The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies

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Via Emile Servan-Schreiber (who claims it&#8217-s the supportive evidence for The Wisdom Of Crowds)

Has somebody read that book?

Previous blog posts by Chris F. Masse:

  • The Most Surprising Piece Of News I’ve Heard Today
  • My first prediction market plugin for WordPress
  • Self-Serving Prediction Market Of The Day — Unlawful Internet Gambling Enforcement Act of 2006
  • Prediction markets tend to be so illiquid, though, that mere activity looks like volatility.
  • Decision Markets and Futarchy are solutions in desperate search for a problem to solve and for their early adopters… and that may stay that way well after Robin Hanson’s head gets cryogenized.

La Sagesse Des Foules

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Good news this week for French-speaking Midas Oracle readers: The French version of Surowiecki&#8217-s book has at last been released. Here&#8217-s wishing it the success it deserves! Early reviews are very positive: One reviewer writes poetically about &#8220-crowds so wise that they become revolutionary.&#8221- Cute, and telling: As the country celebrates the student uprisings of April-May 1968, when Mao&#8217-s little red book was a must read, Surowiecki&#8217-s manifesto is indeed perfectly timed to launch a new cultural revolution.

La Sagesse des Foules

What should be learned from the Overcoming Bias fiasco?

#1. That mistake could happen to any blogger (including moi), as we are all keen to re-publish and link to other people&#8217-s writings without checking and researching the foundations of their rationale.

#2. James Surowiecki taught a lesson in journalism to Robin Hanson.

#3. Robin Hanson should have published James Surowiecki&#8217-s letters to the editor as a new blog post &#8212-in addition to posting addenda to the original, flawed, misleading blog post.

#4. James Surowiecki has confirmed that he has the capacity and the legitimity to lead the field of prediction markets. [Of course, Robin Hanson is capable of mutant abstractions (MSR) whereas James Surowiecki is not.]

That is all, folks. Read the previous blog posts by Chris. F. Masse:

James Surowieckis The Wisdom Of Crowds… still stands.

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James Surowiecki&#8217-s 4 comments at Overcoming Bias (in October 2007), responding to accusations that he got it all wrong about Francis Galton:


James Surowiecki&#8217-s 1st comment:

&#8220-Galton did not even bother to calculate a mean, as he saw his data was clearly not normally distributed. He used the median (of 1207), which was much further off than the mean, but by modern standards clearly the better estimator. It was Karl Pearson in 1924 who calculated the mean.&#8221-

Robin [Hanson], before repeating falsehoods, you might want to go back to the original sources &#8212- or, in this case, to the footnotes to my book. Galton did, in fact, calculate the mean, long before Karl Pearson did. Galton&#8217-s calculation appeared in Nature, Vol. 35, No. 1952 (3/28/07), in a response to letters regarding his original article. One of the correspondents had gone ahead and calculated a mean from the data that Galton had provided in his original piece, and had come up with the number 1196. Galton writes, &#8220-he makes it [the mean] 1196 lb. . . . whereas it should have been 1197 lb.&#8221-

I find the fact that Levy and Peart wrote an entire article about Galton (and, to a lesser extent, about my use of him), and never went back and checked the original sources is astounding in its own right. (They actually wonder in the paper, &#8220-However the new estimate of location came to be part of Surowieki’s account,&#8221- as if the answer isn&#8217-t listed right there in the footnotes.) What makes it even more astounding, though, is that they&#8217-ve written an entire paper about the diffusion of errors by experts who &#8220-pass along false information (wittingly or unwittingly)&#8221- while passing along false information themselves.

It also seems bizarre that Levy and Peart caution, &#8220-The expectation of being careful seems to substitute for actually being careful,&#8221- and yet they were somehow unable to figure out how to spell &#8220-Surowiecki&#8221- correctly. The article is a parody of itself.

