Category Archives: prediction markets

CFP: Auctions, Market Mechanisms, and their Applications

From Peter Coles:

There is [less than] one week left to submit papers to AMMA, [The Second Conference on Auctions, Market Mechanisms and Their Applications], a market design conference that will be held in NYC this August. The conference brings together economists, computer scientists and practitioners who are interested in the use of market mechanisms to solve problems.

The best way to decide whether to submit to a conference you haven’t heard of is to look at the organizers and program committee. In this case, they’re superb.

It’s Arab Spring, but is it Prediction Market Winter?

Is the growing prediction market industry graveyard an omen?

It’s hard to ignore the accumulating bodies, including, may they rest in peace, PPX, Hubdub, Protrade, Tradesports, Newsfutures, Hedgestreet, Yoonew, TheTicketReserve, FirstDibz, BettorFan, ipreo, Tech Buzz Game, The WSX, Storage Markets, FTPredict, real HSX, BizPredict [1], CasualObserver.net, Cenimar, Alexadex [2], Askmarkets, Truth Markets, BetBubble, Betocracy, CrowdIQ, Media Mammon, Owise, RIMDEX, Trendio [3], TwoCrowds, BBC celebdaq/sportdaq, Betfair Predicts, chrisfmasse.com [4], and more.

Is this churn rate normal for startups in general, even healthy? Is it a sign of PM’s place in the trough of the hype cycle? Is the current climate an opportunity for those left standing or someone new? Or does it simply suggest that prediction market proponents like me have lost?

A number of media-PM partnerships which on their face seem perfectly natural are history: USA Today+Newsfutures, Popular Science+HSX, Business 2.0+ConsensusPoint, Financial Times+Intrade, Techcrunch+Askmarkets [5], ABC7+Inkling [6], and CFO Magazine+Crowdcast.

At least two former PM companies found success only after switching gears: Protrade became Citizen Sports before being acquired by Yahoo! and Nigel euthanized Hubdub to focus on FanDuel. Cocision, launched just last fall, has already abandoned its PM roots in favor of breezy Q&A and voting.

Usable Marketeer Alex Kirtland nails exactly why all the “predict Wall Street” games may be fun but aren’t likely to be predictive. Research papers, including my own, report that the accuracy advantage of prediction markets, while real, may often be small compared to statistical models or polls.

Intrade, one of the most cited and well studied PMs, is trying hard with a radical remake that looks great and a new fee structure that’s likely to improve low-probability predictions. I don’t have any inside knowledge but the company and the exchange don’t seem especially strong; I even spotted some bugs in their exchange rules. The venerable Iowa Electronic Market and Foresight Exchange that, together with Robin, started it all, look, well, venerable. Betfair is still a powerhouse and soared in its IPO just last fall, but is perhaps showing signs of age as personnel turn over and the product remains decidedly 1.0.

A few startups like Crowdcast, MediaPredict, smarkets, betable, socialico/PremierX, and InklingMarkets are nimble and promising, but none have hit home runs yet. The SimExchange is well designed and chugging along. Bet2Give [7] and CentSports are both fascinating concepts and still alive, two of the most intriguing real-money markets. Others like ExtZy, RealityMarkets and PublicGyan are hanging on. New entrants like Prediculous, Predictalot, Predictopus, 4cast, beansight, I Called It, IBET, Prediction Book, HuffPo’s Predict the News, Slate’s Lean/Lock, Ultrinsic, Knew The News, Cantor Gaming’s Oracle [8], and the MNI Forecast Competition (Lumenogic) are still coming up, though at an admittedly slower pace than four years ago.

Update 2011/5/10: Crowdpark, a German company with an office in San Francisco, launched in English last December with a web game and an impressive, well-designed Facebook game that’s already attracted 500,000 monthly active users, the 11th fastest growing Facebook app in April. They have an interesting “patent pending” automated market maker that I can’t find any details about (yet).

One PM mailing list is of questionable transparency and another is often silent. The Prediction Market Industry Association is inactive.

The final post on Newfutures Blog in 2009 declares that “resistance is futile”. But is it the world’s resistance of PMs, or PMs resistance of irrelevance, that is futile?

Despite the negative tone of this post, I believe it’s the former. The prediction market spring will come. Here’s why. Prediction markets offer:

  1. Accountability
  2. Meritocracy
  3. A marketplace to reward information release
  4. Real-time updates
  5. Accuracy
  6. Increasing ease of use, as the technology matures and diffuses
  7. Self funding

No other prediction technology offers the same. There’s a great opportunity here for the companies that have squirreled away enough nuts to survive the winter.

