"In evaluating prediction markets (and other crowd-prediction mechanisms), investigators have repeatedly observed a so-called "wisdom of crowds" effect, which roughly says that the average of participants performs much better than the average participant. The market price---an average or at least aggregate of traders' beliefs---offers a better estimate than most any individual trader's opinion. In this paper, we ask a stronger question: how does the market price compare to the best trader's belief, not just the average trader. We measure the market's worst-case log regret, a notion common in machine learning theory. To arrive at a meaningful answer, we need to assume something about how traders behave. We suppose that every trader optimizes according to the Kelly criteria, a strategy that provably maximizes the compound growth of wealth over an (infinite) sequence of market interactions. We show several consequences.…"

"More broadly, a simple dictum such as ‘listen to the experts’ isn’t going to work, precisely because our most powerful methods of generating new knowledge (viz. the sciences) are not so much based on listening to individual experts, as on including these experts (and many others) in broader social systems which expose them continually to the ideas of others and vice-versa. Designing (or – perhaps better- nurturing) such systems is hard to think about and hard to do – but it has to be the way forward."

"It’s informed groupthink at its finest." -- A great quote, but I really like the whole discussion.

The Wisdom of Crowds (WOC) theory does not mean that people are smart in groups—they’re not. Anyone who’s seen an angry mob knows it. But crowds, presented with the right challenge and the right interface, can be wise. When it works, the crowd is wiser, in fact, than any single participant.

"Most large organizations have a "top-down" central planning function, although they operate externally within a "bottom-up" (market) economy. As the business environment becomes more complex, top-down planning systems have been hard pressed to adequately understand and effectively respond to the quickly-developing challenges.

To cope with the complexity, some leading organizations are introducing more market-based BI systems to help with organizational decision-making. One of the emerging practices is called, prediction markets."