Incentive markets work well when they can correctly attribute the value that each member brings to the network. Take, for example, the Red Balloon Challenge, which challenged the general public to find ten red balloons scattered throughout the United States. A successful network would incentivize someone to find a red balloon, obviously, but it would also incentivize people to spread the word and recruit others in the search. In a previous article we described how the team that won the Red Balloon Challenge used cascading incentives:
They promised $2,000 to the first person who submitted the correct coordinates for a single balloon, and $1,000 to whomever invited that person to the challenge. Another $500 would go to the person who invited the inviter, and so on.
Incentive markets that reward people in proportion to their contribution towards a common goal in this recursive way can motivate people to grow a network until its goal are met.
However, this mechanism can be manipulated through collusion between network members who want to cheat the system. Suppose Alice was referred to the Red Balloon Challenge and happens to knows where a red balloon is located. Instead of submitting the location and redeeming her rightful reward, Alice (and her accomplices) can be dishonest: Alice can “refer” her husband Bob, who can “refer” their daughter Carol, who can then claim to have found a red balloon. As a result, Alice, Bob and Carol will receive the three largest rewards of the recursive payout structure and split the windfall rewards among themselves. The person who initially referred Alice gets edged out of these high rewards, which are allocated unfairly to Bob and Carol.
Since the referral chain grew through superfluous referrals, there are more people to be rewarded, and so the cost of finding the red balloon is artificially increased. This collusion makes the network more costly, less efficient, and ultimately unfair to its honest users.