The past does not repeat itself, but it rhymes — Mark Twain.
We can learn to predict the future by generalizing sets of specific transitions in sequences of reported news events and data. We can learn from news data about events in specific countries to build classifiers that consider the likelihood of events on a continent or to regions characterized by particular demographic and geological properties. This effort needs a diversity of crowd participation.
The larger participation and the more diversity is the crowd. The more people who have relevant information who participate, the better. In practice, predictions with even as little as twelve experts participating in any given contract in the market. We would still argue that while 12–20 people are a good number for crowd predictions, it is probably a better idea to include more people.
Crowd size led to better performance when the crowds were more diverse.
The rapid deployment of technology and the shifting demographics of people made businesses much more complex. But an evolution is under way, and people now are beginning to realize that diversity means the breadth of perspective. Where individuals who are experienced, responsible and collaborative and an environment in which challenging issues can be confronted, opposing opinions are sought and trust is implicit.
Stox is an open source, blockchain-based platform for prediction markets where people can predict the outcome of events in almost any imaginable category. The platform targets mainstream audiences and provides a venue where users can enjoy predicting everyday events in real time, and potentially profit from the outcome.
Having multiple views on the possible outcomes of any action makes for a prediction process that is more likely to take into account the various risks, consequences and implications of possible actions. A diversity allows for the crowd to better anticipate and consider the concerns and perspectives of all key factors.
Being able to draw upon a diverse set of competencies and knowledge is essential if prediction markets are to successfully address the complex issues.
