Tag Archives: Prediction Markets

Bits Of Secrets

“It’s classified. I could tell you, but then I’d have to kill you.” Top Gun, 1986

Today, secrets are lumpy. You might know some info that would help you persuade someone of something, but reasonably fear that if you told them, they’d tell others, change their opinion on something else, or perhaps just get discouraged. Today, you can’t just tell them one implication of your secret. In the future, however, the ability to copy and erase minds (as in am em scenario) might make secrets much less lumpy – you could tell someone just one implication of a secret.

For example, what if you wanted to convince an associate that they should not go to a certain party. Your reason is that one of their exes will attend the party. But if you told them that directly, they would then know that this ex is in town, is friendly with the party host, etc. You might just tell them to trust you, but what if they don’t?

Imagine you could just say to your associate “I could tell you why you shouldn’t go to the party, but then I’d have to kill you,” and they could reply “Prove it.” Both of your minds would then be copied and placed together into an isolated “box,” perhaps with access to some public or other info sources. Inside the box the copy of you would explain your reasons to the copy of them. When the conversation was done, the entire box would be erased, and the original two of you would just hear a single bit answer, “yes” or “no,” chosen by the copy of your associate.

Now, as usual, there are some complications. For example, the fact that you suggested using the box, as opposed to just revealing your secrets, could be a useful clue to them, as could the fact that you were willing to spend resources to use the box. If you requested access to unusual sources while in the box, that might give further clues.

If you let the box return more detail about their degree of confidence in their conclusion, or about how long the conversation took, your associate might use some of those extra bits to encode more of your secrets. And if the info sources accessed by those in the box used simple cacheing, outsiders might see which sources were easier to access afterward, and use that to infer which sources had been accessed from in the box, which might encode more relevant info. So you’d probably want to be careful to run the box for a standard time period, with unobservable access to standard wide sources, and to return only a one bit conclusion.

Inside the box, you might just reveal that you had committed in some way to hurt your associate if they didn’t return the answer you wanted. To avoid this problem, it might be usual practice to have an independent (and hard to hurt) judge also join you in the box, with the power to make the box return “void” if they suspected such threats were being made. To reduce the cost of using these boxes, you might have prediction markets on what such boxes would return if made, but only actually make them a small percentage of the time.

There may be further complications I haven’t thought of, but at the moment I’m more interested in how this ability might be used. In the world around you, who would be tempted to prove what this way?

For example, would you prove to work associates that your proposed compromise is politically sound, without revealing your private political info about who would support or oppose it? Prove to investigators that you do not hold stolen items by letting them look through your private stores? Prove to a date you’ve been thinking lots about them, by letting them watch a video of your recent activities? Prove to a jury of voters that you really just want to help them, by letting them watch all of your activities for the last few months? What else?

In general, this would seem to better enable self-deception. You could actually not know things anywhere in your head, but still act on them when they mattered a lot.

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High Road Doubts

According to the intellectual norms that I learned when young, there is a high road and a low road for proposing reforms. The low road is populist and pandering – you ignore critics and try anything to get folks who could do something excited about your idea – sex appeal, group loyalties, demonizing opponents, overselling gains, whatever it takes. The high road is elitist and analytical – you carefully write up arguments, ideally with math models, randomized trials, and stat analysis, and present them to elites for evaluation.

Academics usually see the low road as deceptive – by ignoring critics and refusing to present careful arguments for evaluation, you admit your arguments are weak. Low road advocates counter that academic models and trials are often quite distant from actual applications — what really matters is that people try and evolve ideas in realistic contexts, and see how they feel about them there.

Twenty-five years ago, as a thirty year old wondering how to devote my life to pushing prediction markets, a mentor I respected basically suggested a low road – I should write a popular book to get lots of people excited. Instead I mostly chose a high road, going back to school to get a Ph.D., doing math models, lab experiments, etc.

Today I have reached a notable milestone along that road; my paper arguing for futarchy, a form of governance based on decision markets, is now published in the leading academic journal in the field of political philosophy: the Journal of Political Philosophy. This would be the abstract, if that journal had them:

Shall We Vote on Values, But Bet on Beliefs?