I&#8217-m happy to enter into a discussion of whether the median or the mean should be used in aggregating the wisdom of crowds. But whether Galton himself thought the mean or the median was better was and is irrelevant to the argument of my book. I was interested in the story of the ox-weighing competition because it captures, in a single example, just how powerful group judgments can be. Galton did calculate the mean. It was 1197 lbs., and it was 1 lb. away from the actual weight of the ox. The only &#8220-falsehood&#8221- being perpetrated here are the ones Levy and Peart are putting out there, and the ones that you uncritically reprinted.


James Surowiecki&#8217-s 2nd comment:

Here are the links for the letter from Galton, where he reports the mean:

There&#8217-s no reason for debate here. Levy and Peart say &#8220-Pearson’s retelling of the ox judging tale apparently served as a starting point for the 2004 popular account of the modern economics of information aggregation, James Surowieki’s Wisdom of Crowds.&#8221- It wasn&#8217-t the starting point. The starting point was Galton&#8217-s own experiment, and his own reporting of the mean in &#8220-The Ballot Box.&#8221- Robin writes: &#8220-Galton did not even bother to calculate a mean.&#8221- He did calculate it, and he did report it. This fact shouldn&#8217-t be listed as an &#8220-addendum&#8221- to the original post. The original post should be rewritten completely &#8212- perhaps along the lines of &#8220-Surowiecki and Galton disagree about which estimate is a better representation of group judgment&#8221- rather than &#8220-Author Misreads Expert&#8221- &#8212- or else scrapped.


James Surowiecki&#8217-s 3rd comment:

I appreciate Levy and Peart admitting their mistake. But they seem not to recognize that their mistake undermines the critique that&#8217-s at the center of their paper. Their paper, they write, is about the misconstruing of Galton&#8217-s experiment. &#8220-A key question,&#8221- they write, &#8220-is whether the tale was changed deliberately (falsified) or whether, not knowing the truth, the retold (and different) tale was passed on unwittingly.&#8221- But the account of Galton&#8217-s experiment was not changed deliberately and was not falsified. It was recounted accurately. Levy and Peart want to use my retelling of the Galton story as evidence of how &#8220-experts pass along false information (wittingly or unwittingly) [and] become part of a process by which errors are diffused.&#8221- But there&#8217-s no false information here, and no diffusion of errors, which rather demolishes their thesis. If they really want to write a paper about how &#8220-experts&#8221- pass along false information, they&#8217-d be better off using themselves as Exhibit A, and tell the story of how they managed to publish such incredibly shoddy work and have prominent economists uncritically link to it.


James Surowiecki&#8217-s 4th comment:

To finish, Levy and Peart insist that their really important point still stands, which is that &#8220-When people quote Galton through Surowiecki, they tell Surowiecki&#8217-s tale, not Galton&#8217-s,&#8221- and that this is a problem because Galton&#8217-s thinking is being misrepresented. But as I said earlier, &#8220-The Wisdom of Crowds&#8221- was not intended to be a discussion of Francis Galton&#8217-s opinions on what&#8217-s the best method to capture group judgment, nor, as far as I know, has anyone who&#8217-s &#8220-Surowiecki&#8217-s tale&#8221- used the Galton example since used it to analyze Galton&#8217-s opinions. People aren&#8217-t quoting the Galton story because they&#8217-re interested in what Galton himself thought about the median vs. mean. They&#8217-re quoting it because they&#8217-re interested in the bigger idea, which is that group judgments (and this is true whether you use the median, the mean, or a method like parimutuel markets) are often exceptionally accurate. Levy and Peart have constructed a straw man &#8212- and, in this case, a straw man based on a falsehood &#8212- and then tried to knock it down.

Robin [Hanson] writes: &#8220-it is ironic that Galton made quite an effort to emphasize and prefer the median, in part because the data did not look like a bell curve, while your retelling focuses on him calculating a mean after checking for a bell curve.&#8221- What&#8217-s ironic about this? He did check for a bell curve, and he did calculate the mean. It&#8217-s the data themselves, not Galton&#8217-s interpretation of them, that I was writing about. (If he hadn&#8217-t calculated the mean, I would have happily told the story with the median, since it was also remarkably accurate, and demonstrated the same point about the wisdom of crowds.)

