Category Archives: technology

computer science, economics, people, politics, prediction markets, probability, research, science, technology, trends, yahoo

A toast to the number 303: A redemptive election night for science, and The Signal

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The night of February 15, 2012, was an uncomfortable one for me. Not a natural talker, I was out of my element at a press dinner organized by Yahoo! with journalists from the New York Times, Fast Company, MIT Tech Review, Forbes, SF Chronicle, WIRED, Reuters, and several more [1]. Even worse, the reporters kept leading with, “wow, this must a big night for you, huh? You just called the election.”

We were there to promote The Signal, a partnership between Yahoo! Research and Yahoo! News to put a quantitative lens on the election and beyond. The Signal was our data-driven antidote to two media extremes: the pundits who commit to statements without evidence; and some journalists who, in the name of balance, commit to nothing. As MIT Tech Review billed it, The Signal would be the “mother of all political prediction engines”. We like to joke that that quote undersold us: our aim was to be the mother of all prediction engines, period. The Signal was a broad project with many moving parts, featuring predictions, social media analysis, infographics, interactives, polls, and games. Led by David “Force-of-Nature” Rothschild, myself, and Chris Wilson, the full cast included over 30 researchers, engineers, and news editors [2]. We confirmed quickly that there’s a clear thirst for numeracy in news reporting: The Signal grew in 4 months to 2 million unique users per month [3].

On that night, though, the journalists kept coming back to the Yahoo! PR hook that brought them in the door: our insanely early election “call”. At that time in February, Romney hadn’t even been nominated.

No, we didn’t call the election, we predicted the election. That may sound like the same thing but, in scientific terms, there is a world of difference. We estimated the most likely outcome – Obama would win 303 Electoral College votes, more than enough to return him to the White House — and assigned a probability to it. Of less than one. Implying a probability of more than zero of being wrong. But that nuance is hard to explain to journalists and the public, and not nearly as exciting.

Although most of our predictions were based on markets and polls, the “303” prediction was not: it was a statistical model trained on historical data of past elections, authored by economists Patrick Hummel and David Rothschild. It doesn’t even care about the identities of the candidates.

I have to give Yahoo! enormous credit. It took a lot of guts to put faith in some number-crunching eggheads in their Research division and go to press with their conclusions. On February 16, Yahoo! went further. They put the 303 prediction front and center, literally, as an “Exclusive” banner item on Yahoo.com, a place that 300 million people call home every month.

The Signal 303 prediction "Exclusive" top banner item on Yahoo.com 2012-02-16

The firestorm was immediate and monstrous. Nearly a million people read the article and almost 40,000 left comments. Writing for Yahoo! News, I had grown used to the barrage of comments and emails, some comic, irrelevant, or snarky; others hateful or alert-the-FBI scary. But nothing could prepare us for that day. Responses ranged from skeptical to utterly outraged, mostly from people who read the headline or reactions but not the article itself. How dare Yahoo! call the election this far out?! (We didn’t.) Yahoo! is a mouthpiece for Obama! (The model is transparent and published: take it for what it’s worth.) Even Yahoo! News editor Chris Suellentrop grew uncomfortable, especially with the spin from Homepage (“Has Obama won?”) and PR (see “call” versus “predict”), keeping a tighter rein on us from then on. Plenty of other outlets “got it” and reported on it for what it was – a prediction with a solid scientific basis, and a margin for error.

This morning, with Florida still undecided, Obama had secured exactly 303 Electoral College votes.

New York Times 2012 election results Big Board 2011-11-07

Just today Obama wrapped up Florida too, giving him 29 more EVs than we predicted. Still, Florida was the closest vote in the nation, and for all 50 other entities — 49 states plus Washington D.C. — we predicted the correct outcome back in February. The model was not 100% confident about every state of course, formally expecting to get 6.8 wrong, and rating Florida the most likely state to flip from red to blue. The Hummel-Rothschild model, based only on a handful of variables like approval rating and second-quarter economic trends, completely ignored everything else of note, including money, debates, bail outs, binders, third-quarter numbers, and more than 47% of all surreptitious recordings. Yet it came within 74,000 votes of sweeping the board. Think about that the next time you hear an “obvious” explanation for why Obama won (his data was biggi-er!) or why Romney failed (too much fundraising!).

Kudos to Nate Silver, Simon Jackman, Drew Linzer, and Sam Wang for predicting all 51 states correctly on election eve.

