Breaking down reputation

A good reputation system is able to provide a bias prior to an interaction. I use Yelp as a reputation system to bias my perspective on a restaurant. A bank uses my credit score to bias its decision on providing me a loan. This bias can be helpful to both parties to predict compatibility prior to interaction.

Reputation is a proof-of-work. Meaningful reputation takes time and energy to build. Having a good reputation grants you privilege to a valuable perk. If the reputation is easy to acquire, the perk may be exploited; resulting in either an increase in reputation acquisition difficulty or a decrease in value of the perk until an equilibrium has been reached.

Reputation is typically application-specific. The reputation I’ve built up with my friends won’t help me get a better Uber ride. This is because reputation is not stakable across systems. Leveraging your reputation requires you to put the reputation at stake as collateral. By doing so, you are held accountable for your behavior with the threat of losing the collateral and decreasing your reputation. Since disparate systems are unable to impact each other’s reputation, the reputation you’ve earned from one system won’t carry over to other platforms (ie. nothing-at-stake).

Tokenized Reputation

Tokenized reputation is different from historic reputation systems in that it is:

Measurable — different parties can come to agreement on the quantity of reputation.

— different parties can come to agreement on the quantity of reputation. Valuable — the benefits of a good reputation are stated explicitly.

— the benefits of a good reputation are stated explicitly. Effort based — tokenized reputation is independent from skill or ability.

— tokenized reputation is independent from skill or ability. Stakable — abuse of the system results in loss of reputation.

— abuse of the system results in loss of reputation. Transferable — reputation can be exchanged for currency or other reputation tokens.

Having a tokenized reputation is important as it allows you to not only quantify the work you’ve put into a system, but allows you to leverage this reputation to work for you more efficiently. Let’s look at the three most contentious features of tokenized reputation and see why they are crucial for a modern reputation system.

Effort Based Reputation

Reputation can be broken down into two components: ability and effort. Ability is more akin to identity and represents your skill or capability to achieve a certain task, while effort represents your drive to deliver. Most reputation systems conflate these two concepts into a single metric; however through the process of tokenization, we’ll likely be forced to separate them. Tokenized reputation refers solely to effort, while alternative tokens are needed to represent ability. This distinction is important, since different classes of actions can be taken with each reputation type. To make this concrete, let’s look at a hypothetical story where tokenized reputation is commonplace.

After graduating from John Hopkins University, Marie received a non-transferable token representing her medical degree. The token contains references to a series of off-chain claims that allowed Marie to prove additional characteristics about her degree (GPA, honors, etc.) to her future employer. This token is unique to Marie and is not something she could ever give away or stake as collateral. Through a series of skill-based interviews she started her residency at Swedish Medical Center (SMC) which granted her an SMC non-transferable skill token as well as a starting balance of 800 ⓜ (medcoin). The SMC skill token has a built-in expiry, requiring its owner to renew it every five years. This ensured Marie’s medical skill was always up to the hospital’s standards. The ⓜ balance was applied every day as collateral and was directly affected by the reviews from her patients and co-workers. By applying her skill with effort, she was able to earn an additional 100 ⓜ over the course of the year. This additional ⓜ provided a piece of mind for Marie since the access control gate at the entrance of the hospital required each staff member to have an active SMC skill token and a ⓜ balance of at least 700 prior to entry. In addition, the hospital relies upon both types of tokens to determine promotions. Each new promotion required a new type of skills test as well as an increase in total ⓜ balance.

In the story you can see ability and effort separated into two types of tokens. This distinction provides both a clear, continuous incentive to perform well and an assurance to the hospital that her skills remain sharp regardless of applied effort. Each promotion increased Marie’s pay and scope of responsibility. Since the increased responsibility also increases the potential harm to patients, the collateral must also increase proportionately to compensate. Note that neither ability nor effort alone are sufficient for interacting with most systems.

Stakable Reputation

Separating reputation into effort and ability has an additional benefit: it isolates the reputation that can be used as collateral from the reputation that is core to our identity. We can think of ability tokens as trophies or awards: point-in-time statements that signal the capability of the entity to others. Effort tokens, on the other hand, are earned through effort and can be lost through lack of effort. This implies that effort tokens are used as collateral and, like any collateral, are used to offset the risk of the interaction. This next story follows a fictional character, Emmeline, and her effective use of reputation as stake.