Democracies often fail to aggregate information, while speculative markets excel at this task. I consider a new form of governance, wherein voters would say what we want, but speculators would say how to get it. Elected representatives would oversee the after-the-fact measurement of national welfare, while market speculators would say which policies they expect to raise national welfare. Those who recommend policies that regressions suggest will raise GDP should be willing to endorse similar market advice. Using a qualitative engineering-style approach, I consider twenty-five objections, and present a somewhat detailed design intended to address most of these objections.

Of course I might do even better someday, perhaps publishing top journal articles on math models or lab experiments. Even so, this seems a good time to ask: is the high road really better?

I have doubts. What futarchy and decision markets mainly need, and have long needed, are organizations to try them out on small scales, to work out the little details that general ideas need for practical application. Small scale successes might then lead to larger trials, perhaps eventually at very large scales. And I doubt that publishing this paper, or further top journal papers, will do much to induce such trials.

A pandering popular book might do much more, if it actually got people to try the idea. They wouldn’t have to do it for the right reasons, by correctly evaluating pro and con arguments. In fact, it would be fine if the book gave most folks much worse estimates, as long as it induced a thicker high tail of enthusiasm to actually do something. A better idea for reform, with a big pool of rational advocates, might add much less value to the world than a worse idea for reform, matched with fewer less rational advocates willing to actually try and evolve their idea.

After all, beliefs mainly matter for inducing relevant actions. The high road might produce more accurate beliefs, but the low road may often get more things done.

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US Record All Calls?

Many claim that the US Government saves recordings of all the phone calls, emails, etc. that it can get:

Wednesday night, [CNN's] Burnett interviewed Tim Clemente, a former FBI counterterrorism agent, about whether the FBI would be able to discover the contents of past telephone conversations between [terrorist Tamerlan Tsarnaev and his wife]. He quite clearly insisted that they could. … On Thursday night, Clemente again appeared on CNN, this time with host Carol Costello. … He reiterated what he said the night before but added expressly that “all digital communications in the past” are recorded and stored. …

Former AT&T engineer Mark Klein revealed that AT&T and other telecoms had built a special network that allowed the National Security Agency full and unfettered access to data about the telephone calls and the content of email communications for all of their customers. … His amazing revelations were mostly ignored and, when Congress retroactively immunized the nation’s telecom giants for their participation in the illegal Bush spying programs, Klein’s claims (by design) were prevented from being adjudicated in court.

That every single telephone call is recorded and stored would also explain this extraordinary revelation by the Washington Post in 2010:

Every day, collection systems at the National Security Agency intercept and store 1.7 billion e-mails, phone calls and other types of communications.

Bruce Schneier is skeptical, however:

I don’t believe that the NSA could save every domestic phone call, not at this time. Possibly after the Utah data center is finished, but not now.

This seems to me a great place for a prediction market. It seems quite likely that the truth will be revealed within a half century, and if this claim is true hundreds of people must know who might be tempted to make a little extra money via anonymous bets.

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False Flag Forecasts

As admitted by the U.S. government, recently declassified documents show that in the 1960′s, the American Joint Chiefs of Staff signed off on a plan to blow up American airplanes (using an elaborate plan involving the switching of airplanes), and also to commit terrorist acts on American soil, and then to blame it on the Cubans in order to justify an invasion of Cuba. (more; see also)

One in seven people are convinced that the U.S. government was involved in a conspiracy to stage the September 11 attacks which killed nearly 3,000 people. A survey, which interviewed 1,000 people in the UK and the same number in the U.S., found that 14 per cent of Britons 15 per cent of Americans think the past administration was involved in the tragedy. (more from ’11)

More from ’08:

whobehind911

Such conspiracies aren’t always, or even usually, uncovered eventually, but such uncovering does happen often enough to make it seem socially useful to have betting markets on such questions.

Yes, such markets would have to be long term, and might need to be subsidized. And they might need to be housed in a reasonable distant and independent nation, like New Zealand.

