Nate and I just returned from a week in the Bay Area for meetings and had the opportunity to spend the final two days of our trip attending an O'Reilly foo camp. Typically these are held at O'Reilly headquarters north of San Francisco but this time Google offered to sponsor the event so we spent two days shuttling between 6 conference rooms at a Google satellite office.
There have been several foo camp predecessors but this one was focused specifically on collective intelligence. The format of the "camp" is intended to be the "anti-conference" where the first half hour we collaboratively create the 2-day schedule by filling in time slots with sessions we want to lead. I thought this was going to get a little out-of hand even though attendees were invite only and limited to about 50-60 people but it actually turned out pretty well with at least one session each hour that was of interest and people with similar interest/backgrounds putting on sessions together.
Robin Hanson and I signed up to do a session on corporate prediction markets early in the camp which was fairly well attended although I thought we were driven to spend too much time talking about the potential for market manipulation and not enough brainstorming new ideas. Also, while everyone had a general understanding about prediction markets, there was still very little understanding of how they are actually being used so we spent most of the time talking through use cases.
In terms of overall takeaways from the camp, although not directly discussed, there was certainly re-enforcement of the old garbage-in, garbage-out syndrome; that even if you get a "collective" together, if they aren't incented appropriately (and I don't mean prizes) and they don't have relevant knowledge, just because you've put a group together, you're going to get garbage out. This was most evident when we talked about failed collaborative projects involving wikis, but certainly applies to corporate prediction markets as well in terms of the questions you ask, the people you involve, and the information available to the traders to act upon in the market.
Also after attending a data visualization talk it made me think later how we have just been scratching the surface in terms of gaining insight from trading data, market performance, etc. The recently published Google paper delved deeper in to this area - marrying trading data with demographic data but there is an opportunity to go much much further. We have some big things to get done in the next month but I suspect our focus may turn to this area sooner rather than later.
Finally it was noted by one attendee during an end of day recap that in every single session, the topic of incentive and reputation came up. This is clearly an area those working on collective intelligence driven applications must crack in order to be successful. We've done lots of thinking on this too, but we'll save it for another post.
All in all it was a great way to spend a couple days. Even better than the sessions themselves were the conversations we had in the hallways and during breaks and meals. A few people we already knew, but many whose books we've read or blogs we follow we got to meet in person. And of course this is the primary gravitational pull of Tim O'Reilly. His company writes lots of good books, but there probably isn't a bigger node in the technology space to bring together, as he said in his opening remarks, "the people who should know each other."
And on an unrelated note, if you're ever in Mountain View and you need to find a place to work at night, try the Red Rock Cafe. We worked in to the evening multiple nights there and it's fairly work friendly. Big upstairs area with plenty of desks and outlets. Our only complaint: they turned up some pretty bad music way too loud. :)