While exploring the depths of the internet, Emmeline discovered a novel social media platform, Stākit. Like most modern social media platforms, participants could build up a tokenized reputation by writing quality posts and participating in platform curation. What made Stākit unique was that each post required the author to stake some amount of reputation tokens. The more reputation tokens that were staked, the larger the potential audience. The catch was that if the post didn’t follow the community guidelines, the post could be curated out and the associated stake given to the curators. As Emmeline built up her reputation and trust from the community, the audience of her posts grew along with her potential rewards. She became one of the top voices on Stākit and soon the platform was seen by the mainstream as a source of quality content. However, Emmeline noticed that as her status increased, she received more and more offers from sponsors and advertisers to promote their products through her posts. The offers were of course tempting, but promotional material or biased claims were strictly against the community guidelines. She did the math: her highest paying potential sponsor was offering $10k for a promotional message, however in doing so she would jeopardize almost a year’s worth of reputation, which at market value was around $30k. From historic precedence, she knew there was greater than 33% chance of the community disapproving the content. Even if she didn’t care about the platform, the risk of losing that much reputation token outweighed the potential gains of biasing her content.

Unlike in-person societies, online communities have the potential to scale well beyond the Dunbar number. However, these expansive communities are only sustainable if they incorporate a universal reputation system as well as incentives that encourage community building rather than exploitation. Although it’s often difficult to calculate the potential harm of any given action to a platform, for a community to thrive, the risk of losing staked collateral for any action must outweigh benefits received from exploiting that action. Communities that don’t put reputation at stake are plagued with either centralized censorship from moderators or manipulative content from promoters.

Transferable Reputation

Transferable reputation is probably the most controversial of all the tokenized reputation properties. Transferability implies that reputation could be bought or sold on an open market. We often feel that reputation should be earned and is not something that can be purchased. You shouldn’t be able to buy an audience for your Tweets or customers for your restaurant, right? Let’s jump into another fictional story that takes place in a universe where reputation can be purchased.

Ada is a driver for Connect, the latest decentralized ride-sharing platform. She picked up driving for Connect as a part-time gig to help pay for her college. To drive for Connect, each driver has to pass the preliminary background checks and driving test as well as actively retain a rating of at least 4.6 stars. The Connect matching algorithm gives a preference to high rated drivers; often giving them the ability to choose from a set of potential passengers prior to starting the ride. Building up reputation takes time, but Ada was tired of dealing with rude passengers. She had worked hard to save up $1000 in high school which she was able to use to buy a 4.9 star reputation with. She wasn’t worried about spending her hard-earned money on the reputation since she was confident in her ability to maintain it. After four years of excellent service she made a considerable dent in her tuition while building up a 4.98 star reputation with over three thousand rides completed. With her new computer science degree, she landed a full-time job working at a big software company. Not only did this mean a big relocation to a new city, but that she had no need to drive Connect for the foreseeable future. Realizing that the reputation she built up would go to waste, she sold it on the open market for an extra $2000 that she put towards her student loans.

Even in this hypothetical scenario, Ada had to pass all of the requirements to be an eligible driver. However, without the ability to purchase reputation, Ada would have been stuck building up her reputation from scratch, despite having saved up adequate collateral elsewhere. Even though she hadn’t invested time into the platform, she still had incentive to be a good driver since she otherwise would have lost the money she had worked hard for. In the case that she couldn’t sell the reputation when she was done using it, the reputation would remain locked in the platform. Since the reputation would go to waste, Ada would be incented to abuse the platform to make the most of her excess reputation. Abuse can take shape in many forms and is platform dependent; but this incentive to “cash out” the reputation through abuse inevitably cancels out the benefit to the platform that the reputation provided in the first place. In practice, it may be useful to annotate the source of reputation for optional discrimination. It’s up to each individual to decide if they value purchased reputation equivalently to reputation received directly from the source. It may be some time before users are comfortable with transferable reputation so annotating reputation origin is a practical first step.

This may seem like a repulsive idea at first, but it’s something that most of us are already familiar with in banking systems. When taking out a loan from a bank, the bank will evaluate your credit score (reputation collateral), your down payment (liquid collateral), and your current income (ability to deliver). In the case that your credit score is poor, you can supplement it with a higher down payment. In essence, we’re trading reputation for money as interchangeable forms of collateral. Note that this is independent of the borrower’s ability to deliver, which is correlated but measured independently of the borrower’s reputation.

Irrational Attacks

If malicious actors are able to easily purchase reputation, what’s stopping them from abusing the power? As mentioned before, there will be some exchange rate and required reputation collateral that will reach an equilibrium at a point where the cost to abuse the system becomes higher than the value derived from the abuse. There are of course, trolls; those who act irrationally because of the pleasure derived from destruction. The proposed system would allow cost-insensitive trolls to buy their way in and manipulate others at their own expense. On the other hand, reputation systems today suffer from time-insensitive trolls since they only require time and effort to be spent to build up a reputation. Each individual values their time differently, so different systems will attract different types of trolls. In either case, trolls will burn through their time or money and will be greatly outnumbered by those that wish to rationally improve the platform.

