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In his seminal 1945 essay, The Use of Knowledge in Society, Economist Friedrich Hayek argued that market prices are the means by which disparate pieces of information are aggregated.

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Hayek wrote that what’s in a single person’s head is only a small fraction of the sum of total knowledge held by people in society.

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“Economic problem of society is thus not merely a problem of how to allocate “given” resources … it is a problem of the utilization of knowledge which is not given to anyone in its totality.”

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But what if we could unlock that information?

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What if we could leverage the wisdom of the crowds in a systematic way — if we could separate the experts from the charlatans — and then have the experts weigh in on crucial decisions?

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What if we could aggregate people who are working on the front lines of national security, public health, drug development, movies, government funded projects, trade agreements, banks — and ask them whether their initiatives are on track?

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For example, what if, instead of asking, say, Elon Musk when we’re getting self-driving cars, we could ask all Tesla employees working on them directly?

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What if, more broadly, everyone had skin in the game for their opinions? What if people had a financial incentive to be diligent in their predictions? What if people put their money where their mouths are? Could this help us make better decisions?

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That is the hope and promise of prediction markets.

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Prediction markets are effectively betting markets for the purpose of predicting something we want to know — to discover what people truly believe.

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For example:

  • Will X happen?
  • If X happens, will Y happen?
  • If X happens, what will the change in Y be?

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The most popular prediction markets exist in sports and politics, but effectively, futures contracts, bounties, and insurance agreements are all prediction markets in that they use people’s desire to make money to predict the future.

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Stocks, in contrast, are memes that have some cash flow (via dividends) but really are priced via speculation. Prediction markets always resolve back to some objective thing in the world.

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Prediction markets purchase information from people who know the future, or at least are better at forecasting it. The market represents the public’s best guess as to what will happen. And people with information about the future are given money for divulging it.

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Why are Prediction Markets so important?

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“The pace of scientific progress may be hindered by the tendency of our academic institutions to reward being popular, rather than being right.” — Robin Hanson

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At the highest level, prediction markets are so important because they can lead to better decision making. If we believe that more accurate information is a positive thing, an improvement in accurately valuing certain possibilities can lead to stronger governance and management.

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There is currently little accountability for predictions. Politicians make baseless predictions with no accountability, while the media profits from sensationalist journalism. Pundits of all stripes have no skin in the game. Even when they get things wrong, they typically don’t go back to correct themselves. Experts don’t have incentives to speak up. Too much to lose.

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Charlatans, however, make baseless predictions to build an audience. If they’re wrong, their tribe still supports them. Celebrities are winning The War of Ideas. Tribalism above truth. Entertainment over everything.

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In an era of fake news, prediction markets can make a big impact.

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Indeed, prediction markets are truth-seeking machines. By forcing people to put their money where their mouths are, people now focus on being correct, rather than being liked, popular, or diplomatic. If they’re unwilling to bet, they’ll be discredited. If they’re wrong, they’ll lose money and reputation. Vice versa, if they win, expertise will be elevated, humility will be appreciated, and charlatanism will be eliminated.

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It’s not entirely wisdom of the crowds — it’s wisdom of the “right” crowds — the experts. And, just as important, it silences (or cripples) the blowhards. If you don’t know what you’re talking about, you’ll abstain from voting, because, if you don’t, you’ll lose all your money.

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How could this be used in the wild?

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Consider a board determining whether it should hire or fire a CEO. It could decide based on its own instincts, or it could aggregate insights from the employees. A corporation could ask, “What will our Q1 revenue be if we fire our CEO?” and conversely, “What will our Q1 revenue be if we don’t fire our CEO?”

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Another example: Movies. Movies have huge fixed costs and are difficult to MVP. Will X new movie do well? Employees can assess whether the movie will be ready in time, as good as initially envisioned, and whether people would like it.

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History

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Where did the modern concept of prediction markets originate?

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Prediction markets today are a more specific form of the generalized concept of “crowdsourcing” or using the wisdom of the crowd as a means to better understand the true nature of reality. Using the crowd for this purpose has been discussed as far back as the 4th century BC by Aristotle.

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“It is possible that the many, when they come together, may be better, not individually but collectively, just as public dinners to which many contribute are better than those supplied at one man’s cost. For where there are many, each individual, it may be argued, has some portion of virtue and wisdom, and when they have come together, just as the multitude becomes a single man with many feet and many hands and many senses, so also it becomes one personality as regards the moral and intellectual faculties.” — Aristotle, Politics

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In modern times, there is the famous example involving hundreds of people attempting to estimate the weight of an ox at a county fair back in 1906 in England. It was observed then that the median guess (1,207 pounds) was accurate within 1% of the true weight (1,198 pounds).

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Prediction markets combine the Wisdom of the Crowds with the Efficient Capital Markets hypothesis (stating asset prices reflect all available information providing the best estimate of intrinsic value).

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Over the past 20 years, these concepts have been applied more broadly to such diverse topics as business project deadlines (Project Xanadu), intelligence analysis (DARPA’s experimentation), and box office success (Hollywood Stock Exchange).

