 the no one would pay 60 cents for one of these states because the other person 1:14:15 would buy the alternative state for 40 cents knowing that it's a fair coin and 1:14:19 that you know over the long run they will they will tend to do to do well so 1:14:24 but is that what you were saying or no yes 1:14:38 sure yes I agree 1:14:46 okay okay yes okay so the question is a kind of plutocracy question that says 1:14:58 what if most of the people who have money are have an agenda and then they 1:15:03 can manipulate this market but but this is not a plutocracy this is not like 1:15:07 $1 one vote this is like $1 risk to one vote so if you have a plutocracy you 1:15:13 could just keep it in something else and it would be safe but you know I 1:15:17 would be safely earn or whatever 4% return or whatever we're going on you 1:15:22 don't have to risk it in this and so if you did you would be risking that you 1:15:26 would lose it yeah yeah yes no but it is not though because think about this you 1:15:37 have to get the actual metric up so even if you manipulate the prices 1:15:41 tremendously you have to actually get in you you manipulate the prices 1:15:45 tremendously and no one has enough money to defeat you then you will get whoever 1:15:50 it is Donald Trump you'll get Donald Trump elected instead of Elon Musk yeah 1:15:56 but no I was let me explain no I think because I think I understand what you're 1:15:58 saying so it's like you will get you will get your way a few times but 1:16:04 inevitably you'll get Donald Trump and the unemployment rate with that the 1:16:09 price of that other thing will remain low or will be at zero instead of a 1:16:13 hundred so all the people who can cast counter bets and they say well there's 1:16:18 you see because it's mathematically identical it's like yes is one minus no 1:16:21 and so if so yeah there's you could buy if you thought Elon Musk would do well 1:16:28 you can buy this or you can buy everything other than you can just say 1:16:33 instead I know that whatever I know that Hillary Clinton will screw it up so I buy 1:16:37 all these other ones so as I know that there's not a chance that she'll do a 1:16:41 good job and so then you get something for less than $1 that ends up being a 1:16:45 dollar and so you still make money so even though you can if you have most of 1:16:49 the money you can manipulate the outcome the few people who are forecasting 1:16:55 accurately will be multiplying them their wealth by five times or each cycle 1:17:00 and so eventually they will be the ones that have all of the money and it will 1:17:02 create exponentially more money to manipulate the system yes 1:17:14 rational ignorance 1:17:20 sure 1:17:32 necessarily because this is again the traders are free to decline they can say 1:17:40 I can't improve on this array of prices so they can say even though I've got a 1:17:46 lot of money and I could move the prices to whatever I want they'd say well they 1:17:48 kind of look correct to me so instead I'm gonna do something else with my 1:17:51 money I'm gonna go play golf or something you know but if if there's an 1:17:56 error in the prices anyone can 1:18:03 yes no but you understand it's different from voting because if you feel very 1:18:10 strongly about something you can put more of your wealth into it you've been 1:18:13 maybe and you could even maybe take out a loan or something so this this is not 1:18:17 necessarily just measuring one vote per person each person is free to modulate 1:18:22 their influence in the market by how confident they are so a lot of people 1:18:26 take positions that then then they take positions on global warming and then 1:18:29 they won't bet in the global market so what did they really believe yes okay 1:18:34 let's go more questions yes Emanuel Wallerstein he's a world systems 1:18:41 theorist and what he describes is that we are in what is called a bifurcation 1:18:53 point which is in the last 100 years or so it was very easy there was a very 1:19:00 linear kind of course for the destination of events for example like 1:19:07 when you see the price on a market is going up it's very easy to predict where 1:19:12 it's going to go next but when in a in a system there are too many when it when 1:19:21 there are too many when a system isn't able to accurately when a kind of 1:19:25 worldview isn't able to completely account for all of the variables or all 1:19:31 of the phenomena those kind of factors can can build up in a system and what 1:19:39 happened is a complex system reach a kind of tipping point where things start 1:19:45 to cascade and when a system so for example like when the price starts to go 1:19:51 down and become very difficult to predict of what rate is falling how far 1:19:55 it's going to drop and until what level is going to go down and the entire I 1:20:04 think the entire premise of what you're talking about is the people voted for 1:20:15 Donald Trump because they were misinformed and if they were informed 1:20:21 maybe they could make a better decision what if people what if what if people 1:20:29 what people were informed and still chose to vote for Donald Trump and what 1:20:36 if what if history shows us that this is the inevitable course of all human 1:20:44 civilizations and that there is no mechanism that is going to save us from 1:20:51 a process of renewal this inherent in civilization itself I think that's far 1:20:59 too pessimistic to make any sense pessimistic is the idea that there's no 1:21:03 the idea that there is no possibility of technological improvement I think is 1:21:08 very pessimistic well look at I don't know then if it's a rebirth and what's 1:21:15 the what is how is it different from what happened the last 30 years so the 1:21:19 last 70 years well would you say the Roman Empire breaking up and 1:21:26 Christianity taking over in Europe was progress or was that regression was the 1:21:34 slavery in Rome was that something that was was bad oh yeah well I think it's 1:21:41 clear now with hindsight it's interesting today we all everyone agrees 1:21:46 that slavery was wrong but in the past it was a hotly debated issue and a lot 1:21:51 of people took it for granted that slavery was the morally correct position 1:21:56 and that it was um so obviously that's not yeah well I mean the thing is so 1:22:02 it's a question about about knowledge though I mean it was originally taken a 1:22:05 lot of things were originally taken for granted and then we had to we had to 1:22:08 learn more and improve our you know our legal and governance technology you know 1:22:15 we had to improve our laws and they were improved many different times I mean 1:22:19 there was a time when there was no democracy whatsoever and then