It is worth noting that although effort and money can be thought of as interchangeable in most cases, there may be unintended consequences caused by the immediacy of purchasing reputation. Due to the nature of human emotion, premeditated attacks tend to be more rational, while impulsive attacks will often do damage at the expense of the attacker. Systems which allow the immediate purchase and use of reputation could suffer more from impulsive attacks, with the ability of users to quickly shift reputation across systems. To mitigate this, one could build in “cool-down” periods to force the users to take time to think prior to leveraging their purchased reputation. This technique has been shown to be effective in reducing violence from the purchase of firearms, reducing homicide rates by around 17%.

Rational Attacks

With the ability to quickly purchase reputation across a variety of systems, it becomes possible to make coordinated attacks profitable. We’ve seen these types of attacks become a serious threat in the cryptocurrency space. Markets like NiceHash, which allow people to rent hashing power by the minute, have allowed short-lived, coordinated 51% attacks to become profitable. If an attacker was forced to procure the hardware ahead of time and sell it when they were done, there would be increased risk on the attacker. Not only is there opportunity cost from purchasing that quantity hardware, but there’s a good chance that the opportunity to attack may never arise. To prevent these attacks, we must increase the uncertainty of reward. For example, requiring a hashpower renter to rent the hardware a month in advance would dramatically increase the risk. Similarly, requiring that a purchaser of reputation hold on to that reputation for an extended period of time before and after using it, increases the risk to an attacker and further aligns their incentives to the success of the platform. Each platform will need to tune their waiting threshold to reflect the risk of coordinated attacks. Fortunately, the expressiveness of smart-contract based blockchains allow for these granular incentive mechansims to be practical.

Why not use money?

You may be asking yourself, since tokenized reputation shares many of the same properties of money, why not just use money instead? In fact, it is very similar to money with some notable differences. The value of these tokens doesn’t come directly from the parties involved in the interaction; it is given by the platform itself. Similar to many blockchain token models, the value can be realized through inflation, taking small amounts of value from existing reputation holders. Reputation has become a way for the platform to give back part of the value that the entity provided to the platform. Without this rating system, it’d be difficult to tell the value that an entity provided to the platform during a given transaction. The reputation is similar to a cash tip, however with a cash tip, the party that gives the tip directly loses that amount of value. Because those who assign the reputation are not losing anything, they’ll be more inclined to provide an honest rating.

Self-Sovereign Reputation

The ultimate goal of a formal reputation system is to provide true ownership over one’s reputation. As you switch between Uber, Lyft, or some platform of the future, your reputation should carry with you. The inability to withdraw your reputation from a given platform solely benefits the platform at the cost of the consumer. Platform lock-in leads to network monopolies which reduces market efficiency and concentrates power. By freeing reputation to be valued by an open market, it will force platforms to provide real-value benefits for its reputation holders. Rather than receiving meaningless trinkets or vaguely defined perks, platforms will have to put real value into the hands of those doing the work. Users will be able to freely flow to the platforms that make the best use of dynamic workforce. Better Facebooks will be able to form over night, bootstrapping network effect from existing underserved platforms. Platforms will be free to compete based on merit rather than simply rewarding the platform that came first. However, despite its potential benefits, formal reputation alone is not sufficient for achieving these goals. Reputation, identity, and data all form important pillars of self-sovereignty.

Adoption

Admittedly, it’s still many years out before tokenized reputation becomes mainstream. Reputation models take time for the game-theory to run its course, but inevitably the well designed systems will outlive the less successful alternatives. Blockchain platforms promise not only the technology to formalize these systems but also the sandbox to rapidly experiment and grow a successful platform that puts users first.

Further Reads

The subreddit, r/ethtrader, has begun issuing tokenized reputation (named “donuts”) to reward contributors and moderators. These tokens can be used to participate in community voting or renting billboard space (using depreciating license economic model). Recently, these tokens have become transferable, allowing reputation purchasers to acquire on a market. Because reputation isn’t stakable on Reddit, the platform will be more likely to suffer from reputation attacks.

This discussion is complementary to many of the existing efforts to classify data as labor. “Data as Labor” aims to formalize the hidden economy of human data by encouraging data-aggregation companies to pay a fair price for the data that runs them. This becomes increasingly important as traditional jobs are consumed by this economy while companies only pay for the newly created jobs with digital services.