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Common Criticisms

There are several criticisms and challenges against the wide use of prediction markets. We can divide these into three main buckets:

  • Established power structure
  • Implementation challenges
  • Causal relationships
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Established power structure

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If we think about why things do or do not happen in our society, the typical drivers of change are the powerful (e.g., wealthy families, leading corporations, and political leaders).

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The powerful typically act in their own self interest to hold on to their power in whatever form it is in. Robin Hanson’s Elephant in the Brain goes into depth how people are adept at rationalizing why the interests of the powerful are also the collective best interest.

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Prediction markets, however, threaten the hierarchical control of top managers, by demonstrating that most managers can’t predict the future. If prediction markets work as they should, they would diminish the power of those in control and give more of a voice to everyone else. While this could improve society as a whole, it could worsen the standing of the powerful.

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There is also a view that without centralized moderation, communities inevitably collapse into mediocrity and chaos (essentially, Eternal September), so having a small number of users in charge could be a necessary evil.

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Implementation challenges

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In terms of implementing prediction markets, there are two major factors to consider: (i) the cost of running & maintaining the markets and (ii) the clarity of the markets & associated outcomes.

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Currently, most major prediction markets are run by centralized teams and platforms. These teams are important as they create new markets, maintain the integrity, handle disputes, etc.

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As a consequence, there are fees associated with these types of markets, resulting in negative sum games. Prediction markets currently are more like gambling (either I win and you lose or vice versa) versus investing in most other markets (with a positive overall growth rate).

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For prediction markets to truly take off, we need to establish more positive sum situations by either substantially lowering the costs associated with these platforms or by proving their positive sum nature.

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Outside of cost, the clarity of the markets and outcomes can be a major challenge. Regarding the markets themselves, we need explicit language without any possibility of misinterpretation. If the market is that Steph Curry will hit a three in tonight’s game on June 10, 2019, what happens if the game is delayed and he doesn’t hit a three until 1am EST (on June 11). If the market is for a project to be completed by a certain date, how do you define “completed”? What if everyone thinks the project is done but then needs follow up work the next month?

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And if prediction markets are run completely decentralized, how do you prove that an outcome truly occurred (i.e., the Oracle Problem)? If the market is a sports game, do you trust ESPN even though ESPN is centrally run?

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Causal relationships

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The last major bucket of challenges is when betting performance impacts the actual results and can become self fulfilling prophecies.The proliferation of markets might mean everyone is operating under monetary incentives and the future becomes effectively deterministic because the crowd can not just predict, but also affect the future.

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This can lead to both severe negative consequences or positive ones. On the extreme negative side, this can lead to assassination markets or terrorist attacks. If there is a market for an individual to die on a certain day, one could be incentivized to make sure that occurs.

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Yet on the positive side, if there is a market for a certain project to be finished by a certain time, those involved could be financially motivated to ensure that it does get completed.

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Conclusion

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Despite these challenges, we believe prediction markets leveraging the collective of the crowd will end up being a net positive for society. As the importance of uncovering truth increases, and similarly, the cost of false information increases, the value of these types of markets will in turn become increasingly paramount.

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We are excited by decentralized projects such as Augur that are attempting to tackle these challenges. And we’re excited for the applications being built on top of these platforms as well as their centralized predecessors.

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Market Map

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Centralized Prediction Markets

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*Metaculus — Metaculus is a community dedicated to generating accurate predictions about future real-world events by aggregating the collective wisdom, insight, and intelligence of its participants.

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Hypermind — Hypermind harnesses the wisdom of an elite crowd to deliver the most accurate forecasts about politics, the economy, and your business.

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Good judgment — With the most extensive, independently verified track record of early foresight ever compiled, Good Judgment and its global network of certified Superforecasters are uniquely equipped to help you think more clearly about an uncertain future.

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PredictIt — A project of Victoria University of Wellington, PredictIt has been established to facilitate research into the way markets forecast events.

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Smarkets — Smarkets simplifies peer-to-peer trading on sporting and political events. Smarkets lets you set your own odds and trade against others with confidence.

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[Betfair]https://us.betfair.com/) — Paddy Power Betfair was formed in 2016 and is an international, multi-channel sports betting and gaming operator.

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Decentralized Prediction Markets

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Augur —Augur is a decentralized protocol for users to create their own prediction markets - it’s a set of smart contracts that can be deployed to the Ethereum blockchain.

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Gnosis — Through blockchain-based, decentralized platforms, Gnosis enables the redistribution of resources  from assets to incentives, and information to ideas.

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Veil — Veil is a peer-to-peer prediction market built on open protocols such as Augur and 0x, designed to bring Augur mainstream.

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Guesser — Guesser’s mission is to foster a community of people predicting the future by connecting them to the markets where they can invest in the outcomes of real world events. Built on top of Augur.

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BlitzPredict — BlitzPredict delivers a cutting-edge betting exchange focused on sports, esports and politics. Built on the Ethereum blockchain and powered by Augur and 0x, BlitzPredict harnesses the power of blockchain technology to deliver low fee, high transparency markets with reduced counterparty risk.

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Flux — Flux is a platform for peer-to-peer trading of derivatives on startups. Flux allows users to create prediction markets to trade startup milestones like product releases, investment rounds, and progress (or setbacks)

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Author

Erik Torenberg
Co-founder @Villageglobal, @tokendaily https://t.co/NnuJs4N1hU