How do you find the job candidate who’s an exact fit for your organization? How do find the person you are going to marry? How do you locate the right house for you and your family? How about a pet that’s been missing? Worse yet, a child who’s been missing?
As a society, we spend a lot of time looking for things. Individuals search for apartments to rent, cars to buy, and romantic partners to date. Businesses search for customers, employees, and suppliers. Although we tend to approach these searches as if they are unique, we at nCent believe that they appear distinct on the surface but are often subject to similar dynamics on a meta level. Our goal is to enable people to use incentive programs and blockchain technology in order to solve some important problems facing the world today. We believe, in particular, that we can help people find higher quality things in a fraction of the time and more efficiently than they might expect.
Some search problems, like finding the closest Italian restaurant, are easy to solve. But other search problems are more difficult and involve higher stakes. Finding a missing child, for example, is more challenging because it may be unclear where to start and how to efficiently gather information. It’s obviously a high stakes situation, because it involves the welfare of a child — quite a bit different then satisfying a pasta hankering.
Difficult searches are called “needle in haystack” problems. One of our guiding principles at nCent is our belief that these “haystack” problems can be optimally solved by combining decentralized networks, blockchain technology, and the right incentives programs.
A ‘proof of concept’ for this approach happened in 2009 when DARPA (USA defense research agency) placed ten red balloons in secret locations around the U.S. and offered $40,000 to the first team to locate them all. The winning team solved this search problem by offering recursive incentives: Anyone who either correctly identified the location of a red balloon or referred someone whose information led to a person who identified the location of a red balloon was rewarded. For example, if Person A referred Person B who referred Person C who correctly identified the location of a red balloon, then all three people in this chain would get rewarded in some capacity.
Even if you don’t know where the needle is in the haystack, you are still incentivized to help by referring others to get closer. If the tail end of your subtree finds the needle, you too will be rewarded.
Utilizing blockchain technology in this process enables the network to be transparent and to be audited by anyone at any time. Everyone who contributes to the network can be absolutely sure that if their contribution is valuable, their reward will be commensurate with this value. This means that the person who finds the missing child and the person who spread the word to the finder’s social media network will be rewarded. The person who refers a successful candidate for a specialized job and the person who informed the referrer will be rewarded. These programs can reduce their overall cost with recursive payout structures (Larger payouts for those who are “closer” in the chain to the final goal). These recursive programs are scalable and when designed correctly, have an upper bound on the cost of sponsoring them.
The biggest hurdle to solving a haystack problem is growing the search network quickly enough so that the chance of identifying the needle increases exponentially. Recursive incentives motivate people to inform other people of the search problem. When executed properly, these networks grow quickly and organically, increasing the statistical probability of finding the target. In fact, we believe that recursive incentives, where every node of the successful chain is rewarded, become increasingly more valuable as the search problem becomes more difficult. Spam is another common problem that we will address in a forthcoming post: “Cashout: What Does it Mean to be Spammed with Money?”
As the tail end of the network is further removed from the origin of the network, the spread of information will be more efficient than any other search process implemented in the marketplace.
We fully recognize that each case will come with its own idiosyncrasies, ranging from economic constraints of the searcher to the psychological realities of how people respond to incentives. The incentive structures implemented on our blockchain will be modular enough to apply to many types of search problems. The inclusion of “decentralized networks” and “blockchains” might sound like tech jargon, but in reality it’s just the underlying tech that enables you to give “asking your friends for help” a global reach!