Editor's Blog
You know it’s summer when newsstands across America have an explosion of magazines, typically meant to have shelf-life until fall, on the topic of do-it-yourself prediction. Over a dozen publications are offered to players of Fantasy Football, itself a $5 billion a year business, to help them create and manage teams that use statistics generated by actual games to determine who wins the fantasy games. Is it possible that this fall these fans could be the innovators and early adopters of a new and novel way to make predictions as entertainment in a variety of fields that are more vital to real world concerns, such as prices, markets, wars and weather?
Prediction is at the core of Western civilization – the Oracle at Delphi was consulted about war and more for over a thousand years – and being able to predict the future is something that millions are paid to do, and that billions of people do every day. Prediction is the claim that a particular event will occur in the future, given in specific terms and falsifiable over time. Predictive power is an important measure of truth. In science, predictive power is increasingly important when studying systems where provability is not an option.
Some sports fans are as passionate about predicting the outcome of games and being known as better guessers, in part to gain reputation and in part to win money by betting tens of billions annually in office pools and casinos. Watching a game in the NASA Mission Control Room-like Caesars Palace Race and Sports Book is on a number of “do before I die” lists.
Is there a way to be a better predictor? There is, by combining the best of open source models and crowd-sourced prediction. Open source is most familiar in the context of software, where it means software whose source code is freely available to anyone who wishes to have it, and who shares any improvements. The open source model allows for parallel input of multiple approaches, agendas, knowledge banks, and priorities with far more flexibility and speed than traditionally closed or centralized models. The idea of crowdsourced predictions is to use complexity to solve complexity: The wisdom of crowds has been discussed at length in a book of the same name.
Author James Surowiecki studies the aggregation of information in groups, resulting in decisions that, he argues, are often better than could have been made by any single member of the group.
This fall a young company called On The Record Sports (OTRS), based in San Diego, CA. will enable users to predict the outcome of sporting events on a multi-tiered scale with a simple interface – dragging and dropping, checking boxes, and moving a bell curve, allowing players to get points based on how many standard deviations they are away from actual outcomes. Users can predict the outcome of a single game, or the champions of the entire season. The predictions of millions of OTRS users would ideally display diversity of thought, decentralization, independence and aggregation. The “on the record” aspect relates to the fact that everyone’s predictions are locked in, and everyone will see where they ranked, allowing a sort of psychic Darwinism. The best predictions and the best predictors will be clearly identifiable, and the methods and mechanisms of prediction can be studied through analysis of OTRS data. Making predictions is free, but a user has to be a paying member of the Champion’s Club to see exactly where one ranked, and to be able to see the aggregate predictions prior to each game.
OTRS makes possible a scalable, massively crowd-sourced open prediction model, allowing recorded, ranked predictions to be made millions of times an hour. The data gained will not only apply to the world of sports; the implications stretch from complexity theory to neuroscience to artificial intelligence. It is an academic’s dream, and a sports fanatic’s hobby. An OTRS patent pending relates to prediction as entertainment. OTRS has far-reaching implications, but it appeals to the human spirit of competition: prediction is a sport in itself. Prediction reflects one’s ability to comprehend reality enough to say what will happen next. Predictive entertainment is recreational, and will provide unparalleled insight into the wisdom of crowds, and into the nature of intelligence itself.
The implications stretch from complexity theory to neuroscience to artificial intelligence. It is an academic’s dream, and a sports fanatic’s hobby.
If predictive entertainment ends up with the same “S-curve” growth as the Internet itself, humanity could develop a sort of social superorganism superpower of precognition. Being able to have billions of times more data about the future predictions could help to predict the weather (Katrina damage was more costly than 9/11), markets (better models of mortgage defaults could have saved trillions), wars (the Iraq war cost over 50 times what was predicted by George W. Bush), and even climate change (“cap and trade” is a decision with trillion dollar implications).
In the end, prediction as entertainment could help us to reinvent politics, markets, management, science, even the nature of what it means to be human. Next time you hear someone make a prediction about a game, give him a hug or buy her a beer, because a tiny bit of salvation is in the process of unfolding.
9 Comments
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Interesting article. But the major question I have is: People can predict things like sports games because they can watch their teams and players on TV/Internet or in person and learn their actions/movements well enough to possibly predict their future actions and success against other teams. People have the ability to actually gain knowledge and make money on sports betting. How would this translate to climate change? That is something that scientists with expensive instruments track over decades — how would the so-called crowd be able to study climate change with any type of intelligence? Without data to back it up, predictions/betting for climate change would be random guessing and/or based on media perception.
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Fascinating write-up. However the main query I’ve is: Individuals can predict issues like sports activities video games simply because they can view their groups and gamers on TV/Internet or in individual and discover their actions/movements nicely sufficient to probably predict their long term measures and good results towards other groups. Individuals have the capability to really acquire information and make cash on sports activities betting. How would this translate to local weather alter? That’s some thing that scientists with costly instruments track more than decades — how would the so-called crowd be in a position to examine local weather alter with any kind of intelligence? With out information to back again it up, predictions/betting for local weather alter could be random guessing and/or primarily based on media notion.
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But the major question I have is: People can predict things like sports games because they can watch their teams and players on TV/Internet or in person and learn their actions/movements well enough to possibly predict their future actions and success against other teams. People have the ability to actually gain knowledge and make money on sports betting. How would this translate to climate change? That is something that scientists with expensive instruments track over decades — how would the so-called crowd be able to study climate change with any type of intelligence? Without data to back it up, predictions/betting for climate change would be random guessing and/or based on media perception.
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Very Interesting article! That’s some thing that scientists with costly instruments track more than decades. Without data to back it up, predictions/betting for climate change would be random guessing and/or based on media perception. Thats very important “In the end, prediction as entertainment could help us to reinvent politics, markets, management, science, even the nature of what it means to be human. Next time you hear someone make a prediction about a game, give him a hug or buy her a beer, because a tiny bit of salvation is in the process of unfolding.”
I could have predicted losing money in your “paper” company had I simply done some research. Successful CEO’s focus on things like marketability and profit. They don’t focus on Isaac Asimov type future-tales. Lesson learned = you can largely predict someone’s future largely from whether or not they learned from their past.