But such market odds might offer an independent and reasonably reliable source to which doubters could turn when they weren’t sure how much weight to put on conspiracy theories vs. their skeptics. If you doubted who was behind the 9-11 attacks, wouldn’t it be great if you could turn to a betting market to better calibrate your doubts?

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Diagnosis Futures

From ’97 to ’99 I was a RWJF Health Policy Scholar (at UC Berkeley), and my final project and presentation was on what I called “treatment futures”, i.e., the idea of using decision markets to forecast treatment-conditional health outcomes for individual patients. I proposed:

  1. At major treatment decision point, post sanitized medical record & options to web.
  2. Subsidize [betting] markets estimating treatment-conditional outcomes (e.g. lifespan).
  3. Anyone can trade or add treatment options.
  4. Market estimates inform treatment choice.
  5. Outcome determines market asset values.

I also posted on this in ’07. Yesterday I learned that a new startup, CrowdMed, is spending $1.1M to try a related idea. They will have ordinary people “bet” on particular patient diagnoses. I put “bet” in quotes because they only bet donations, and they don’t tell users how individual predictions, individual winnings, and consensus estimates on patients are related. That is apparently part of their patented secret sauce – you’ll just have to trust them.

A patient pays $200 to post their problem, and promises to eventually declare a “correct” diagnosis. Each player is given $5 to start, and can only spend winnings on donating to Watsi patients. So if after several years hard work, you do much better than average, and end up with $20, you might donate that much – woo hoo! Player incentives to diagnose correctly are diluted further by the fact that they only predict what the patient will say is their diagnosis, not the true diagnosis. And players don’t get to look at a full medical history, just a few paragraphs of description.

Patients mainly pay for possible diagnoses to suggest to their doctor to consider, diagnoses that players believe might find supporting evidence, if only the patient’s doctor would consider them. So patients have to believe that their doctor will believe that these volunteer amateur detectives have useful diagnosis suggestions to pursue, ones the doctor would not have otherwise considered. Seems a pretty high bar to me.

My conditional forecasting concept could help patients even if patient doctors don’t believe in it, but it does require players to wait longer to find out if they win. And I think that players deserve a much higher fraction of the patient payments than this startup seems willing to give them — I expect CrowdMed incentives are way too weak. Many seem to have decided that the big idea in “crowd-sourcing” is getting amateurs to do for free what you’d otherwise have to pay professionals to do. Me, I think you usually need to pay good money to get good info, even when you do it right.

Added 3p: The CrowdMed founder replies in the comments; I respond also.

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Machiavelli On Listening

In 1505, Machiavelli advised leaders to let a few trusted advisors tell them the truth when answering specific questions in private, but to never let anyone advise them in public, especially at those people’s own initiative:

There is no other way of guarding oneself from flatterers except letting men understand that to tell you the truth does not offend you; but when every one may tell you the truth, respect for you abates.

Therefore a wise prince ought to hold a third course by choosing the wise men in his state, and giving to them only the liberty of speaking the truth to him, and then only of those things of which he inquires, and of none others; but he ought to question them upon everything, and listen to their opinions, and afterwards form his own conclusions. With these councillors, separately and collectively, he ought to carry himself in such a way that each of them should know that, the more freely he shall speak, the more he shall be preferred; outside of these, he should listen to no one, pursue the thing resolved on, and be steadfast in his resolutions. He who does otherwise is either overthrown by flatterers, or is so often changed by varying opinions that he falls into contempt. (more)

Machiavelli was very smart and insightful on such subjects. So I’m reluctant to disagree with him. But his advice seems to tell leaders never to listen to prediction markets, and I’m not quite ready to give up on that idea yet. So what I want now is to better understand Machiavelli’s advice: why exactly should leaders not let themselves be seen as listening to public advice others initiate?