P.S. Also read Paul Hewitt’s Prediction Market Prospects 2010.


Footnotes:

[1] In 2006, the teaser prediction for BizPredict was “Do you know when MySpace’s traffic will surpass Yahoo’s?”.

[2] Techcrunch declared Alexadex “the web 2.0 stock market”, back when Techcrunch encouraged Diggs

[3] I like Trendio’s post-mortem:

..Trendio rapidly became popular and attracted massive traffic from all over the world, as well as attention from major newspapers, TV-channels and blogs. To develop Trendio as a large-scale web property and an income-generating business would however have required to dedicate time and resources that I wasn’t able to provide.

I still believe there is a massive potential for prediction markets, both as games and for their predictive power…

[4] A truly sad loss, and not just because of the 2005 awards. Someone should archive the archive to be sure this gem, as information-rich as it was verbose and disorganized, survives. Hang in there Midas Oracle!

[5] Ironically, upon launch of Askmarkets in 2008 Techcrunch asked “who’s going to the deadpool?”

[6] Technically not dead, but seems neglected.

[7] We independently considered an idea similar to bet2give at Yahoo! in 2007 but never pursued it.

[8] Cantor Gaming’s odd-setting mechanism seems effectively like an automated market maker with intelligent prior.

Predictopus in the Times of India

Today, Yahoo! placed two full-page ads on the back cover of the Times of India, the largest English-language daily in the world, to promote Yahoo! Cricket, a site that reaches 13.4 percent of everyone online in India and serves as the official website of the ICC Cricket World Cup.

Take a look at the middle right of the second page: it says “Play exciting games and win big” and features… Predictopus! That’s the Indian spinoff of Predictalot, the combinatorial prediction game I helped invent.

Page 1 of two full-page Yahoo! Cricket ads in the Times of India, p. 31, 2011/03/30Predictopus on Page 2 of two full-page Yahoo! Cricket ads in the Times of India, p. 32, 2011/03/30

Predictopus has nearly 70,000 users and counting, and this ad certainly won’t hurt.

Yahoo!!!

BTW, I grabbed these images from an amazing site called Press Display, which I discovered via the New York Public Library.

Times of India Mumbai edition
30 Mar 2011

Times of India Mumbai edition
30 Mar 2011

Also, congrats India, and thanks! I nearly doubled my virtual bet with the victory:

Dave's Predictopus prediction: India will advance further than Pakistan, 3/2011

We’re baaack: Predictalot is here for March Madness 2011

March Madness is upon us and Predictalot, the crazy game that I and others at Yahoo! Labs invented, is live again and taking your (virtual) bets. Filling out brackets is so 2009. On Predictalot, you can compose your own wild prediction, like there will be exactly seven upsets in the opening round, or neither Duke, Kentucky, Kansas, nor Pittsburgh will make the Final Four. You’ll want your laptop out and ready as you watch the games — you can buy and sell your predictions anytime, like stocks, as the on-court action moves for or against you.

Predictalot v0.3 is easier to play. We whittled down the ‘Make Prediction’ process from four steps to just two. Even if you don’t want to wager, with one click come check out the projected odds of nearly any crazy eventuality you can dream up.

Please connect to facebook and/or twitter to share your prediction prowess with your friends and followers. You’ll earn bonus points and my eternal gratitude.

The odds start off at our own prior estimate based on seeds and (new this year) the current scores of ongoing games, but ultimately settle to values set by “the crowd” — that means you — as predictions are bought and sold.

Yahoo! Labs Predictalot version 0.3 overview tab screenshot

For the math geeks, Predictalot is a combinatorial prediction market with over 9 quintillion outcomes. Prices are computed using an importance sampling approximation of a #P-hard problem.

What kind of information can we collect that a standard prediction market cannot? A standard market will say that Texas A&M is unlikely to win the tournament. Our market can say more. Yes, A&M is unlikely to reach the Final Four and even more unlikely to win apriori, but given that they somehow make it to the semifinals in Houston, less than a two hour drive from A&M’s campus, their relative odds may increase due to a home court advantage.

Here’s another advantage of the combinatorial setup. A standard bookmaker would never dare to offer the same millions of bets as Predictalot — they would face nearly unlimited possible losses because, by tradition, each bet is managed independently. By combining every bet into a single unified marketplace, we are able to limit the worst-case (virtual) loss of our market maker to a known fixed constant.

