Let’s ask a tough question: Will Hillary Clinton become president of the United States in 2016?
If you had people “bet” on the topic, and monetarily rewarded the ones who guessed correctly, you can actually get a good idea whether Hillary Clinton will become the head of state. A better idea, in fact, than virtually any alleged “expert” could give you.
It would work as follows: A market would be opened in which possible answers to the question (yes or no) are “stocks” that cost anywhere from 1 cent to $1. Automatically, the market price of the “yes” and “no” would reflect the possibility of Clinton’s election. So if a share of “yes, Clinton will be elected” costs 63 cents, then the likelihood of her being elected can be understood as 63 percent.
The option worth more (yes or no) is probably the right answer.
Since humans care about their money, this market data can provide accurate aggregated information for a myriad of purposes.
This is called a prediction market, a market where investors can buy and sell predictions about the outcome of an event.
Robin Hanson, Ph.D., professor at George Mason University, was one of the first people to start writing about prediction markets in 1988 and has been working on related projects ever since.
“Prediction markets became more popular around the dot-com boom,” says Hanson. “Presently, there’s been more activity in it.”
There’s been more enthusiasm for prediction markets in academia than in industry.
“Academics have been more willing to test the market’s claims, while businesses are less eager to adopt them – regardless of the fact that repeated trials tend to find that they are more accurate than status quo mechanisms,“ says Hanson.
“For example,” he said, “some of the most dramatic and successful prediction markets have been about deadlines. The question has been stated as: Will this project make its deadline? There are number of dramatic cases where management and officials forecast ‘yes’ and the prediction market data reveals that the answer is in fact ‘no.’ It’s not necessarily information organizations want to make publicized. This is the main barrier to widespread adoption of prediction markets: demand. Not enough people in these organizations want the product that prediction markets claim to produce.
“Prediction markets,” continues Hanson, “claim to produce uniquely accurate estimates and provide more accurate data than can be acquired from anywhere else. They’re a relatively cheap, robust manipulation; they’re timely, precise; they give you the tools necessary if you needed information and you wanted to make it known to people in an organization.”
Past implementations of prediction markets on the Internet did not succeed in the long-term. The most popular was Intrade.com.
Intrade.com, based in Ireland, was a web-based “trading exchange” where users “traded” contracts on the probabilities of various events occurring. They even allowed users to speculate on gold and oil.
In 2012, however, the U.S. Commodity Futures Trading Commission [USCFTC] filed a complaint in federal court claiming that Intrade solicited American customers to trade investment contracts that technically are options. Options can be traded only on approved, regulated exchanges.
Since Intrade was not a licensed exchange, they were forced to exclude U.S. users in 2012, and on March 10, 2013, Intrade ceased all trading.
“Intrade was a place where users got a chance to prove themselves and bet,” says Hanson. “That product, however, was limited by anti-gambling laws.”
In 2015, like many other industries, businesses and software models, prediction markets are now being implemented on blockchain technology. There is a dedicated team of individuals building what will be the world’s first decentralized prediction market platform that goes by the name Augur.
Augur plans to allow users to create their own peer-to-peer prediction markets.
“The important thing here,” says Jack Peterson, core developer at Augur, “is that it is a decentralized system. There’s no single point of failure.”
The Augur team is fully aware of past struggles of centralized prediction markets. “We’re making software,” says Peterson. “We expect the user to follow their respective jurisdiction’s laws. Our whole team has a stipulation in their employment agreement to not create, or participate in, markets on the platform.”
Regarding the upcoming software token sale, Peterson stated: “Augur’s tokens (called Reputation) occupy a unique niche. They are not used in its prediction markets; these are cash markets. Rather, the tokens are used only to report on the outcomes of events, after the events occur. Since this reporting is done after the event happens, no skill at making predictions is required. All that is required is honesty: Augur is designed so that those who report honestly will automatically gain more tokens – at the expense of lazy or dishonest reporters.”
Augur has maintained day-to-day contact with attorneys from Wilson & Sosini and Pillsbury Winthrop throughout the development of their platform. Additionally, they’ll be having a token sale in June. The team is currently finishing up the first version of their software.
“We want to launch Augur as soon as Ethereum is ready to make sure that everything is in sync with the live network,” Peterson said.
Prediction markets have a clean argument for their use and consistently pass tests of accuracy and user satisfaction. Nevertheless, most organizations are not interested in using them.
When Bitcoin Magazine asked Hanson why he thought this occurred, he replied, “It seems to be that the information that they provide is threatening and problematic, politically.”
These prediction markets can provide information that is detrimental to the status quo, and, in simpler terms, tell people/organizations things that they don’t want to hear.
“Do we really want the capability to do that?” Hanson asked. “A lot of people think they do. We’ll just have to wait and see if it’s true.”
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