As Felix Salmon said, “The dominant narrative, the day after the presidential election, is the triumph of the quants.” Mashable’s Chris Taylor remarked, “here is the absolute, undoubted winner of this election: Nate Silver and his running mate, big data.” ReadWrite declared, “This is about the triumph of machines and software over gut instinct. The age of voodoo is over.” The new news quants “bring their own data” and represent a refreshing trend in media toward accountability at least, if not total objectivity, away from rhetoric and anecdote. We need more people like them. Whether you agree or not, their kind — our kind — will proliferate.

Congrats to David, Patrick, Chris, Yahoo! News, and the entire Signal team for going out on a limb, taking significant heat for it, and correctly predicting 50 out of 51 states and an Obama victory nearly nine months prior to the election.

Footnotes

[1] Here was the day-before guest list for the February 15 Yahoo! press dinner, though one or two didn’t make it:
-  New York Times, John Markoff
-  New York Times, David Corcoran
-  Fast Company, EB Boyd
-  Forbes, Tomio Geron
-  MIT Tech Review, Tom Simonite
-  New Scientist, Jim Giles
-  Scobleizer, Robert Scoble
-  WIRED, Cade Metz
-  Bloomberg/BusinessWeek, Doug MacMillan
-  Reuters, Alexei Oreskovic
-  San Francisco Chronicle, James Temple

[2] The extended Signal cast included Kim Farrell, Kim Capps-Tanaka, Sebastien Lahaie, Miro Dudik, Patrick Hummel, Alex Jaimes, Ingemar Weber, Ana-Maria Popescu, Peter Mika, Rob Barrett, Thomas Kelly, Chris Suellentrop, Hillary Frey, EJ Lao, Steve Enders, Grant Wong, Paula McMahon, Shirish Anand, Laura Davis, Mridul Muralidharan, Navneet Nair, Arun Kumar, Shrikant Naidu, and Sudar Muthu.

[3] Although I continue to be amazed at how greener the grass is at Microsoft compared to Yahoo!, my one significant regret is not being able to see The Signal project through to its natural conclusion. Although The Signal blog was by no means the sole product of the project, it was certainly the hub. In the end, I wrote 22 articles and David Rothschild at least three times that many.

artificial intelligence, computer science, economics, people, research, technology, trends

Congratulations Pete Wurman and Kiva Systems, a bellwether of the automated economy

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Congratulations to my academic sibling, friend, and Detroit Red Wings fan Pete Wurman, whose company Kiva Systems just became Amazon’s second largest acquisition ever.

In short, Kiva Systems designs, builds, and operates intelligent autonomous robots to pick and stow products in giant distribution centers for companies like Toys R Us, Walgreens, and Zappos. (The latter is an Amazon subsidiary.) The best way to understand Kiva Systems is to watch their robots in action: an amazing sight to see. Here is a clip from IEEE Spectrum:

In 2003, I remember sitting in the back seat of a car with Pete, him excitedly demo-ing the concept to me via an animated simulation on his laptop, little dots representing robots weaving in and out of each on the screen. (Pete’s laptop was a mac. In grad school, Pete was every bit the Apple fan I was and more. He and I programmed HyperCard and Newton together. Pete advocated for simplicity in design before it was cool. When I briefly switched to Windows, he never wavered.)

By 2006, the robots were real. Pete took me and our shared academic parent, Mike Wellman (who I believe also played an early role in the company), on a tour. Dots on a laptop had become squat orange robots receiving orders, fetching products, avoiding each other, seeking power, and otherwise navigating around a complex environment with computational minds of their own. The designs were inspired: for example, to lift a box, the robot spun underneath it to extend a corkscrew so that the product wouldn’t get jarred. They even added noise in the robots’ paths, so their wheels wouldn’t wear grooves in the floor (call it a floorsaver algorithm).

By coincidence, a few weeks ago, I was speaking to someone from Amazon who works on optimizing the way people (ha!) retrieve, store, and pack items in their distribution centers and I mentioned Pete’s company. He said “until that happens” he would focus on optimizing their current systems. Little did we (or at least I) know how quickly “until” would come.

Kiva Systems isn’t just an incredibly cool company run by amazing people. It’s a harbinger of things to come as the world moves inexorably toward an Automated Economy.