International Conference on Prediction and Information Markets: Who’s going?

Abstracts are due today for the Third International Conference on Prediction and Information Markets. It will be held in Nottingham, England April 3-5 along with two related conferences: the International Conference on Gambling Studies and the International Conference on Money, Investment and Risk. (Abstracts also due today for both of these conferences.)

I’ve been considering submitting some thing(s): I’m curious if anyone else is planning to submit or attend?

Date: 3 – 5 April 2011
Event: Third International Conference on Prediction and Information Markets
Location: Nottingham Conference Centre
Organiser: Nottingham Business School

Details:

The Third International Conference on Prediction and Information Markets will be held in association with Economic Issues and the Journal of Prediction Markets.

Prediction / information markets offer a way of harnessing the wisdom of crowds. They have been used to aggregate information in order to provide forecasts of a wide range of events…

In recent years, a number of companies have employed these markets as a means of aggregating the information dispersed widely among their employees and customers…

Call for papers and presentations
Please send an abstract (maximum of 200 words) to Professor Leighton Vaughan Williams by email, by the closing date for receipt of abstracts of Monday 21 February 2011. Confirmation of receipt of abstracts will be sent within a maximum of five working days.

Predictalot goes East: Introducing Predictopus for the ICC Cricket World Cup

Yahoo! India Predictopus logo

I’m thrilled to report that Predictalot had an Indian makeover, launching as Predictopus* for the ICC Cricket World Cup. The Yahoo! India team did an incredible job, leveraging the idea and some of the code base of Predictalot, yet making it their own. Predictopus is not a YAP — it lives right on the Yahoo! Cricket website, the official homepage for the ICC Cricket World Cup. They’re also giving away Rs 10 lakhs — or about $22,000 if my calculations are correct — in prizes. Everything is bigger in India, including the crowds and the wisdom thereof. It will be great to see the game played out on a scale that dwarfs our college basketball silliness in the US.

The Y! India team reused some of the backend code but redid the frontend almost entirely. To adapt the game to cricket, among other chores, we had to modify our simulation code to estimate the starting probabilities that any team would win against any other team, even in the middle of a game. (How likely is it for India to come back at home from down 100 runs with 10 overs left and 5 wickets lost? About 25%, we think.) These starting probabilities are then refined further by the game-playing crowds.

It’s great to see an experiment from Labs grow into a full-fledged product run by a real product team in Yahoo!, a prime example of technology transfer at its best. In the meantime, we (Labs) are still gunning for a relaunch of Predictalot itself for March Madness 2011, the second year in a row. Stay tuned.

2011/02/24 Update: An eye-catching India-wide ad campaign for predictopus is live, including homepage, finance, movies, OMG, answers, mail, everywhere! Oh, and one of the prizes is a Hyundai.

predictopus ad on Yahoo! India homepage 2011/02/24


* Yes, that’s a reference to legendary Paul the Octopus, RIP.

wise.gov: NSF and IARPA funding for collective intelligence

The US National Science Foundation’s Small Business Innovation Research program provides grants to to small businesses to fund “state-of-the-art, high-risk, high-potential innovation research proposals”.

In their current call for proposals, they explicitly ask for “I2b. Tools for facilitating collective intelligence”.

These are grants of up to US$150,000 with opportunity for more later I believe. The deadline is December 3, 2010! Good luck and (not so) happy Thanksgiving to anyone working on one of these proposals. I’m glad to help if I can.


The deadline for another US government program has passed, but should yield interesting results and may lead to future opportunities. In August, the Intelligence Advanced Research Projects Activity (IARPA, the intelligence community’s DARPA), which “invests in high-risk/high-payoff research programs” in military intelligence, solicited proposals for Aggregative Contingent Estimation, or what might be called wisdom-of-crowds methods for prediction:

The ACE Program seeks technical innovations in the following areas:

  • Efficient elicitation of probabilistic judgments, including conditional probabilities for contingent events.
  • Mathematical aggregation of judgments by many individuals, based on factors that may include past performance, expertise, cognitive style, metaknowledge, and other attributes predictive of accuracy.
  • Effective representation of aggregated probabilistic forecasts and their distributions.