Finally, on the substantive question, Robin (and Levy and Peart) seem to think that because the distribution of guesses wasn&#8217-t normal, that makes using the mean a mistake. But this is precisely what&#8217-s so interesting: if the group is large enough, even if the distribution isn&#8217-t normal, the mean of a group&#8217-s guesses is nonetheless often exceptionally good.

Meet again James Surowiecki, author of The Wisdom Of Crowds.

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James Surowiecki

James Surowiecki, author of The Wisdom Of Crowds

Previously: James Surowiecki’s The Wisdom Of Crowds… still stands.

Previous blog posts by Chris F. Masse:

  • A second look at HedgeStreet’s comment to the CFTC about “event markets”
  • Since YooPick opened their door, Midas Oracle has been getting, daily, 2 or 3 dozens referrals from FaceBook.
  • US presidential hopeful John McCain hates the Midas Oracle bloggers.
  • If you have tried to contact Chris Masse thru the Midas Oracle Contact Form, I’m terribly sorry to inform you that your message was not delivered to the recipient.
  • “Over a ten-year period commencing on January 1, 2008, and ending on December 31, 2017, the S & P 500 will outperform a portfolio of funds of hedge funds, when performance is measured on a basis net of fees, costs and expenses.”
  • Meet professor Thomas W. Malone (on the right), from the MIT’s Center for Collective Intelligence.

HISTORY: Prediction Markets Timeline

For an updated version of this document, see the &#8220-paged&#8221- Prediction Markets Timeline.

CHRONOLOGY &amp- HISTORY: Prediction Markets Timeline

Feel free to post a comment or contact me, and I&#8217-ll correct or add a factoid. Thanks.

#1. Historical Prediction Markets

According to Paul Rhode and Koleman Strumpf, prediction markets almost never got it wrong forecasting the 19 presidential elections that took place from 1868 to 1940. (PDF)

#2. The three Iowa Electronic Markets founders (Robert Forsythe, Forrest Nelson and George Neumann)

&#8220-We ran our first market in 1988. We didn’t have regulatory approval at that point so we were restricted solely to the University of Iowa community. We had under 200 traders and under $5,000.&#8221- &#8211- [Robert Forsythe – PDF file]

– [CFTC’s no-action letter to the IEM – 1992 – PDF file]

– [CFTC’s no-action letter to the IEM – 1993 – PDF file]

#3. Robin Hanson

a) Robin Hanson set up and ran a rudimentary prediction exchange (a market board, PPT file) in January 24, 1989. The outcome to predict was the name of the winner of a Poker party.

b) Until evidence of the contrary, it seems that Robin Hanson was the first to set up and run a corporate prediction exchange &#8212-at Xanadu, Inc., in April 1989. See: A 1990 Corporate Prediction Market + Anonymity is important for employees trading on internal prediction markets.

Robin Hanson: &#8220-I started a market at Xanadu on cold fusion in April 1989. In May 1990, I started a market there on whether their product would be delivered before Deng died.&#8221-

c) Until evidence of the contrary, it seems that Robin Hanson was the first to set up and run a bunch of imagination-based prediction markets. See the Murder Mystery Evening described by Barney Pell &#8212-circa June 8, 1989.

d) Until evidence of the contrary, it seems that Robin Hanson was the first to write a paper on prediction markets created and existing primarily because of the information in their prices (as opposed to markets created primarily for speculation and hedging).

