The Emperor of enterprise prediction markets is naked.
Robin Hanson:
I can confirm that this disinterest is real. For example, when I try to sell firms on internal prediction markets wherein employees forecast things like sales and project completion dates, such firms usually don’t doubt my claims that such forecasts are cheap and more accurate. Nevertheless, they usually aren’t interested.
Excellent editorial from Lawrence O’-Donnell. Make sure to watch the whole segment till the end.
You can build a predictive model to find hidden patterns in financial data, or else.
–> Google Prediction API – Machine learning for your business.
In April 1989, Robin Hanson created this prediction market:
By 1/1/91 a <-1 liter device will have generated over 1 watt of power output more than input from room-T fusion, including amortized power to create/separate components.
I suppose that InTrade will be willing to float E-cat contracts. We’-ll see.
And that includes Jason Ruspini.
UPDATE:
– Keep in mind that, at inception, Apple also underestimated the iPad numbers. They had to ramp up production, later on.
– See Paul Hewitt’-s comment, below.
Web 2.0 Summit 2010: Vinod Khosla, “-Innovation vs. Punditry”-
Extrapolating the Past vs Inventing the Future:
In summary, “-momentum”- can exist, but the places where you’-ll see it is in races where current public opinion is out of step with best predictions. The mere information that a race has a 5-point swing is not enough to predict a future shift in that direction. As Nate emphasizes, such a prediction is only appropriate in the context of real-world information, hypotheses of “-factors above and beyond the direction in which the polls have moved in the past.”-
–
Don’-t Create Standards You Will Find Hard to Maintain Yourself.
Be Honest.
Understand That There’-s Much More to Being a Good Pollster.
Appreciate Innovation.
Do Some Polling.
UPDATE: Prof Andrew Gelman’-s take.