in ancient 1:22:23 Athens it was accidentally introduced by someone who was using it for selfish 1:22:28 reasons they just kind of kept doing it and then Rome had all kinds of weird 1:22:34 tinkering that they were doing with their setup but yeah I don't I don't know 1:22:41 if I would call the Enlightenment progress and I would call ancient Greece 1:22:46 progress but I don't know maybe I would call Florence in the 1300s but I don't 1:22:53 know if I would call it and everything after the Enlightenment in the West I 1:22:56 would call progress but I don't know if I recall anything else yeah it's funny 1:23:05 that people do they do that like the World Bank yeah yeah the the joke is I 1:23:12 should just measure energy consumption and that is something so you know very 1:23:15 from the stem department right that it's just like doesn't have any of these but 1:23:19 as I said it's not it this project takes no stance on values it just tries to 1:23:23 provide people with information and I think it's plausible that if people had 1:23:27 more information they might still have voted for Donald Trump yeah yeah no I 1:23:32 thought we have more questions that we can so last question then make this room 1:23:41 for something completely different yeah what was your what did you think about 1:23:49 the conference in Lisbon oh yeah yes I was at the Lisbon conference ah that's 1:23:54 a good one you really kind of well you know actually that's funny that you 1:23:58 mentioned that I had a great time at a conference in Lisbon building on 1:24:00 Bitcoin you know it was yesterday in the day before and it's great to see 1:24:05 everyone as always and people present a lot of interesting ideas but I kind of 1:24:09 wonder about something I have a very different view and I have no idea if how 1:24:14 many people share this view but for me there's a kind of drama in the space 1:24:18 that makes the conference is much more exciting and so they had scaling one in 1:24:22 Montreal in 2015 and that was just like so exciting and then stuff kind of gets 1:24:28 old and you know I got a scaling three wasn't as interesting as scaling one and 1:24:32 two and then it was kind of like breaking Bitcoin kind of tried to it had 1:24:38 some reason it had more drama and I think these things where all the 1:24:42 technical people meet have they go through these waves somehow I don't know 1:24:46 I can't quite explain it and I don't want to attribute it to anyone or 1:24:50 anything I don't know I don't understand it myself but I think sometimes there's 1:24:54 just a need for a conference and it just appears and it's a great success it's 1:24:58 like lightning in a bottle or something and then then people try to replicate it 1:25:03 and it's parts of it get you know just a little bit less interesting and sometimes 1:25:11 I feel that way you know there's a kind of capture you know that something is a 1:25:15 success and then everyone wants to affiliate with the success and then you 1:25:18 can have these weird cycles and so I enjoyed it a lot I loved especially that 1:25:24 I presented at the second half of day two and I loved that half not just 1:25:28 because I was in it but there was a lot of stuff that referenced my kind of 1:25:32 areas of interest including Sergio's Drivechain thing and also talks about 1:25:36 like super soft forks and these other kind of theoretical things that I'm 1:25:40 interested in and yeah so I I like that I I don't know it's like these these 1:25:47 conferences we you know we do so many conferences and it's very hard to like 1:25:50 put any of them into context but yeah I thought it was very neat I think the 1:25:56 community is very it's a very interesting you know I if you saw if you 1:26:05 watch my talk then it's a little bit of it is about a kind of my frustration 1:26:09 with how slow things are in terms of the reactivity to altcoins but a lot of 1:26:15 people are very proud of the fact that they are resistant to any mental 1:26:19 manipulation at all they say oh we're not gonna let that affect our decisions 1:26:23 our technical decisions which is admirable in a sense but that is a kind 1:26:27 of a weird difference of opinion and you do see a lot of that with these 1:26:30 conferences in the later waves a lot of very academic topics that are kind of 1:26:35 very you know a lot of math and debatable applicability it's time for a 1:26:42 closing statement oh yeah statement yeah that's like in an American television 1:26:48 presidential debate where the 30 seconds long and just have a lot of boring words 1:26:53 about freedom but yeah I mean I don't think I have a closing statement I'd 1:26:57 rather ask I'd rather answer more more questions I quite liked a description of 1:27:01 Lisbon is lightning in a bottle that was great it's a pun on the phrase and 1:27:07 lightning network 1:27:14 yeah and this project has to it's so bizarre and experimental that it has to 1:27:20 be a sidechain or an altcoin if it can't be a sidechain because it's just so 1:27:24 weird there's no possible way that it you could get people to buy into it and 1:27:28 you know it's kind of it's like it's a but yeah as I explained you know you'd 1:27:34 start this off as you started off as something experimental and people would 1:27:38 try it out to be a little bit like like lightning network and people could try 1:27:42 out a little bit of it at a time and then they could figure out what what 1:27:45 about it they like and what about they don't like and how to make it how to 1:27:48 make it better and then how to kind of scale it up and do all those other 1:27:51 things so I mean I have a lot of plans for all of those but I think you just 1:27:57 get people involved and then you do have a have a stuff about like you know 1:28:00 you try to get something where it's like how can you get I one thing I would do 1:28:06 is assemble a giant website with all of the entire track record of prediction 1:28:11 markets and I would try to compare it to other other people to try and demonstrate 1:28:14 how superior it is and I need I need something to crack that that statistical 1:28:20 ignorance that pervades the population where the prediction market says that 1:28:24 something has a 10% chance and then one out of every times you hear from your 1:28:28 friends an email that the prediction market said that thing wouldn't happen 1:28:31 but it happened prediction markets are wrong and I don't know what to do about 1:28:35 that you get those people to the people who are just we know numeral folks just 1:28:41 afraid of numbers and afraid of measurement and we still have depressing 1:28:45 one more talk this so she'll have some time for that yeah all right it won't 1:28:50 give Paul a grand applause here