The full announcement is clear, detailed, and well thought out. I was impressed with the solicitors’ grasp of research in the field, an impression no doubt bolstered by the fact that some of my own papers are cited 😉 . Huge hat tip to Dan Goldstein for collating these excerpts:

The accuracy of two such methods, unweighted linear opinion pools and conventional prediction markets, has proven difficult to beat across a variety of domains.2 However, recent research suggests that it is possible to outperform these methods by using data about forecasters to weight their judgments. Some methods that have shown promise include weighting forecasters’ judgments by their level of risk aversion, cognitive style, variance in judgment, past performance, and predictions of other forecasters’ knowledge.3 Other data about forecasters may be predictive of aggregate accuracy, such as their education, experience, and cognitive diversity. To date, however, no research has optimized aggregation methods using detailed data about large numbers of forecasters and their judgments. In addition, little research has tested methods for generating conditional forecasts.

2 See, e.g., Tetlock PE, Expert Political Judgment (Princeton, NJ: Princeton University Press, 2005), 164-88; Armstrong JS, “Combining Forecasts,” in JS Armstrong, ed., Principles of Forecasting (Norwell, MA: Kluwer, 2001), 417-39; Arrow KJ, et al., “The Promise of Prediction Markets,” Science 2008; 320: 877-8; Chen Y, et al., “Information Markets Vs. Opinion Pools: An Empirical Comparison,” Proceedings of the 6th ACM Conference on Electronic Commerce, Vancouver BC, Canada, 2005.

3 See, e.g., Dani V, et al., “An empirical comparison of algorithms for aggregating expert predictions,” Proc. 22nd Conference on Uncertainty in Artificial Intelligence, UAI, 2006; Cooke RM, ElSaadany S, Huang X, “On the performance of social network and likelihood-based expert weighting schemes,” Reliability Engineering and System Safety 2008; 93:745-756; Ranjan R, Gneiting T, “Combining probability forecasts,” Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2010; 72(1): 71-91.

[Examples:]

  • Will the incumbent party win the next presidential election in Country X?
  • Will the incumbent party win the next presidential election in Country X?
  • When will Country X hold its next parliamentary elections?
  • How many cell phones will be in use globally by 12/31/11?
  • By how much will the GDP of Country X increase from 1/1/11 to 12/31/11?
  • Will Country X default on its sovereign debt in 2011?
  • If Country X defaults on its sovereign debt in 2011, what will be the growth rate in the Eurozone in 2012?

Elicitation – Advances Sought
The ACE Program seeks methods to elicit judgments from individual forecasters on:

  • Whether an event will or will not occur
  • When an event will occur
  • The magnitude of an event
  • All of the above, conditioned on another set of events or actions
  • The confidence or likelihood a forecaster assigns to his or her judgment
  • The forecaster’s rationale for his or her judgment, as well as links to background information or evidence, expressed in no more than a couple of lines of text
  • The forecaster’s updated judgments and rationale

The elicitation methods should allow prioritization of elicitations, continuous updating of forecaster judgments and rationales, and asynchronous elicitation of judgments from more than 1,000 geographically-dispersed forecasters. While aggregation methods, detailed below, should be capable of generating probabilities, the judgments elicited from forecasters can but need not include probabilities.

Challenges include:

  • Some forecasters will be unaccustomed to providing probabilistic judgments
  • There has been virtually no research on methods to elicit conditional forecasts
  • Elicitation should require a minimum of time and effort from forecasters; elicitation should require no more than a few minutes per elicitation per forecaster
  • Training time for forecasters will be limited, and all training must be delivered within the software
  • Rewards for participation, accuracy, and reasoning must be non-monetary and of negligible face value (e.g., certificates, medals, pins)

Book of Odds is serious fun

In the Book of Odds, you can find everything from the odds an astronaut is divorced (1 in 15.54) to the odds of dying in a freak vending machine accident (1 in 112,000,000).

Book of Odds is, in their own words, “the missing dictionary, one filled not with words, but with numbers – the odds of everyday life.”

I use their words because, frankly I can’t say it better. The creators are serious wordsmiths. Their name itself is no exception. “Book of Odds” strikes the perfect chord: memorable and descriptive with a balance of authority and levity. On the site you can find plenty of amusing odds about sex, sports, and death, but also odds about health and life that make you think, as you compare the relative odds of various outcomes. Serious yet fun, in the grand tradition of the web.

I love their mission statement. They seek both to change the world — by establishing a reliable, trustworthy, and enduring new reference source — and to improve the world — by educating the public about probability, uncertainty, and decision making.

By “odds”, they do not mean predictions.

Book of Odds is not in the business of predicting the future. We are far too humble for that…

Odds Statements are based on recorded past occurrences among a large group of people. They do not pretend to describe the specific risk to a particular individual, and as such cannot be used to make personal predictions.