Could Gambling Save Science? &#8211- (Reply to Comments) &#8211- by Robin Hanson &#8211- 1990-07-00
Market-Based Foresight: a Proposal &#8211- by Robin Hanson &#8211- 1990-10-30
Idea Futures: Encouraging an Honest Consensus &#8211- (PDF) &#8211- by Robin Hanson &#8211- 1992-11-00

e) Robin Hanson godfathered the Foresight Exchange (created in 1994) and NewsFutures (created in 2000).

f) Robin Hanson invented the concepts of decision markets (PDF) and decision-aid markets.

g) Robin Hanson invented a new market design (for the 2000-2003&#8242-s Policy Analysis Market), the Market Scoring Rules, a mix between CDA and Scoring Rules &#8212-now in use for most enterprise prediction markets and public, play-money prediction exchanges. Note that MSR is mainly used in a one-dimension version, but many researchers are interested in its combinatorial version.

#4. Other Pioneering Public Prediction Exchanges (Betting Exchanges, Event Derivative Exchanges) and Inventors/Innovators/Entrepreneurs

a) The Foresight Exchange was founded on September 22, 1994 by Ken Kittlitz, Sean Morgan, Mark James, Greg James, David McFadzean and Duane Hewitt. The Foresight Exchange is a play-money prediction exchange (betting exchange) managed by an open group of volunteers. It pioneered user-created and user-managed, play-money prediction markets. Any person can join the Foresight Exchange and interact with the rest of the Web-based organization. An independent judge (independent from the owner of the claim) should be appointed among the volunteers. [Thus, it’s not “DYI prediction markets”.]

b) The Hollywood Stock Exchange was founded on April 12, 1996, by Max Keiser and Michael Burns. See the patent for the Virtual Specialist. For more info, see: Is HSX the “longest continuously operating prediction market”??? &#8211- REDUX

c) BetFair was founded in 1999 by Andrew Black and Edward Wray, and was launched in England in June 2000. As of today, BetFair is the world&#8217-s biggest prediction exchange (betting exchange, event derivative exchange).

d) NewsFutures was founded in March 2000 and launched in September 2000 in France and in April 2001 in the US by Emile Servan-Shreiber and Maurice Balick. See: NewsFutures Timeline. NewsFutures was the first exchange to let people buy or sell contracts for each side of a binary-outcome event. The advantage of this design is that it avoids the need for &#8220-shorting&#8221-, a notion that tends to confuse novice traders. NewsFutures later extend that approach to deal with n-ary outcome events while implementing automatic arbitrage.

e) TradeSports was launched in Ireland in 2002 by John Delaney. InTrade was later purchased and became a non-sports prediction exchange (betting exchange). As of today, InTrade is the biggest betting exchange on the North-American market &#8212-where betting exchanges are still illegal. As for TradeSports, it closed at the end of 2008, alas.

#5. The Policy Analysis Market Brouhaha

a) Robin Hanson was the main economist behind the 2000–2003 US DoD&#8217-s DARPA&#8217-s IAO&#8217-s FutureMAP–Policy Analysis Market project. (For this project, Robin Hanson invented a new market design, the Market Scoring Rules.) On July 28, 2003, two Democratic US Senators called for the termination of PAM, the the big media gave airtime to their arguments, and the US DOD quickly ended the IAO&#8217-s FutureMAP program.

b) The second branch of the 2000–2003 US DoD&#8217-s DARPA&#8217-s IAO&#8217-s FutureMAP program was handled by the Iowa Electronic Markets and was intended to predict the SARS pandemic. (This project later gave birth to IEM&#8217-s Influenza Prediction Market.)

#6. James Surowiecki&#8217-s The Wisdom Of Crowds

a) James Surowiecki&#8217-s book, The Wisdom Of Crowds, was published in 2004.

b) Impact of The Wisdom Of Crowds.

#7. Recent Public Prediction Exchanges (Betting Exchanges, Event Derivative Exchanges) and Inventors/Innovators/Entrepreneurs

a) US-based and US-regulated HedgeStreet was launched in 2004 by John Nafeh, Russell Andersson, and Ursula Burger. A designated contract market (DCM) and a registered derivatives clearing organization (DCO), HedgeStreet is subject to regulatory oversight by the Commodity Futures Trading Commission (CFTC). In November 2006, IG Group bought HedgeStreet for $6 million.

b) Inkling Markets was launched in March 2006 and co-pioneered (with CrowdIQ, which later bellied up) the concept of DIY, play-money prediction markets.

c) In September 2006, TradeSports-InTrade was the first prediction exchange (betting exchange, event futures exchange) to apply Chris Masse&#8217-s concept of X Groups. See: TradeSports-InTrade prediction markets on Bush approval ratings.

d) HubDub was launched in early 2008 and is the second most popular play-money prediction exchange, behind HSX.

