Coolhunt #9 - Thursday, April 26, 2007
Coolhunt Log #9
Thursday, April 26, 2007
Scott Cooper, MIT researcher with the Sloan School of Management, co-author of Coolhunting
Peter Gloor, MIT researcher with the Sloan School of Management, co-author of Coolhunting
Steve O’Keefe, moderator
Listening in from Sweden is one of the co-authors of the book Design-Inspired Innovation.
Leading the Coolhunt today is Peter Gloor.
PETER: Today, we’re going to talk about prediction markets. A really great example is InTrade.
PETER: Prediction markets are a great way to tap into the wisdom of crowds. Instead of having an expert predicting the outcome of certain events, you have people placing bets on what’s going to happen.
SCOTT: This ties in with things we’ve discussed in previous days. The concept of collective intelligence to predict outcomes is similar to what we talked about with “Mutual Fun” at Rite Solutions. Essentially, anything that hits the news that has an outcome related to it can be bet on here. For example, right now bets are being placed on whether Paul Wolfowitz will be asked to resign at the World Bank. Whether the news items are actually bet on depends on what the swarm wants to do.
PETER: Let’s look at what the swarm wants to do by going to the U.S. Politics section of InTrade.
PETER: For each potential candidate, you can place a bet. Right now, if you invest 30 cents, you will get $1 if Giuliani is selected as the Republican candidate for President.
MODERATOR: Is there “skin in the game,” as you say in the book? Does this use real money?
PETER: Yes, it uses real money. These are real bets. In one of our research projects, a group of students monitored web chatter to accurately predict Oscar winners. The closer an event gets, the more accurate the predictions get. The closer we get to the elections, these predictions get more accurate.
MODERATOR: Is there any analysis that compares the accuracy of prediction markets with other means of polling?
PETER: Usually, the prediction markets outperform traditional polling, by far. You have to look at how the prediction market is set up. It has to be a large crowd. It has to have a good mix of participants — different types of people. Private companies are also using prediction markets, such as HP, Google, and Microsoft. There is undeniable evidence that even small prediction markets are more accurate in predicting software delivery dates than managers or experts.
SCOTT: I’ve read interesting stories over the past year about businesses using prediction markets, partially precipitated by an article that appeared last spring in the New York Times Business section. The article said that while some high-tech companies were making breakthroughs trading on idea futures, most companies had not done it. Prediction markets threaten the hierarchal control of managers and would make it obvious that most managers are stupid, to paraphrase many bloggers.
MODERATOR: If the costs of setting up the mechanism are not prohibitive, it seems prediction markets would be preferred.
PETER: There are prediction markets for success of movies at the box office.
SCOTT: We talk about the Hollywood Stock Exchange in Coolhunting and how it’s useful to help determine the likelihood of a given release becoming a box office smash. There are 1.4 million people who trade on the Hollywood Stock Exchange as of a year ago when we wrote that section of Coolhunting.
PETER: One interesting note is that people are not betting real money on this site. There are some rewards such as T-shirts and tickets for very successful predicters.
SCOTT: It’s expanded over the years, not just to predict success of movies. There are also star bonds — essentially, betting on the future success of a given entertainer.
MODERATOR: There is a leader board with top traders for the site. You’d think someone would recruit these people as movie reviewers?
SCOTT: It would be interesting to find out if anyone has parlayed their success on Hollywood Stock Exchange into becoming a paid movie critic.
PETER: Companies want successful predictors to participate in their prediction markets. It creates accuracy. Having people with a good track record of making predictions helps the hive. We’ve found that it is not just the number of people participating in the markets that counts, but also the quality of their prediction capabilities — and of course their “betweenness” factor — how well networked they are. We’d love to have a swarm full of Warren Buffets — the investor with a track record for accurately predicting markets. Now, let’s visit the grandfather of prediction markets sites, the Iowa Electronic Markets.
PETER: This is a longstanding market for predicting presidential elections, run from the University of Iowa College of Business.
MODERATOR: You can make predictions on diseases as well. Can people really predict the outbreak of a disease better than medical professionals?
