Collective Wisdom Gets Decentralized


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Two heads are better than one. Unsurprisingly, this adage means that two people are generally better at solving problems than a single person. If you scale this concept up to ten, a hundred, or ten thousand heads, you’ll get what’s called “the wisdom of crowds” or “collective wisdom.” The wisdom of crowds — a phenomenon known to humankind for thousands of years — implies that large groups of regular people can be smarter than experts in certain fields.

The wisdom of crowds has been applied to solve complex tasks in engineering, corporate governance, environmental protection, and even search and rescue operations. When the Internet arrived and enabled people to communicate and collect data faster and easier than ever before, the concept of collective wisdom got a whole new life.

Now it seems that blockchain technology has also found a way to use this phenomenon on the emerging market of decentralized systems.

Wisdom of Crowds: Origins and Evolution

By definition, the wisdom of crowds refers to the principle which suggests that large groups of people perform better at solving problems, making decisions, and generating new ideas collectively. The principle itself was described back in the antiquity in Aristotle’s Politics.

“The many, who are not as individuals excellent men, nevertheless can, when they have come together, be better than the few best people, not individually but collectively, just as feasts to which many contribute are better than feasts provided at one person’s expense,” reads Aristotle’s Politics (Reeve Edition, 1998).

Aristotle emphasized that the better decisions made by a group of people come as the result of collective discussion and combination of pieces of information and contradicting arguments from different members of the group. The notion of the “collective discussion” or deliberation between the people is what differs the old definition of collective wisdom from the one that we use now.

In fact, the interest in the wisdom of crowds was rekindled by James Surowiecki’s New York Times bestseller somewhat unsurprisingly titled The Wisdom of Crowds. The book describes a notable example of a statistical experiment by a Victorian-era polymath Francis Galton, who asked roughly several hundreds of country fair attendants to write down their best guess about the mass of a slaughtered and dressed ox. As a result, the median from the submitted values was one pound off the actual weight.

Contemporary forms of applied collective wisdom no longer depend on a direct discussion between the participants. In addition, thanks to the power of the internet people have access to vast amounts of information, whether it is scientific research, public sentiment, or literally anything else. The same power allowed the systems utilizing collective wisdom principles to get opinions from thousands and millions of people of any background and skill.

However, such collective decisions aren’t always perfect.

How Does Collective Wisdom Work and Why Sometimes It Doesn’t

First of all, Surowiecki explained, it is important that people who contribute to a collective decision think independently and don’t discuss the issue in question with their peers. Otherwise, the median value calculated from the submissions may be affected by somebody’s bias that spread across the deciding crowd.

A research by Albert Kao, Andrew Berdahl et al. published in the Journal of the Royal Society Interface, examines the effect of individual bias and information exchange between the participants.

“There is growing evidence that the wisdom of crowds can be really powerful. A lot of studies show that you can calculate the average of estimates and that average can be surprisingly good,” says Albert Kao.

The researchers asked a group of over eight hundred people to guess the number of gumballs in different jars, which contained from 54 to over 27,000 pieces. As part of the experiment, they offered participants to peek at fake numbers represented as peers’ submissions and correct their own.

“However, there is a great deal of evidence that people have strong biases in estimation and decision tasks,” added Andrew Berdahl.

Ultimately, the scientists found out that people are likely to guess quantities lower than the actual amount and offer a bigger range of guesses for bigger containers. As for the effect of information sharing, it was found that people tend to account for the guesses that suggest bigger amounts of gumballs than their own estimations and disregard those suggesting smaller amounts.

As part of their study, Kao and colleagues found a mathematical method to correct collectively made answers and account for individual bias and information sharing.

Another important point with the wisdom of crowds is that it isn’t universally applicable. The principle generally works well with problems such as guessing the weight of an ox, counting gumballs, or forecasting election results, but in some cases, it is better to employ a smaller group of experts in the respective field than a large crowd of non-professionals.

Neither one nor a thousand non-professionals would be able to make judgments in certain technical or scientific fields of knowledge. For example, there’s research showing that groups of people are quite good at guessing things such as critical acclaim of popular movies, and not as good at forecasting national GDP changes, companies’ retail sales growth, etc.

Nevertheless, collective wisdom has been widely utilized over the last few decades.

Prediction Markets Today

The most widespread and well-known modern form of the wisdom of crowds is the concept of the prediction market, a virtual venue where people trade contracts on certain unknown future outcomes. Simply put, the price of a certain contract for a certain outcome indicates the crowd sentiment regarding the probability of such an outcome. For example, the more the participants believe Elon Musk will eventually send people to Mars, the more the price of the respective contract would be.

Public prediction markets are actively utilized to forecast election outcomes, news events, sales, box-office proceeds, etc. On numerous occasions, such markets offer better accuracy than pollsters or professional marketers. Today, there are numerous companies offering prediction market services to high-profile clients

Consensus Point, for example, works with General Electric, Motorola, and Best Buy. According to the website, at the moment of writing, the company facilitated almost 5 million predictions, tested almost 14,000 and engaged over 320,000 participants while keeping about 90% accuracy rate. Lumenogic works with Siemens, l’Oreal, Yahoo, Sony Music, and Bayer. The customer roster of Cultivate Labs, another major prediction market service provider, includes companies like Lockheed Martin, LG, Shell, and Twitch.

However, the concept of prediction markets bloomed again with the advent of blockchain tech. A new form of prediction markets emerged, this time based on decentralized trustless systems. By now, there is quite a few blockchain-driven prediction markets: Augur, Wings, Gnosis, and Stox.

Augur was a pioneer of blockchain-based prediction market solutions. The project was founded in 2014 and held an ICO in 2015, gathering about $11 million. Augur provides a protocol allowing users to create their own prediction markets on Ethereum blockchain. The protocol is distributed as open-source software and the creators of Augur are not involved in creating or operating individual markets. The protocol allows users to trade contracts for outcomes, using ETH tokens as a unit of value.

Gnosis was established in 2015 and successfully raised $12.5 million through the sale of its own GNO tokens. Just like Augur, it is based upon Ethereum blockchain and smart contracts. Apart from a protocol to govern prediction markets, Gnosis offers a trading interface for prediction markets, a cryptocurrency wallet, and an exchange for ERC20 token pairs utilizing the Dutch auction mechanics.

There’s also Wings, which is a bit different from the projects above. Wings utilizes its prediction market to evaluate new blockchain-driven projects. People use platform’s tokens to express their support to a project they find viable or simply vote for its rejection. The projects that pass such evaluation successfully become eligible for crowdfunding right there on Wings platform.

In the decision-making process, the platform offers users to share their forecast on projects viability and also the expected value of the evaluated project’s token that would result from the forecasted outcome. After a fixed amount of time, the expected and real value of the token in question are compared and the most accurate forecasters are rewarded.

Prediction Markets Tomorrow

It would be safe to say that blockchain is not the final form of prediction markets evolution, although it is the latest one for now. Compared to the “traditional” platforms, blockchain-based prediction markets offer trustlessness, meaning that the platform operators are unable to mess with the data and manipulate it to their benefit.

Another important distinction is that many projects in the niche provide their users with all the tools needed to build and operate their own prediction markets.

As for the role of collective wisdom and prediction markets in the broader picture, it anything but neglectable. Large corporations and governments rely heavily on the wisdom of crowds in making their own decisions, and it’s been like that for years.

With decentralized prediction markets, more people are accessing the collective wisdom to share and gain knowledge about their potential investment targets, destinations for vacation and whatever else they would like to have a forecast for. After all, it’s quite pleasant to have at least a little glimpse of the statistics and probabilities of tomorrow.

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