SciCast participated in the TechCast Webinar Series on May 7, 2015, Forecasting in Turbulent Times: Tools for Managing Change and Risk.
The webinar covered The SciCast Prediction Market (Charles Twardy), Cybersecurity Markets (Dan Geer), and Near and far future of AI (Robin Hanson). Read the full description. There were a few questions after each segment, and some more at the end. (Hanson fans: note that Robin’s talk was not about markets this time, but a particular scenario extrapolation using economic reasoning from some strong initial assumptions, and the subject of his forthcoming book.)
@IntellInside: “I believe that more and more people have become adept at going directly to amazon.com to search, whereas for Walmart they are more inclined to use Google search….”
The market is better calibrated than we thought, but not perfect. In our previous calibration post, each question counted once. In the chart below, each forecast counts once, which is the usual method.
Because SciCast strives for continual improvement and also needs even more participants and forecasts than in previous years, we have been exploring the effectiveness of incentives, particularly monetary incentives, for increasing the quality of participation in a prediction market. This post is the first of a five-part series to summarize the first two incentives studies as we start a third. (Parts of this series of posts are based on previous technical reports unavailable to the public.) This first post lays out the goals, hypotheses, and background of the incentives studies. If you’ve been participating in SciCast for a while, you might better understand some of your own experiences after reading this. Continue reading →