PETER: There has been research done in this field. If you have a mix of experts, ordinary people, and well-educated people, you get the best predictions. The mix is more accurate than the experts alone. Experts have really strong opinions.
SCOTT: There is a specific reason we refer back to collective wisdom and collective intelligence. They can mean two very different things, with respect to the combination of experts and “ordinary” people. It’s with the ordinary that you often get the wisdom part of the equation. They don’t have the bias associated with being an expert. That, mixed with real expertise, can be a powerful predictor. People making “bets” are informed non-experts. One has to assume that if you’re betting real money on InTrade on whether Barack Obama will get the nomination, you’re doing it based on some of your own intelligence applied in a wise way.
In our book, we make mention of the fact that a few years ago, the Pentagon proposed a market for anonymous bettors to predict when a terrorist attack would take place. They thought it’d be a worthwhile endeavor rather than an academic experiment. It didn’t happen because after the news of it went public, people were horrified by the concept of using a disaster as a “game.”
I worked at a firm a few years ago on an early version of a prediction market regarding the energy crisis. Consultants would get together once a week and make bets about certain aspects of the electricity market in the U.S. This was 15 years ago, and we were using collective wisdom plus a general information dump from the corporate librarian.
MODERATOR: Much like turning an office football pool into a powerful new business tool.
PETER: Let’s now look at how something that was really cool in the past is becoming less cool. The brand of Apple is mired in maintaining coolness. Right now, there is the controversy of the backdated stock options. Bloggers are suggesting that Steve Jobs knew about this all along. We can view the various comments on Slashdot to see some examples.
MODERATOR: By the way, Slashdot is a hugely popular blog for nerds and geeks. It’s a great place for cool farming.
PETER: Yes, it’s a great place for cool farming and even more so for coolhunting. Scroll through the comments on this particular blog post about the stock option crisis at Apple and see what respondents think about Jobs.
We could go to InTrade and see if people are already placing bets on Jobs stepping down.
MODERATOR: These comments give us the sense of what’s happening with the hive.
PETER: Exactly. The wisdom of crowds is amazing for predicting these sorts of things.
MODERATOR: We are out of time. Thank you very much, Peter and Scott. Listeners, please post your comments to the blog — whether they’re about commentary on the subject of today’s coolhunt or any connection problems you experienced.
Join us tomorrow for the next installment of our live, online coolhunt with Peter Gloor and Scott Cooper.
Copyright Notice: Please feel free to duplicate or distribute this log as long as the contents are not altered and this notice is intact.
Web Coolhunting compared with Prediction Markets – Intrade.com
Yesterday’s New York Times profiles Intrade.com, a prediction market and betting web site in Ireland. The article makes the point for the wisdom of crowds, where swarms of people putting their money where their mouth is are better in predicting outcomes of political elections than the official polls of TV stations and the like.
For example, in the 2004 presidential elections, Intrade correctly predicted the outcome in all 50 states. For the 2008 elections, bets are on…… Hillary Clinton and John McCain as the Democratic and Republican frontrunners (see Intrade snapshots of yesterday)
The article got me curious to see what the Web predicts. I ran a TeCFlow coolhunting query on the leading presidential contenders over the last 40 days. The results were somewhat different from Intrade:
The first point to notice is that there is no clear frontrunner, at least by Web buzz. Hillary is not doing too well, John Edwards is spoken about more, while Mitt Romney displays a weakness attack even after the day he officially announced his candidacy.
Looking at the snapshot picture of the movie showing the centrality of the candidates is a little bit more insightful:
Hillary Clinton, Barack Obama and John McCain are all about similarly central, while John Edwards has a higher centrality value, he is not part of the central cluster. The “kingmaking” Web sites are still time.com, the New York Times, Ovaloffice2008, and blog search engine Technorati. All the candidates are eclipsed, however, by non-candidates Condoleezza Rice and Newt Gingrich.
Click here to see the QuickTime movie (8.6MB). (Explanation: the numbers behind the names of each candidate depict his/her centrality at any given point in time, the closer two candidates are located together on the screen, the stronger their connection.)