By the way, if you’re worried that robots will take jobs away from people, don’t. The world is a better place with mechanical devices doing mechanical tasks, leaving people to do more interesting and creative things, for example turning crazy ideas into companies. Remember that the purpose of jobs is to produce valuable things and improve the world. Despite political rhetoric, jobs are not an end to themselves. Otherwise, we should all be happy digging ditches and filling them back up, or pumping gas for people who would rather do it themselves. Think about where society should go in fifty or a hundred years when automation can handle more and more tasks. It would be a real shame if at that time people were still “working for a living” in jobs they don’t enjoy simply for the sake of keeping them occupied.

fun, gambling, law, prediction markets, sports, startups, technology

Slipjockey: A marketplace for buying and selling Las Vegas bet slips

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In late 2010, I began talking to a very early-stage startup named Slipjockey, based in Salt Lake City. When we first started corresponding, Slipjockey was little more than a good idea coupled with some very basic technology and passionate co-founders. In the time since, Slipjockey has taken appropriate steps to bring their concept to market, including securing a favorable legal opinion and filing a patent for their technology.

The core concept of Slipjockey is ingenious. It’s a marketplace for buying and selling Las Vegas bet slips. The process starts when someone makes a bet at a licensed Nevada race and sports book. If he or she wants to sell the bet slip for whatever reason — suppose the predicted team is winning in a landslide at halftime and the slip has doubled in value — they can log onto Slipjockey and list it for sale. Another Slipjockey user may agree to buy it. The buyer takes ownership of the bet slip and he or she can keep it or resell it again to another Slipjockey user, etc. The final owner of any bet slip is paid in full directly from the sports book that originally issued the ticket.

Real-time trading on Slipjockey is similar to the action on betting exchanges like Betfair. The key difference is that all wagers must originate from a licensed Nevada race and sports book where gambling is legal.

The Slipjockey business concept grew from the notion that handicappers should have an option other that win, lose, or push. Slipjockey provides that fourth option by enabling handicappers to terminate their outcome risk, locking in a gain or avoiding a total loss prior to the end of the event. With the growth in live betting (aka “in-running betting”) around the world, and in Las Vegas courtesy of Cantor Fitzgerald, it’s clearly an option that people want.

Initially, Slipjockey is focused on launching with coverage of US football, tennis, and golf before expanding into other sports.

I’ve spoken mainly with Ryan Eads and his brother Rory, two of the co-founders. They are smart, well spoken, and tireless entrepreneurs. I have every expectation that, to the extent this idea has wings — and I believe it does — they will make it fly.

The first question you’re likely to ask is: is this legal? Indeed, that’s the first question I asked Ryan. As a pre-condition to launching, he secured a legal opinion from a former Nevada Gaming Control Board attorney that says, in effect, that because bets originate in Las Vegas and are ultimately paid out in Las Vegas, the Slipjockey exchange is legal. The attorney’s opinion is just that: an opinion, and not a guarantee. But it is convincing and credible. Certainly Slipjockey users are safe.

Currently, Slipjockey is inviting users to participate in a soft launch for trading National Football League games. To participate, create a profile at www.slipjockey.com and send an email to info@slipjockey.com. Mention that you read my blog post and I’m sure they’ll send you an invitation containing all the details if they have spots remaining.

commentary, computer science, lastanalogs, new media, people, personal, technology

A professional thanks and a personal goodbye to Steve Jobs

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Small Apple tribute logo, created by Mak Long

10 Print "Hello"

That line typed on an Apple II computer in my Dad’s office in the fourth grade got me hooked on computer programming, an addiction I never outgrew.

Over the years, I’ve had the pleasure of owning, using, or programming on many of Steve Jobs’s creations, including Apple II+, Macintosh IIcx, Power Mac 7100, Newton, NeXT, Powerbook, Macbook Pro, and iPhone. I’ve been a consistent Mac in the Mac-vs-PC battle since 1984 (though I admit to a brief affair in 1998: it didn’t mean anything, Steve, I swear!). Jobs himself ignited an us-versus-them fire, which smolders on today in Apple’s John Hodgman-as-PC ads, back in 1985 with one of his best quotes:

Playboy: Are you saying that the people who made PCjr don’t have … pride in [their] product?

[Jobs:] “If they did, they wouldn’t have made the PCjr.” [Playboy, Feb. 1, 1985]

Around that time, my friends and I had a running joke: “I got a PCjr,” one of us would say; “you’re going straight to hell, kid,” the other would shoot back.

