At its heart, Möbby includes a layer-1 blockchain protocol and an associated token that relies on a novel concept termed: “Proof of Reputation” (PoR). The system utilizes the reputation (assigned to its servers via a newly designed recommender system) by its users to iteratively select committees of reputable nodes that propose and vote on the next block in a hash-pointer-based blockchain: In each round, one such committee is chosen and proposes one block which might include multiple transactions, endorsements, and various metadata. By a methodology that combines PoR with a light-weight Proof-of-Stake (PoS) mechanism, the system ensures that (1) the recommendation of the committees can be trusted, and (2) even nodes with low reputation (that are trying to build it up) get a fair chance at becoming a committee member. But how does this address the issues listed above? This is achieved by a sophisticated reward mechanism that shares block rewards with the voters of every block according to their reputation and service quality. This means that nodes/servers are incentivized to behave honestly, and users are incentivized to increase their reputation to maximize their own profit. Importantly, as discussed below, maximizing one’s unilateral profit also maximizes a well-defined societal impact that can benefit higher-level applications and the greater good.

1 Monetizing Reputation for a Stable and Truthful Recommender / Reputation System

One of the key novelties of Möbby is a new mechanism, developed by the Möbby research team, which has the following properties: There are two types of actors in the system: users (aka endorsers) and servers (aka nodes). Möbby servers are responsible for maintaining the Möbby chain. Their importance in the system—which weighs in their expected total reward—is decided by the endorsements that users give them. (One can think of endorsements as a confidence vote by an endorser on the trustworthiness of each server when executing the system.)

Properties of our reward mechanism. We discuss below the effect these properties have in terms of incentives that benefit the system:

1.

Reward proportional to reputation. Servers are rewarded proportionally to their reputation (which, remember, is a reflection of their credibility/trustworthiness from the point of view of the system). This reward is a combination of tokens and a reputation increase.

2.

Incentives to endorse. For any user, it is a dominant strategy to endorse (rather than not endorsing). Endorsers are rewarded proportionally to their own reputation and the accuracy of their endorsements.

3.

Incentives to endorse truthfully. In a stable state (Nash equilibrium), endorsers are incentivized to endorse according to their true belief about the trustworthiness of the servers. Furthermore, by observing the endorsements in the above stable state, the system can learn useful information about the trustworthiness of the servers from its users’ perspective.

In the following, we discuss how each of the above properties influences the quality and impact of the Möbby ecosystem and applications that can benefit from it.

• Effect of Property 1:
  • It incentivizes servers to behave honestly.
  • It allows us to compute—and leverage in DeFi mechanisms that build into the system (see below)—the average loss by misbehaving.
  • It allows users to “invest” their endorsement budget (which is proportional to their own reputation) to servers that have a cause they align with (e.g., support a charity or organization they trust).
• Effect of Property 2:
  • It incentivizes participation in the endorsement mechanisms. Looking ahead to use cases of the Möbby blockchain, this can offer a remedy to one of the major plagues of recommender systems: Users who are neither excited nor disappointed about the provided service typically abstain from submitting a review/recommendation–this, in turn, results in polarized and more manipulable recommender systems.
  • As with the effect of Property 1 on servers, this incentivizes users to increase their own reputation in the system.
• Effect of Property 3:
  • This demonstrates how powerful the paradigm of combining reputation with a built-in monetization mechanism is—a combination that is the cornerstone of the Möbby philosophy. It implies that a user cannot increase their reward by endorsing against their belief about the trustworthiness of the service. Thus the endorsements themselves can be used as an indication of how the system perceives the trustworthiness of each node. The fact that such truthful endorsements allow (the system) to learn (useful information) about the server’s trustworthiness turns Möbby into an AI tool, which allows it to converge to the ground truth about such trustworthiness. As we will discuss below, this has the potential to disrupt several established industries that use recommender systems.