Some possible theories:

  1. Advice givers are higher status that advice receivers, and leaders must seek maximal status.
  2. There are standard embarrassing truths and audiences take one’s ability to keep people from voicing them as a costly signal of dominance.
  3. If people can influence you by telling you things, they will spend too much effort trying to do so, at the expense of other useful activities.
  4. What else?
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Hail Scott Siskind

Scott Siskind gets it:

A democracy provides a Schelling point, … an option which might or might not be the best, but which is not too bad and which everyone agrees on in order to stop fighting. … In the six hundred fifty years between the Norman Conquest and the neutering of the English monarchy, Wikipedia lists about twenty revolts and civil wars. … In the three hundred years since the neutering of the English monarchy and the switch to a more Parliamentary system, there have been exactly zero. … Democracy doesn’t always perform optimally, but it always performs fairly, … and that is enough to prevent people from starting civil wars.

Academia is different. Its state resembles that of pre-democratic governments, when anyone could choose a side, claim it was legitimate, and then get into endless protracted fights with the partisans of other sides. If you believe ObamaCare will destroy the economy, you will have no trouble finding a prestigious academic who agrees with you. Then all you need to do is accuse the other academics of bias, or cherry-picking, or using the wrong statistical test, or any of the other ways to discredit scientists you don’t like. …

A democratic vote among the scientific establishment is insufficient to settle these topics. The most important problem is that it gives massive power to the people who determine who gets to be part of “the scientific establishment”. … So not having any Schelling point – being hopelessly confused about the legitimacy of academic ideas – sucks. But a straight democratic vote of academics would also suck and be potentially unfair.

Prediction markets avoid these problems. There is no question of who the experts are: anyone can invest in a prediction market. There’s no question of special interests taking it over; this just distributes free money to more honest investors. Not only do they escape real bias, but more importantly they escape perceived bias. It is breathtakingly beautiful how impossible it is to rail that a prediction market is the tool of the liberal media or whatever. …

Nate Silver might do better than a prediction market, I don’t know. But Nate Silver is not a Schelling point. Nobody chose him as Official Statistics Guy via a fair process. And if someone objected to his beliefs, they could accuse him of bias and he would have no recourse until it was too late. If a prediction market is almost as good as Nate, and it is also unbiased and impossible to accuse of bias, we have our Schelling point. …

Just as democracy made it harder to fight over leadership, prediction markets make it harder to fight over beliefs. We can still fight over values, of course – if you hate teenagers having sex, and I don’t care about it, we can debate that all day long. But if we want to know whether a certain law will raise the pregnancy rate, there will be only one correct answer, and it will only be a mouse-click away.

I think this would have more positive effects than anyone anticipates. If people took it seriously, not only would the gun control debate be over in an hour, but it would end on the objectively right side, whichever side that was. If single-payer would be better than Obamacare, we could implement single-payer and anyone who tried to make up horror stories about how it would destroy health care would be laughed out of the room. And once these issues have gone away, maybe we can reach the point where half the country stops hating the other half because of disagreements which are largely over factual issues. (more; HT Stephen Bachelor)

By the way, my futarchy paper will appear this year in Journal of Political Philosophy. This is very close to the final version.

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Grounded Visionaries

I recently got to spend ten minutes explaining prediction markets to a (nice, smart) software billionaire. He had already been exposed to the basic idea, but from me he came to understand the larger potential for markets on decision consequences. He said they could be useful inside for-profit firms, like hedge funds. I suggested that software firms could also benefit from better estimates on user satisfaction, rates of bugs, and making deadlines. He quickly countered that software visionaries, in charge of implementing an unusual vision, shouldn’t be held to the conventional wisdom of a crowd.

The conversation moved before I could reply that prediction markets aren’t about crowds or conventional wisdom, and that even unconventional concepts can gain from grounded estimates on their implementation details. Alas this seems another example of the usual excuse making; even those who see big gains from prediction markets elsewhere tend to find excuses for why such gains are not to be found in their organization.

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At Loooooong Last

In 2001, DARPA started funding my Policy Analysis Market:

We planned to cover eight nations. For each nation in each quarter of a year, we planned to have traders predict its military activity, political instability, economic growth, US military activity, and US financial involvement. In addition traders would predict US GDP, world trade, … and a few to-be-determined miscellaneous items. This would require a hundred or so base markets. Most important, we wanted to let our traders predict combinations of these, such has how moving US troops out of Saudi Arabia would affect political stability there, how that would affect stability in neighboring nations, and how all that might change oil prices. …

[We] prepared for and ran lab experiments comparing two new combinatorial trading mechanisms with traditional mechanism. These experiments, where six traders set 255 independent prices in five minutes, found that a combinatorial market maker was the most accurate. Phase II was mostly being spent implementing a scaleable production version of this market maker.

