What makes a Crowd Wise

The “Wisdom of Crowds” is a well-respected theory that suggests that large groups of people are collectively smarter than individual experts when it comes to problem solving, decision making, innovating and predicting. This theory was popularized by James Surowiecki in his 2004 book, The Wisdom of Crowds yet the origin of the theory was popularized about a century earlier. In 1907, Sir Francis Galton asked 787 villagers to guess the weight of an ox. None of them got the answer correct, but when Galton took the median score of their guesses, he arrived at a near perfect estimate and that near perfect estimate was more accurate than most of the individual by themselves.

A more modern, yet imperfect example of the wisdom of crowds is the famous show “Who Wants to be a Millionaire?” hosted by Regis Philbin. A contestant had the chance to win $1,000,000 if they answered correctly a series of questions. If a contestant was stumped on any given question, they could exercise a few options to assist them. The options included one of the following:

Ask the Audience— The audience would immediately cast votes via a computer;

Phone a Friend— a person singled out as one of the smartest people the contestant knew; or

Have 2 out of the 4 options removed— (50/50 chance at being right).

As it turns out, the “Ask the Audience” option ended up getting the question correct 91% of the time compared with the “Phone a Friend” option which was successful about 65% of the time. It was the audience’s independence and diversity which allowed it to be collectively wise. There are many studies to demonstrate the effectiveness of the wisdom of crowds when applied directly but that’s not the point of this piece.

According to the academic literature, the conditions necessary to have a wise crowd are as follows:

1. Diversity of Opinion: Each person should have private information

2. Independence: People’s opinions aren’t determined by the opinions of those around them

3. Decentralization: People are able to specialize and draw on local knowledge.

Let’s explore what happens when those conditions are not present.

If crowds are so wise, why do bubbles occur?

This is a fascinating question, and the one we (at Proof) hear the most as it relates to the wisdom of crowds. What about “the herd” or “mob mentality” … well, let us take a look at that. Financial markets are great example of how crowds can fail miserably. Financial markets are diverse, however they are not independent. To understand this completely, I recommend reading The (Mis)behavior of Markets a seminal book written by the “Father of Fractals” Benoit Mandelbrot, that corrected most of the textbook finance I learned in college and confirmed what I witnessed first-hand on Wall Street.

Financial bubbles are plentiful, the famed tulip crisis, the Stock Market Crash of 1929, Black Monday in 1987, the Financial Crisis of 2008, and so on… According to the finance textbooks, the odds of each of these crises occurring are actually quite small. What Mandelbrot found is that large changes in prices, of more than five standard deviations from the average, happened two thousand times more than probability theory or more specifically, a Gaussian distribution would suggest. In his book, Mandelbrot provides a great example to highlight this; on a single day, the U.S. dollar gained 3.78% vs the Japanese yen. At that time, this move was 5.1 standard deviations from the mean. Under a Gaussian distribution, that would be expected to happen once in a century. In fact, it happens quite often. Let’s continue…

On a separate occasion, there was a fall of 7.92% or a 10.7 sigma event. According to a Gaussian distribution, if we were to trade currencies for 15 billion years, that type of event should have not occurred. Ok, so the traditional models are wrong, why is this important? The point is simply, humans are unpredictable and when operating in markets, do not fit normal distributions.

Wait, aren’t humans rational?

It depends. Why are market participants not rational actors? Consider the following game that Mandelbrot poses. Imagine a person can flip a coin to win $200 if it lands on heads, or they can skip the toss and collect $100 immediately. Most people will skip the toss and take the $100. Now, let’s change that a bit, suppose they can flip a coin and will lose $200 if it lands on heads, or they can skip the toss and pay $100 immediately. In this scenario, most will take the gamble rather than the safer route. When the element of risk is introduced, rational actors become quite, well… irrational. The two scenarios are identical except the potential of loss alters their behavior.

Back to markets. The point is, price dependency occurs because of the tendency for people to follow one another even when it is illogical, otherwise known as “the herd” mentality. You must be asking yourself, “didn’t you say that crowds were wise?” Yes, I did, and they are, but under the right conditions. When behavior is not independent, crowds become mobs. Let’s take a look at a great example provided by Surowiecki in his book. In the late 1950s, bowling, yes I said bowling, was the rage, it was referred to as “the people’s country club.” In this time period, if you had a bowling related idea, people were happy to give you money. By 1960, there were 12,000 alleys, with a total of 110,000 lanes and $2 billion in capital poured into the industry. Wall Street, of course perpetuated the frenzy with analysts arguing that soon every American would be bowling 2 hours a week. You can probably guess the rest, by 1963, the stocks crashed over 80% from their peaks and it took nearly a decade for them to reclaim the lost ground. Fun fact! Today, there are about half as many bowling alleys nationally as there were forty years ago, even though there are 100 million more Americans. You can replace the word bowling with ripple, rare earth metals, junk bonds, tulips and really not much would change. These cycles repeat because of the way markets are constructed and because of price dependency.

Prices are one of the mechanisms that perpetuates mob mentality; they elicit emotion and greed rather than truth and pragmatism from participants. It is probably for this reason that prediction markets incorrectly predicted seminal events such as the Brexit Vote or the 2016 United States election. Experts have argued for decades that asset prices follow a Brownian motion or follow a Random Walk. Their point is that every time a price of a stock flashes on a screen, it is independent of the last trade or any other trade before that. This is incorrect. In fact, each price is dependent on all its previous prices. Price dependence is actually quite important as it relates to the wisdom of a crowd. In fact, in a bubble, all the conditions that make groups collectively intelligent, completely disappear. It is not price alone however, price and liquidity combined, increase irrationality. The Greater Fools Theory is based on the notion that the price of an asset can be justified to a person by the belief that another party is willing to pay an even higher price for it (call it a hot potato…). This speculation is what creates the perfect environment for bubbles and why markets can be quite poor “weighing” or “voting” mechanisms at times.

So far, we have established that not all crowds are wise and that the necessary conditions present in a mechanism are what allow a crowd to be wise.

Proof is a platform designed to elicit a Wise Crowd

At Proof (www.proofmedia.io), we are building a platform to evaluate the truthfulness of online content. Drawing on the literature of the wisdom of crowds, we carefully constructed a voting mechanism that elicits the truth from a group of diverse, independent and decentralized voters. We will be releasing more details shortly on our voting mechanism and how you can participate. For now, please visit our website and subscribe for more information to stay up to date on our developments.