In other words, they report how often some property occurs among a group of people, for example the fraction all deaths caused by vending machines, not how likely you, or anyone in particular, are to die at the hands of a vending machine. Presumably if you don’t grow enraged at uncooperative vending machines or shake them wildly, you’re safer than the 1 in 112,000,000 stated odds. A less ambiguous (but clunky) name for the site would be “Book of Frequencies”.

Sometimes the site’s original articles are careful about this distinction between frequencies and predictions but other times less so. For example, this article says that your odds of becoming the next American Idol are 1 in 103,000. But of course the raw frequency (1/number-of-contestants) isn’t the right measure: your true odds depend on whether you can sing.

Their statement of What Book of Odds isn’t is refreshing:

Book of Odds is not a search-engine, decision-engine, knowledge-engine, or any other kind of engine…so please don’t compare us to Google™. We did consider the term “probability engine” for about 25 seconds, before coming to our senses…

Book of Odds is never finished. Every day new questions are asked that we cannot yet answer…

A major question is whether consumers want frequencies, or if they want predictions. If I had to guess, I’d (predictably) say predictions — witness Nate Silver and Paul the Octopus. (I’ve mused about using *.oddhead.com to aggregate predictions from around the web.)

The site seems in need of some SEO. The odds landing pages, like this one, don’t seem to be comprehensively indexed in Bing or Google. I believe this is because there is no natural way for users (and thus spiders) to browse (crawl) them. (Is this is a conscious choice to protect their data? I don’t think so: the landing pages have great SEO-friendly URLs and titles.) The problem is exacerbated because Book of Odds own custom search is respectable but, inevitably, weaker than what we’ve become accustomed to from the major search engines.

Book of Odds launched in 2009 with a group of talented and well pedigreed founders and a surprisingly large staff. They’ve made impressive strides since, adding polls, a Yahoo! Application, an iGoogle gadget, regular original content, and a cool visual browser that, like all visual browsers, is fun but not terribly useful. They’ve won a number of awards already, including “most likely company to be a household name in five years”. That’s a low-frequency event, though Book of Odds may beat the odds. Or have some serious fun trying.

Three Crowd-ed events this fall

Research and Analysis of Tail Phenomenon Symposium

August 20, 2010, Sunnyvale, CA

The last decade has witnessed the emergence of enormous scale artifacts resulting from the independent action of hundreds of millions of people; for example, web repositories, social networks, mobile communication patterns, and consumption in “limitless” stores… the first Research and Analysis of Tail phenomena Symposium (RATS)… will explore the different computational, statistical, and modeling problems related to tail phenomena… We are particularly encouraging summer interns in any of the Bay Area research centers to join us in the event.
We will start with a video welcome by Chris Anderson (Wired), followed by a series of invited talks by Michael Mitzenmacher (Harvard), Aaron Clauset (Univ. of Colorado), Neel Sundaresan (eBay), Sharad Goel (Yahoo! Research, NY) and Michael Schwarz (Yahoo! Research, CA).

We invite proposals for short (20 minute) talks from students and researchers working in the area.

CrowdCof2010: 1st Annual Conference on the Future of Distributed Work

October 4, 2010, San Francisco, CA

Were you crowdsourcing before it was cool? We want to hear about your projects.

We are inviting submissions on all topics regarding crowdsourcing, including:

  • Past, present, and future of crowdsourcing
  • Quality assurance and metrics
  • Social and economic implications of crowdsourcing
  • Task design/Worker incentives
  • Innovative projects, experiments, and applications
  • Submission Guidelines

Deadline: Sept. 1

CrowdConf will bring together researchers, technologists, outsourcing entrepreneurs, legal scholars, and artists for the first time to discuss how crowdsourcing is transforming human computation and the future of work.

Confirmed Speakers:
Sharon Chirella: Vice President, Amazon Mechanical Turk
Tim Ferriss : Author, The 4-Hour Work Week
David Alan Grier: Author, When Computers Were Human
Barney Pell: Partner, Search Strategist, and Evangelist, Microsoft
Maynard Webb: CEO, LiveOps
Jonathan Zittrain: Professor of Law and Computer Science, Harvard

Computational Social Science and the Wisdom of Crowds Workshop at NIPS 2010

December 10th or 11th, 2010, Whistler, Canada

We welcome contributions on theoretical models, empirical work, and everything in between, including but not limited to:

  • Automatic aggregation of opinions or knowledge
  • Prediction markets / information markets
  • Incentives in social computation (e.g., games with a purpose)
  • Studies of events and trends (e.g., in politics)
  • Analysis of and experiments on distributed collaboration and consensus-building, including crowdsourcing (e.g., Mechanical Turk) and peer-production systems (e.g., Wikipedia and Yahoo! Answers)
  • Group dynamics and decision-making
  • Modeling network interaction content (e.g., text analysis of blog posts, tweets, emails, chats, etc.)
  • Social networks

[Covers] computational social science… [and] social computing… with an emphasis on the role of
machine learning…

Deadline for submissions: Friday October 8, 2010

Where is the betting market for P=NP when you need it?