#8. Enterprise Prediction Markets

a) Until evidence of the contrary, it seems that Robin Hanson was the first to set up and run a corporate prediction exchange &#8212-at Xanadu, Inc., in April 1989. See: A 1990 Corporate Prediction Market + Anonymity is important for employees trading on internal prediction markets.

b) In the 1996&#8211-1999 period, HP ran a series of internal prediction markets to forecast the sales of its printers.

c) Eli Lilly sponsored 10 public, industry-level prediction markets in April 2003 (on the NewsFutures prediction exchange).

d) Eli Lilly began using internal prediction markets in February 2004 (powered by NewsFutures).

e) Google&#8216-s Bo Cowgill published about their use of internal prediction markets in October 2005.

f) Since then, many companies selling software services for enterprise prediction markets have been created.

#9. Disputes Between Traders And Exchanges

a) The scandal of the North Korean Missile prediction market that erupted in July 2006 is, as of today, the biggest scandal that rocked the field of prediction markets.

Email Interview: Ken Kittlitz

My responses to a set of questions Chris Masse recently emailed to me:

Chris. F. Masse: Ken Kittlitz, you co-founded the Foresight Exchange (it went by the name &#8220-Idea Futures&#8221- at the time) in 1994. Would you mind telling me two words on your co-founders? Which ones brought the most into the project? Are you still in touch with them? Do you know what they have become?

Ken Kittlitz: David McFadzean got the ball rolling by bringing one of Robin Hanson&#8217-s early prediction market papers to our weekly discussion group. Sean Morgan realized that the WWW, then still in its infancy, would be a great way to create such a market. Mark James, along with Sean, did most of the coding of the initial prototype. Duane Hewitt and myself did most of the work on a paper and presentation that our group presented at a conference the following year.

I&#8217-m still in touch only with David- he&#8217-s currently a software architect at QuIC, a company that creates financial risk analysis/mitigation products.

CFM: What was the spirit of your group at that time (in 1994). Did &#8220-entrepreneurship&#8221- mean something for you, guys? Did you envision a commercial venture, or was it just collegians&#8217- play?

KK: Our weekly discussion group was known as the &#8220-BS Group&#8221- (Biological Simulation, in case you&#8217-re wondering), so I&#8217-d have to admit that &#8220-collegians&#8217- play&#8221- is a fair summary. In 1995, we did try to turn it into a commercial venture, which quickly revealed our lack of business experience. We were all techies of one sort or another, and techies often struggle in the business realm.

CFM: Would you mind telling me two words on GMU professor Robin Hanson? How would you introduce him to some of our readers (I pity them) who have never heard of him?

KK: Robin&#8217-s one of the smartest people I&#8217-ve ever met and, unlike many smart people, not over-specialized. He has deep understanding of a number of fields: artificial intelligence, physics, economics and likely a few others I&#8217-m not aware of. He has a habit of coming up with fascinating, controversial ideas, prediction markets being just one example.

CFM: You co-founded this play-money prediction exchange (Foresight Exchange) in 1994. In 1999/2000, Andrew Black and Edward Wray created and launched BetFair in England. BetFair became one of the most successful British start-ups and its two co-founders are now sitting pretty on a small fortune. In hindsight, don&#8217-t you think that you should have moved to the U.K. and incorporated the Foresight Exchange there, using real money?