Alas, disaster hit a month before we were to start live testing, and five months before we were to start public trading:

The media storm hit on July 28, 2003, when two senators (falsely) complained that we were planning to let people bet on individual terrorist attacks. The next morning the secretary of defense announced that FutureMAP was cancelled.

While the press on that event did help jump-start today’s prediction market industry, I have always regretted that the storm didn’t wait until we had a demo to show, of combinatorial markets on Mideast geopolitical events. This is why if felt so satisfying to announce Friday:

We are live! If you register at DAGGRE.org, you can join hundreds of others who browse and edit estimates on over 100 questions intended to be of interest to the US intelligence community. … You can also make assumptions, and then browse and edit as before.

Over nine years later, you can finally see the demo I wanted everyone to see in ’03! Of course this is only a play money market, and it isn’t open to everyone. We don’t allow foreigners, you can’t lose any money in it, and we only pay for activity, not accuracy. So there’s less reason for you to believe these prices as event estimates. But still, you can see combinatorial prediction markets in action. At long looooong last!

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Combo Markets, Live!

Prediction markets let people bet on events of interest. This aggregates info on those events into market prices. So if you want to know the chance of an event, consider sponsoring a prediction market on it, and then watching the price. And if you want to persuade observers of a chance, consider betting in such a market, to change the price.

Sadly, the CFTC is cracking down on Intrade, making it harder to sponsor or use such markets. I can’t do much about that. But I can help improve the tech. For example, combinatorial prediction markets can let users bet on the chances of many unforeseen combinations of events. This can aggregate a lot more info on those events, as it lets users spontaneously express their opinions on a lot more topics.

Others have built combo markets. For example, WiseQ let people bet on certain combinations of events on the last election, such as whether the same party would win in two particular states. But those other markets allow inconsistencies, often big, between estimates on different questions. Our DAGGRE markets, in contrast, maintain exact globally consistency (up to machine precision) over a large combinatorial space of estimates, And they are live, today, for you to see and use at DAGGRE.org!

Let me explain. As I said five months ago:

Within a few months we will field an edit-based system where users can browse current answer estimates, and for each estimate can:

  • Edit the value. After you change an estimate to a new value, estimates that users see on all questions are Bayes-rule updates from that new value.
  • Assume a value. After you assume a value for this estimate, all estimates you see on all questions are conditional on this assumption. (more)

I said that we need to compute current estimates, edit limits, and long vs. short relative positions, and that we can now do these exactly (well, up to machine precision) with globally consistent estimates, in the case of a low-treewidth Markov network. Other approaches to combo markets allow inconsistencies, often big, between estimates on different questions. Large inconsistencies can hinder information aggregation, and risk large financial losses to clever traders who find them.

OK five months is not “few”, but today I can announce: we are live! If you register at DAGGRE.org, you can join hundreds of others who browse and edit estimates on over 100 questions intended to be of interest to the US intelligence community. We hand out $3000 a month to users in proportion to their activity (as 60 50$ Amazon gift cards; details here).

Actually, you could have done all that a year ago. But today you can also make assumptions, and then browse and edit as before. For example, we ask if foreign armies will fight in Syria soon, and also if Syria will use chem or bio weapons soon. So if you think that Syria using chem weapons would increase the chance of a foreign fight, you can assume that chem weapon use, and then edit the foreign fighter chance accordingly.

Actually you could have done that a month ago. But the system was slow and buggy; it is now much better. Which is why I’m announcing now. Yes, we still limit which estimates can be edited for any given set of assumptions; we have to do that to keep a low treewidth network of relations. But compared to ordinary prediction markets, this is a major advance in functionality. And we’ll keep working to relax these limitations.

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