HP research scientist Vinay Deolalikar has constructed the most credible proof yet of the most important open question in computer science. If his proof is validated (and there are extremely confident skeptics as you’ll see) he proved that P≠NP, or loosely speaking that some of the most widespread computational problems — everything from finding a good layout of circuits on a chip to solving Sudoku puzzles to computing LMSR prices in a combinatorial market — cannot be solved efficiently. Most computer scientists believe that P≠NP, but after decades of some of the smartest people in the world trying, and despite the promise of worldwide accolades and a cool $1 million from the Clay Mathematics Institute, no one has been able to prove it, until possibly now.

Scott Aaronson is a skeptic, to say the least. He made an amazing public bet to demonstrate his confidence. He pledged that if Deolalikar wins the $1 million prize, Aaronson will top it off with $200,000 of own money. Even more amazing: Aaronson made the bet without even reading the proof. [Update: I should have said “without reading the proof in detail”: see comments] (Perhaps more amazing still: a PC World journalist characterized Aaronson’s stance as “noncommittal” without a drip of sarcasm.) [Hat tip to Dan Reeves.]

As Aaronson explains:

The point is this: I really, really doubt that Deolalikar’s proof will stand. And while I haven’t studied his long, interesting paper and pinpointed the irreparable flaw… I have a way of stating my prediction that no reasonable person could hold against me: I’ve literally bet my house on it.

Aaronson is effectively offering infinite odds [Update: actually more like 2000/1 odds: see comments] that the question “P=NP?” will not be resolved in the near future. Kevin McCurley and Ron Fagin made a different (conditional) bet: Fagin offered 5/1 odds (at much lower stakes) that if the question is resolved in 2010, the answer will be P≠NP. Bill Gasarch says that he, like Aaronson, would bet that the proof is wrong… if only he were a betting man. Richard Lipton recounts a discussion about the odds of P=NP with Ken Steiglitz.

But beyond a few one-off bets and declarations, where is the central market where I can bet on P=NP? I don’t even necessarily want in on the action, I just want the odds. (Really!)

My first thought was the Foresight Exchange. It does list one related contract — Good 3SAT Algorithm by 2020 — which should presumably go to zero if Deolalikar’s proof is correct. It hasn’t budged much, consistent with skepticism (or with apathy). My second thought was the PopSci Predictions Exchange (PPX), though sadly it has retired. InklingMarkets has a poll about whether P=NP will be resolved before the other Clay Institute prize questions, but not about how it will be resolved or the odds of it happening. (The poll is one of several markets sponsored by the Woodrow Wilson Center’s Science and Technology Innovation Program — hat tip to Vince Conitzer.) I don’t see anything at longbets, and anyway longbets doesn’t provide odds despite it’s name.

In 1990 Robin Hanson provocatively asked: Could gambling save science?. That question and his thoughtful answers inspired a number of people, including me, to study prediction markets. Indeed, the Foresight Exchange was built largely in his image. P=NP seems one of the most natural claims for any scitech prediction market.

All these years later, when I really need my fix, I can’t seem to get it!


2010/08/14 Update: Smarkets comes the closest: they have real-money betting on whether P=NP will be resolved before the other Clay Institute prize questions. They report a 53% chance as of 2010/08/14 (for the record, I would bet against that). What’s missing is when the award might happen and how the question might be resolved, P=NP or P≠NP. I also don’t see a graph to check whether Deolalikar’s proof had any effect.

If it wasn’t clear in my original post, I found Aaronson’s bet incredibly useful and I am thrilled he did it. I believe he should be commended: his bet was exactly what more scientists should do. Scientists should express their opinion, and betting is a clear, credible, and quantitative way to express it. It would be as shame if some of the negative reactions caused him or others not to make similar bets in the future.

I just wish there were a central place to make bets on scientific claims and follow the odds in the vision of Robin Hanson, rather than every scientist having to declare their bet on their own individual blogs.