KK: In hindsight, I think that I should have done a massively-leveraged short sale of NASDAQ stocks in March, 2000. :-)

The best way forward is always hard to identify, even with tools like prediction markets&#8230-

When we tried to commercialize the original &#8220-Idea Futures&#8221-, starting a real-money market offshore was certainly something we considered &#8212- though at that point, somewhere in the Caribbean seemed the likely venue. Even back then, it seemed likely that prediction markets would be considered a form of gambling, and hence subject to draconian restrictions. The Caribbean can be a nice place to live, but the prospect of never being able to return to North America to visit family and friends was quite a disincentive.

CFM: One thing that strikes me when visiting the Foresight Exchange is that you forbid sports prediction markets, which are very popular on the betting exchanges. Even Bo Cowgill&#8217-s group of Googlers trade on sports, sometimes &#8212-I believe. Sports trading can be fun. Are you a jock hater?

KK: Not really, but the Foresight Exchange was created primarily to focus on science and technology claims. Having it cluttered with a couple of dozen &#8220-tonight&#8217-s game&#8221- claims per day wasn&#8217-t too appealing.

CFM: If I can count, you have more than 12 years of experience in the field of prediction markets. You&#8217-ve seen them all, in all colors and shapes. Do you agree with what Robin Hanson said at the Yahoo! Confab, namely that the DARPA&#8217-s PAM scandal ignited interest in corporate prediction markets? Was the PAM scandal a &#8220-tipping point&#8221-?

KK: No. I think the real tipping point was the publication of James Surowiecki&#8217-s &#8220-The Wisdom of Crowds&#8221-. Those of us interested in prediction markets tend to overestimate the PAM controversy&#8217-s importance- it was a big deal for us, but only an incremental step in the general public&#8217-s awareness of the topic. The interest generated by Surowiecki&#8217-s book showed that prediction markets had &#8220-arrived&#8221- &#8212- they weren&#8217-t just of academic interest, but instead had real-world applicability.

CFM: Note that the DARPA&#8217-s PAM prediction markets was to be public. Which leads to my next question. You and partner David Perry at Consensus Point help Fortune-500 companies setting up and running their own internal prediction markets. Have you ever had the case where one firm opened its corporate prediction markets to contractors and clients?

KK: Some of the firms we deal with are certainly interested in having a fairly wide audience, including customers and contractors, for their markets. I can&#8217-t go into specifics at the moment, however.

CFM: How is Consensus Point doing, so far? Can you draw for us the portrait of the firm that wants to use internal prediction markets? Is it always to forecast sales? Do you sense that the requests come from senior executives or from mid-level prediction markets-enthusiast managers?

KK: Consensus Point is doing very well so far. A lot of inquiries do indeed originate from mid-level managers and researchers, but a fair number also come from the executive level. Sales forecasting is a popular application of the market, but project completion times and commodity price forecasting have also proved to be frequent questions.

CFM: Sorry to ask you this question bluntly. Would TradeSports and Betfair make great competitors of Consensus Point if ever they decided one day to sell prediction market services to organizations?

KK: Quite possibly, but it&#8217-s certainly not a given. Both companies have great trading platforms, but their expertise is in running real-money, public markets. Corporations aren&#8217-t really looking for that sort of domain knowledge when considering how to implement and use a prediction market.

CFM: Would you mind describing in a few words the prediction market services you sell? I guess it&#8217-s web-hosted CDA, but are some firms interested in web-hosted MSR?

KK: We offer both hosted and on-site installations of our software, as well as training, analysis and consulting services. As for MSR versus CDA, see below.

CFM: Speaking of Market Scoring Rules, why did you decide to use this design as the engine for the Washington Stock Exchange? What is its main competitive advantage to CDA? How can MSR best be described: &#8220-betting&#8221- or &#8220-simplified trading&#8221-?

KK: The line between an MSR and a CDA is thinner than you might think! We have a market maker for each stock that provides liquidity by placing bid and ask orders- this is a convenient way of implementing an MSR within a CDA framework. An MSR really helps to start (and keep) the market going, because people always have a price they can buy or sell at. With an unadorned CDA, the bid/ask spread can be enormous, and trading volumes very thin. This alas, is often the case on the Foresight Exchange.

