SciCast Prediction Market Offers Collaborative Forecasting
SciCast is a crowdsourced forecasting platform based on the idea that the collective wisdom of an informed and diverse group can be gathered and used to accurately predict future events.
(SciCast crowdsourced forecasting platform )
Unlike other forecasting sites, SciCast can create relationships between forecast questions that may have an influence on each other. For example, we may ask a question about the volume of sea ice in the Arctic in a given month. We may also ask a question about average temperature in this same locale or other influencing metrics. SciCast will learn from its participants how strong of a relationship these questions have to each other and will adjust their outcomes accordingly. So, if participants raise the forecasted average Arctic temperature, SciCast will instantly adjust forecasts for the corresponding level of Arctic sea ice, according to the correlations made by previous forecasters…
SciCast is a community-driven initiative. Participants write their own questions in our publishing tool called Spark and participate in a process to get those questions published. SciCast participants can make forecasts at any time about any published question. Unlike a survey, participants can change their forecast at any time to account for new information. In this way, SciCast is a real-time indicator of what our participants think is going to happen.
Technically, SciCast is a (combinatorial) prediction market. Prediction markets can be used to forecast the outcome of a wide variety of topics and are used today in large corporations and governments to understand the likelihood of meeting key performance metrics, quantify risks that may jeopardize operations, and better understand industry trends.
In his 1975 novel The Shockwave Rider, John Brunner introduces sf readers to the idea of a Delphi pool:
It works, approximately, like this.
First you corner a large - if possible, a very large - number of people who, while they've never formally studied the subject you're going to ask them about and hence are unlikely to recall the correct answer, are nonetheless plugged into the culture to which the question relates.
Then you ask them, as it might be, to estimate how many people died in the great influenza epidemic which followed World War I...
Curiously, when you consolidate their replies they tend to cluster around the actual figure as recorded in almanacs, yearbooks and statical returns.
Well, if it works for the past, why can't it work for the future? Three hundred million people with access to the integrated North American data-net is a nice big number of potential consultees.
(Read more about Brunner's Delphi pool)
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