Old Apple II and Power Macintosh computers
Buried treasure: Old Apple II and Power Macintosh computers, waiting to be dusted off… someday



My wife and kids (ages 7 and 4) are more recent converts, owning a Duo, an iPhone, an iPad, and two iPod Touches among them.

I’ve owned Apple stock since about 1997, my single best investment, increasing 4,460 percent. (Priceline is my second best, gaining 3,990%.)

Like Lance, I’ll never forget where I was when I learned that Steve Jobs had died. Steven Colbert told me. Live. After a hilarious taping of the Colbert Report and four performances by the artist formerly known as Mos Def (apparently a perfectionist: who knew?), Colbert ended by balancing his iPhone on his desk, letting it fall over, then telling us, “Steve Jobs died. Sorry to be the one to tell you.” To say the mood of the audience changed instantly would be an understatement. Smiling faces turned down. Cries of anguish and “oh no!” rang out from nearly everyone in the audience, a mark of how Jobs’s influence and name recognition has grown from tech hero to global cultural icon. (Colbert gave Jobs a proper tribute the next day.)

There’s a thread in our office about the extent to which perceived success or failure at the CEO level is a fooled-by-randomness trick of the mind. But there are some examples where even the strongest skeptic must admit that an organization’s success is almost surely owed to the exceptional greatness of a single individual. Warren Buffet and Coach K come to (my) mind. But Steve Jobs must be the prime example. As if ushering in the era of personal computing and computer-animated movies was not enough, Jobs continued to outdo himself year after year, with iPod, iTunes, iPhone, and, barely a year ago, iPad. Sadly, or maybe purposefully, Jobs seemed to hit his stride just as he died. As a long-time disciple of Jobs, I’m amazed at the amount of focus in his obituaries spent on gadgets he created in the last ten years.

Jobs famously advised not to spend too much time celebrating success.

I think if you do something and it turns out pretty good, then you should go do something else wonderful, not dwell on it for too long. Just figure out what’s next.
—NBC Nightly News, 2006

Those were not empty words for Jobs: it’s how he lived his own life and how he squeezed so much out of the 56 short years he was given. The early storyline of Apple pegged Steve Wozniak as the brains and Jobs as the lucky business-minded sidekick. It turns out that Jobs was way more exceptional than the 1990s nerderati — who like me relate more to Woz — gave him credit for. Jobs had the brains, the vision, and the charisma in a combination so rare I’m not the only one who can’t think of another human alive who compares. To get a taste, read or watch Jobs’s Stanford commencement speech: it’s truly brilliant, inspiring, and one of the best ways you can spend the next few minutes of your time.

To the ultimate hacker painter, the first last analog, the nerdiest salesman, the studliest genius, the most productive perfectionist, the most detail-oriented visionary, and a personal hero:

20 Print "Goodbye"
commentary, computer science, people, personal, technology, yahoo

A professional goodbye and a personal thanks to Carol Bartz

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My geek CEO was fired. If you’re wondering whether she deserved it, or Yahoo! is better off for it, or Roy Bostock is a doofus or dorfus, I don’t really know.* But I do have a personal story about Carol Bartz that’s indicative of the kind of CEO she was and the kind of person she is, perfect for Ada Lovelace day, a day to blog about women in science and technology who inspire you.

In May 2010, my wife Lauren was diagnosed with breast cancer. On Sunday, May 9, 2010—Mother’s Day no less—I received a phone call. “Hello?,” I said. “Hi, this is Carol Bartz,” she said. “Wow!,” I couldn’t help saying. I had never spoken to her before. She proceeded to say how sorry she was for me and Lauren, to reassure us, to ask me questions, and to answer mine.

More than a year, multiple surgeries, and six chemo sessions later, I’m happy to say that Lauren is past the worst part of the treatment and, to the best of anyone’s knowledge, cancer free. At the time, we were frightened, bewildered, and angry. To me, the most overwhelming feeling was disbelief. Was this really happening to us? It was surreal. Lauren’s strength and sheer will to keep our home life as normal as possible, and her ability to turn the ordeal into a positive is amazing and helped me cope. That my mom and Lauren’s mom went through the same thing also helped. The more we looked into it the more we realized breast cancer was everywhere—shockingly common even at Lauren’s age. (Especially in New Jersey, one of only five states in the top tier for both incidence of and mortality from breast cancer.) The calls to increase the age of first mammogram border on criminal. One silver lining for Lauren has been meeting the amazing support community of breast cancer sufferers, survivors, and their friends. They have inspired her to give back in many ways. My mom, a radiologist and ACR fellow, was herself inspired to specialize in mammography and pursue breast cancer research.

