I am not a fan of the prediction market business. I know that many game and social theorists think they're valuable predictors of crowd behavior, but I've seen too many prediction start-ups turn into intellectual wastelands, with a few people controlling the "price" of opinions that are either pointless on the face of it, or bizarrely tilted in one direction or the other.
For Apple to sell 45 million iPhones next year, it would have to quadruple its sales from 2008.
Yes, that's more than a bit optimistic. The analyst who originally made that sales prediction for Apple back before the phone was even launched is at it again, though, on Monday explaining how he thinks it could happen.
Piper Jaffray analyst Gene Munster insists--despite consensus that his prediction is entirely overeager--that Apple will do so by introducing a 3G version of the iPhone in the second or third quarter of this year, as well as a lower-price version of the … Read more
I've always preferred prognostication to nostalgia, so rather than replay the best of 2007, I'll use these late December doldrums to make 10 predictions for the coming year. Some editors will warn you that this kind of list is suicide--it's too easy for everybody to look back a year later and see where you were wrong--but it hasn't hurt Cringely, so here goes. In no particular order.
Far be it from me to question the work of McKinsey but their list of Eight business technology trends to watch in 2008 all seem like things we already watch just with different names. Nonetheless, it's a good read as we head into the new year.Distributing cocreation--sounds like open source development to me Using consumers as innovators--crowdsourcing Tapping into a world of talent--see above Extracting more value from interactions--see above, again I find Number 7-"Putting more science into management" the most interesting The amount of information and a manager's ability to use it have … Read more
SAN FRANCISCO--Scientists are trying to peer a bit further into the future than the typical five-day weather forecasts available today.
Forecasting weather is a notoriously tough challenge that combines physics modeling, data collection, and computer processing--and unlike many scientific problems, pretty much everyone on the planet cares how well it's done. But forecasts today peter out after a few days, leaving a cloud of uncertainty (forgive me) that only lifts when it comes to predicting seasonal weather phenomena such as El Nino.
Scientists are now getting a handle on intermediate-term forecasts by computer models of a particular type of … Read more
Watch it first.
OK. NOW you can tell me why I'm going to be so totally wrong. In fact,I encourage you to post your predictions in the comments here,and we'll circle back in a year and see who's right.
Predictify is a survey engine cleverly masquerading as a prediction market. On the site, users can answer questions that test their predictive abilities in various fields. If they prove to be right, they can win actual real money. Users even get a small payout for answering a question if they end up being wrong.
People and companies wanting to do market research can submit questions to the Predictify audience--for a fee--and the answers that prove to be most accurate split the bulk of "pot" that is attached to the question.
The money is ingenious misdirection. The point of rewarding accuracy is not to actually pay people for being right. The money is there, rather, to ensure that people who answer questions try to be right. Data from a Predictify survey is broken down in many ways for its users who pay for results, and it's that demographic breakdown that Predictify is really selling, not absolute predictions.
For example, suppose a company wants to know how to price a product. It can ask a question, "What do you think the price of this product will be when it hits the market?" The answers will be correlated with demographics, revealing what different groups (gender, age, ZIP code, etc.) think the item is worth. The "winners" who select the right price aren't predicting the price so much as determining it, and the people who select the price point are basing it not on the aggregate wisdom of the crowd but on the pricing level their target demographic has zeroed in on.
It's one of the cleverest Web 2.0 mind games I've seen in a while, and it just might work. Like many prediction markets, though, the community will run out of gas unless there's a strong incentive to keep people engaged. Money is just part of it on this system. Predictify also ranks users, and pays out more to the more accurate ones.