Red-Balloon Incentivised Economic Model

Steven Levitt and Stephen Dubner in their hugely popular book, Freakonomics: A Rogue Economist Explores The Hidden Side Of Everything stated;

“Economics is, at root, the study of incentives.”

Economic incentives are what motivates people to behave in a certain way, to follow a certain set of rules and to put it most simply, do more of a good thing and less of a bad thing. Levitt and Dubner continue;

The typical economist believes the world has not yet invented a problem that he cannot fix if given a free hand to design the proper incentive scheme. [To an economist] an incentive is a bullet, a lever, a key: an often tiny object with astonishing power to change a situation.

Economic Policy Instruments (EPIs) are incentives designed and implemented with the purpose of adapting and motivating individual decisions to collectively agreed goals.

Similarly, recursive incentive models are designed to motivate, however instead of motivating the individual they are designed to motivate the collective to bind together to achieve goals and solve problems.

However this mode of thinkings is far bigger than engaging networks, it is about designing a smarter way to organise and engage large groups of people to solve a problem. Any problem.

The Red-Balloon experiment

In December 2009, 10 red weather balloons were deployed from locations throughout the United States. The task was simple, find the balloons.

However the reason for the project was more nuanced. It was testing the mettle and effectiveness of social media as a tool for connectivity.

The Red Balloon Challenge, sponsored by the Defense Advanced Research Projects Agency (DARPA) of the U.S. Department of Defense, laid out a simple objective: Use social media to identify the GPS coordinates for all 10 balloons, suspended at fixed locations across the country.

The first team to do so would win $40,000.

The challenge, celebrating the 40th anniversary of the Internet, highlighted social networking’s potential to solve problems using widely distributed, time-critical social mobilisation.

According to DARPA, “a senior analyst at the National Geospatial Intelligence Agency characterised the problem as impossible” using conventional intelligence-gathering methods.

The winning team, a group of MIT students, found all of the balloons in under nine hours.

How?

They used a recursive incentive structure to engage existing networks of people to work together more effectively.

In a recursive incentives the chain of connectivity will always have two fixed points of certainty.

You will have a finished state of a chain (completing task, being hired, reaching the moon whatever) and a beginning state of a chain (when someone can’t complete the task themselves).

The person who starts the chain will always receive the least reward, and the person who completes the task will always receive the most.

The people in this chain that are in the middle these two points will of course receive recursive rewards based on where they are in the chain.

The reward will halve itself at every link in the chain from the last link, to the first link.

So in the case of the MIT Red Balloon challenge, their incentive structure worked as follows;

The team promised $2,000 to the first person who submitted the correct coordinates for a single balloon, and $1,000 to the person who invited that person to the challenge. Another $500 would go to the person who invited the inviter, and so on.

Alex “Sandy” Pentland, director of the Human Dynamics Laboratory in the MIT Media Lab.

“Humans are really social animals. We live in this web of social relationships, and a lot of what we do and the satisfaction we derive comes from the web of social relationships. So if you want to get people to coordinate or change their behaviour, you have to first and foremost deal with the existing web of relationships, rather than treat people as isolated individuals.”

This experiment provided the insight for the nCent protocol, however when using a blockchain this model can scale so much further.

This is because of trustless incentive markets, where anonymous people can work together without needing to trust each other, while still being confident they will receive a reward proportional to the work they contribute.

At scale, with the help of blockchains, trustless incentive markets will function as a conductor of much greater social change than merely finding balloons.

The NCENT Telegram Crossword

nCent recently completed the worlds-largest collaborative crossword. Further than just a fantastic community building and education exercise, this was a very successful example of both recursive incentive models and the core insight of nCent itself: connectivity of engaged networks.

The Crossword

Words from the litepaper, were released as clues at random intervals on Telegram as to not disadvantage people in different timezones.

Points were awarded to people who solved the word first. The incentive? 1ETH to the top three scores and to the first to submit a picture of the completed puzzle.

However when the incentive became recursive, the group quickly swelled from a few hundred people to 20,000 in a few weeks. The humble Telegram group had gone viral.

It was decided to reward people for recruiting others to help solve the problem. If someone you referred earned points, a chain would be formed and you would also receive a reward.

The chain rewards worked as follows; a word solver would receive 16 points, the parent (referrer) of the solver would receive 8 and the grandparent would receive 4, and so on.

All of our winners had built a strong chain of referral, and not relied on trying to solve the problem themselves.

This fun and small scale exercise was incredible successful but is only a snapshot of the unlocked power of dormant networks.

A crossword puzzle with 3 ETH on the line engaged a community of over 20,000 people in just a few days. Imagine if that same dynamic could be scaled and directed to solve all kinds of difficult problems such as connecting communities to address failing education systems or on a more grand scale engaging more Americans to vote and participate in our representative democracy.

To re-quote Levitt and Dubner, “economics is, at root, the study of incentives”, so with the right model of incentive any problem can be solved.

It also become apparent to me that incentive markets are not just outcome driven mechanisms, but also models for education.

This is an important duel-edged benefit for consideration when thinking about future use-case scenarios of incentive markets.

Summary

Recursive incentive structures are far bigger than blockchains, or NCENT, as these are instruments that create connectivity and collaboration amongst people (both on-chain, and in the real world).

When all of these elements comes together (recursive incentives, blockchains, and NCENT) trustless incentive markets are created, which allow people to work together with or without knowing each other (trusting each other), and can still be confident that they will receive reward proportional to their contribution.

This is not only the future of greater connectivity and collaboration, but also a new solution to solving problems that were not previously thought possible using conventional methods.

A merit based model of interaction, that rewards those who contribute most to connecting compatible parties to solve problems.

This is not the future of blockchain, but the future of organising and motivating people to work collaboratively.

Red-Balloon Incentivised Economic Model was originally published in Hacker Noon on Medium, where people are continuing the conversation by highlighting and responding to this story.