It turns out, Carol Bartz is a survivor herself and, in addition to being one of the fifty most powerful women in business, is just another member of the breast cancer support community who cares deeply. Carol had over twelve thousand employees. To take the time to call one of them on a holiday weekend to address personal problems and pain shows the kind of leader she is. (And shows the kind of bosses Preston and Prabhakar are, who thought enough to bring it to her attention.) It’s a “Yahoo! moment” and a Carol moment that I remember vividly and continues to stick out in my mind. I suspect most stereotypes of corporate and public leaders as conniving powermad ladder climbers are just that: stereotypes. But still, I’m convinced that not all—probably few—CEOs would do what Carol Bartz did. Goodbye, good luck, and, most of all: Thanks, Carol.

* I will say that I respect Carol’s willingness give her blunt assessment of the board, possibly risking $10 million to do so, and to come right out and say “I was fired” rather than hide behind “more time with family” cliches. I’m not surprised that the board gave their full confidence to her in public just two months before firing her—of course a board always has to say that they have confidence in their current CEO. I am surprised and dismayed that, at least judging by her reaction, it seems the board was also giving their confidence to her in private. That’s HR 101: No one who’s fired should be surprised.

gambling, games, prediction markets, research, review, startups

Crowdpark: Taking Facebook and now Florida by storm

Crowdpark logoCrowdpark is an impressive, well-designed prediction market game that’s already attracted 500,000 monthly active users on Facebook, the 11th fastest growing Facebook app in April.

It’s a dynamic betting game with an automated market maker, not unlike Inkling Markets in functionality (or even Predictalot minus the combinatorial aspect). What stands out is the flashy UI, both literally and figuratively. The look is polished, slick, refreshing, and richly drawn. It’s also cutesy, animation-happy, and slow to load. Like I said, Flash-y in every way. The game is well integrated into Facebook and nicely incorporates trophies and other social rewards. Clearly a lot of thought and care went into the design: on balance I think it came out great.

Crowdpark is a German company with an office in San Francisco. In addition to their Facebook game, they have German and English web versions of their game, and white-label arrangements with gaming companies. They launched in English just last December.

Crowdpark’s stunning growth contrasts with decidedly more mixed results on this side of the Atlantic. I wonder how much of Crowdpark’s success can be attributed to their German roots, their product, their marketing, or other factors?

Crowdpark has an automated market maker they call “dynamic betting” that I can’t find any technical details about [1]. Here’s their well-produced video explanation:

They say it’s “patent pending”, though my colleague Mohammad Mahdian did some nice reverse engineering to show that, at least in their Facebook game, they’re almost certainly using good-old LMSR. Here is a graph of Crowdpark’s market maker price curve for a bet priced at 1%:

Crowdpark's automated market maker price curve

Here is the raw data and the fit to LMSR with b=20,000.

risk   to win (CP)   to win (LMSR)
1 91 91.079482
2 181 181.750593
5 451 451.350116
10 892 892.847929
20 1747 1747.952974
50 4115 4115.841760
100 7535 7535.378665
200 13019 13019.699483
500 23944 23944.330406
600 26594 26594.687310
700 28945 28945.633048
800 31059 31059.076097
900 32979 32979.512576
1000 34740 34740.000000

Still, there’s a quote buried in the video at 0:55 that caught my attention: “you’re current profit is determined by the fluctuation of the odds”.

There’s only one market maker that I know of where the profit fluctuates with the odds, and that’s my own dynamic parimutuel market, which by coincidence recently went from patent pending to inventor cube delivered. 🙂

David Pennock's dynamic parimutuel market (DPM) patent cube - 4/2011

With every other market maker, indeed almost every prediction market, the profit is fixed at the time of the bet. Add to that the fact that Crowdpark bought a majority stake in Florida horse racing circuit Saratoga Racing Inc. and plans to operate all bets exclusively through their system, leads me to wonder if they may have some kind of parimutuel variant, the only style of betting that is legal in the US.

Of course, it may be that I simply misinterpreted the video.

