John Tierney and Jed Christiansen are making the same mistake: they think that people and experts should be impressed by the information aggregation functionality of the prediction markets. They are not —-people still prefer reading Nate Silver and Electoral-Vote.com over InTrade, and the political experts have not added InTrade in their toolbox. (On this last point, do read the very last sentence of that interview.)
You won’-t be impacting if you publish enthusiastically about the features of the prediction markets —-yes, they do incorporate the latest news quickly, they quantify reasonable anticipations, they output probabilities, and they are relatively unbiased. You will be impacting the day you are able to demonstrate the benefits of the prediction markets —-for people, on one hand, and for the experts, on the other hand.
This would require a new focus, and a much bigger effort.
The social utility of most prediction markets is minimal —-busy people (who don’-t have time to read extensively the news) get relatively objective probabilities, real quick. But very few companies are using enterprise prediction markets, as of today. If these new IAM tools were magical (as some sur-excited free-market proponents think they are), all the Fortune-500 companies without any exception of any kind would be using them today.
If you want to discover the true benefits of the prediction markets, you should first be able to rank them by degree of utility. Which ones are more useful than others? Why? To answer this last question, you have to lay out the panorama of all the information sources that people and expert have access to, these days. What were the specific instances where the prediction markets were a tie breaker between the experts and the mass media, or between the decision makers and the experts, or between 2 opposite groups of experts? You should build an airtight, documented case. I haven’-t seen such a case, yet. If some of my readers are interested in such a project, let’-s talk.
I agree that markets ‘incorporate the latest news quickly, they quantify reasonable anticipations, they output probabilities, and they are relatively unbiased.’ This being said, I’ve found at least from the friends I introduce to Hubdub that the funnest thing they get out of markets is seeing forecasts on what’s going to happen. Most of these individuals are University mates who’ve been brought up under facebook, so actually participating in Hubdub or other markets is less of a priority than just observing.
In my view the consumers of prediction markets are for now mostly regular people, and the participants are mostly regular people. (This comes from my work at Hubdub, so I can’t say the same for intrade) While a normative source of revenue should come from the corporate participants and consumers, the only way you get those corporate interests is from regular everyday people involvement. So that always has to be key.
“This being said, I’ve found at least from the friends I introduce to Hubdub that the funnest thing they get out of markets is seeing forecasts on what’s going to happen. Most of these individuals are University mates who’ve been brought up under facebook, so actually participating in Hubdub or other markets is less of a priority than just observing.”
In the above you are describing a situation where your buddies watch the prediction market probabilities and enjoy them —and I assume that your buddies don’t spend hours reading news articles about the topics they spot on HubDub. They just enjoy the HubDub probabilities. Good. Fine.
But to answer the question, “Are prediction markets useful?”, we need to compare those probabilities with the polls, the pundits’ predictions, and the mass media’s axle to grin (a.k.a. bias). Assessing the prediction markets requires us to put them in a social context. It is much more difficult and costly than to go on HubDub and just watch the probabilities with friends.
Your buddies are seeking fun. That’s fine. But to be impacting upon the journalists and decision makers, we should demonstrate a certain social utility.
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The truth about prediction markets