I&#8217-d describe an MSR as allowing for &#8220-simplified trading&#8221- rather than &#8220-betting&#8221-, though I suppose it depends on how much thought the person interacting with it puts in!

CFM: Just curious. When a prediction exchange decides to use MSR, does it have to pay fees or royalties to its inventor, Robin Hanson?

KK: I don&#8217-t believe so, but Robin is in a far better position to answer that question than I am&#8230-

CFM: What is the biggest mistake (if any) you have made since the grand opening of Consensus Point? What did you learn from this big mistake?

KK: No really big mistakes come to mind. Of course, such things are often only obvious in retrospect, so ask me again in a few years.

CFM: What are corporate prediction markets competing against (if any)? Internal polls? Groups of in-house experts? The firm&#8217-s executives? Something else?

KK: Generally, the firm&#8217-s executives. We haven&#8217-t encountered too many cases where firms have been trying to use internal polls as part of their forecasting efforts.

CFM: Are you positive that corporate prediction markets will show something for it? Will the economics literature soon be filled with business cases on how firms can clearly benefit from using internal prediction markets?

KK: Based on my experiences in the field thus far, I&#8217-m confident that prediction markets will prove to compare favorably with the other forecasting methods companies use. This isn&#8217-t to say that they&#8217-ll always yield good information, or be the best thing to use in all situations, but I think they will turn out to be valuable.

Am I positive of this? Not absolutely. But then, I try not to be absolutely positive of anything!

CFM: Now, the question that kills. Tell me frankly. Are corporate prediction markets a &#8220-fad&#8221- or are they just started?

KK: Great question! I think it largely depends on how the prediction market community presents the ideas. There&#8217-s a very real danger that the topic will be over-hyped and, consequently, ultimately dismissed, just as so many other trendy business ideas have been in the past. Today&#8217-s darling is often tomorrow&#8217-s pariah. That would be a shame, since (obviously) I think the markets have a lot of merit.

Note by &#8220-prediction market community&#8221-, I&#8217-m referring not only to those who create and sell prediction markets and associated services, but also people who blog about the topic, create vortals, etc. Not mentioning any names here --) .

CFM: Are prediction markets just one forecasting tool, or do they have a bigger function, in your view?

KK: The pragmatist in me says they&#8217-re just one tool, albeit a great one. The idealist finds something profoundly appealing in their ability to democratize how information is gathered and, ultimately, how decisions are made. The idealist thinks they&#8217-re something more.

BetFair fixes the corruption that it suscitates (since short selling could be used by cheating athletes or jockeys).

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From Andrew Gelman:

In a letter published in the latest New Yorker, Douglas Robertson writes,

James Surowiecki, in his column on sports betting, writes, &#8220-How much difference is there, after all, between betting on the future price of wheat . . . and betting on the performance of a baseball team?&#8221- (The Financial Page, September 25th). Future markets in products such as wheat allow famers and other producers to shield themselves from some financial risks, and thereby encourage the production of necessities. In this sense, the futures markets are more akin to homeowners&#8217- insurance or liability insurance than to gambling on sports. But there is no corresponding economic benefit to betting on sports- on the contrary, there are serious costs involved in protecting the sports activities from fixing and other corruptions that invariably accompany such gambling activity.

This is a good point. I enjoy gambling in semi-skill-based settings (poker, sports betting, election pools, etc.), and betting markets are cool, but it is useful to step back a bit and consider the larger economic benefits or risks arising from such markets.

My Take: They are both misinformed. With an ethical real-money prediction exchange (a.k.a. betting exchange), this problem is easily solved. As I reported last month, BetFair has signed memorandums of understanding with TWENTY FOUR sports bodies. If the BetFair managers spot manipulation attempts, they will report the villains&#8217-s mischiefs to the sports bodies and, possibly, to the Police, too. How do you like that, Andrew Gelman?

Addendum (October 30): Andrew Gelman published a blog post on Midas Oracle, in response.