[1] The technical exec at Crowdpark seems to be Aleksandar Ivanov. I found a trade press paper on (internal) prediction markets he wrote in 2009 for the Journal of Business Forecasting.

artificial intelligence, computer science, economics, finance, fun, gambling, prediction markets, probability, review, sports, startups

There’s a new oracle in town

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Cantor Gaming mobile device for in-running bettingLast January, a few friends and I visited the sportsbook at the M Casino in Las Vegas, one of several sportsbooks now run by Cantor Gaming, a division of Wall Street powerhouse Cantor Fitzgerald. Traditional sportsbooks stop taking bets when the sporting event in question begins. In contrast, Cantor allows “in-running betting”, a clunky phrase that means you can bet during the event: as touchdowns are scored, interceptions are made, home runs are stolen, or buzzers are beaten. Cantor went a step further and built a mobile device you can carry around with you anywhere in the casino to place your bets while watching games on TV, drink in hand. (Cantor also runs spread-betting operations in the UK and bought the venerable Hollywood Stock Exchange prediction market with the goal of turning it into a real financial exchange; they nearly succeeded, obtaining the green light from the CFTC before being shut down by lobbyists, er, Congress.)

Back to the device. It’s pretty awesome. It’s a Windows tablet computer with Cantor’s custom software — pretty well designed considering this is a financial firm. You can bet on the winner, against the spread, or on one-off propositions like whether the offensive team in an NFL game will get a first down, or whether the current drive will end with a punt, touchdown, field goal, or turnover. The interface is pretty nice. You select the type of bet you want, see the current odds, and choose how much you want to bet from a menu of common options: $5, $10, $50, etc. You can’t bet during certain moments in the game, like right before and during a play in football. When I was there only one game was available for in-running betting. Still, it’s instantly gratifying and — I hate to use this word — addictive. Once my friend saw the device in action, he instantly said “I’m getting one of those”.

When I first heard of Cantor’s foray into sports betting, I assumed they would build “betfair indoors”, meaning an exchange that simply matches bettors with each other and takes no risk of its own. I was wrong. Cantor’s mechanism is pretty clearly an intelligent automated market maker that mixes prior knowledge and market forces, much like my own beloved Predictalot minus the combinatorial aspect. Together with their claim to welcome sharps, employing a market maker means that Cantor is taking a serious risk that no one will outperform their prior “too much”, but the end result is a highly usable and impressively fun application. Kudos to Cantor.

P.S. Cantor affectionately dubbed their oracle-like algorithm for computing their prior as “Midas”, proving this guy has a knack for thingnaming.

commentary, economics, prediction markets, startups, trends

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

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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.

artificial intelligence, computer science, economics, finance, fun, gambling, games, hacking, prediction markets, probability, research, technology, yahoo

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

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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.

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Yahoo! Key Scientific Challenges: Applications due March 11

Applications for Yahoo!’s third annual Key Scientific Challenges Program are due March 11. Our goal is to support students working in areas we feel represent the future of the Internet. If you’re a Ph.D. student working in one of the areas below, please apply!

We are thrilled to announce Yahoo!’s third annual Key Scientific Challenges Program. This is your chance to get an inside look at — and help tackle — the big challenges that Yahoo! and the entire Internet industry are facing today. As part of the Key Scientific Challenges Program you’ll gain access to Yahoo!’s world-class scientists, some of the richest and largest data repositories in the world, and have the potential to make a huge impact on the future of the Internet while driving your research forward.

THE CHALLENGES AREAS INCLUDE:

– Search Experiences
– Machine Learning
– Data Management
– Information Extraction
– Economics
– Statistics
– Multimedia
– Computational Advertising
– Social Sciences
– Green Computing
– Security
– Privacy

KEY SCIENTIFIC CHALLENGES AWARD RECIPIENTS RECEIVE:

– $5,000 unrestricted research seed funding which can be used for conference fees and travel, lab materials, professional society membership dues, etc.

– Access to select Yahoo! datasets

– The unique opportunity to collaborate with our industry-leading scientists

– An invitation to this summer’s exclusive Key Scientific Challenges Graduate Student Summit where you’ll join the top minds in academia and industry to present your work, discuss research trends and jointly develop revolutionary approaches to fundamental problems

CRITERIA: To be eligible, you must be currently enrolled in a PhD program at any accredited institution.

We’re accepting applications from January 24th – March 11th, 2011 and winners will be announced by mid April 2011.

To learn more about the program and how to apply, visit http://labs.yahoo.com/ksc.