Reputation Power Matrix — a mechanism design for sustaining value and protecting privacy
This article explains the concept and intuition behind Reputation Power Matrix, the long term version of an ideal reputation power system.
It’s a widely supported belief that Web2 (our current web) is becoming increasingly centralized, to the point where we, as individuals, don’t even own our data. We need to find a way where we as individuals are able to reclaim our own data, and in turn, our identity on the web.
New technologies, such as blockchain and crypto, have opened opportunities to make our web decentralized. We can now give power back to individual users, instead of huge corporations. This is the new Web3.
Reputation Power Matrix (RPM) is a Web3 mechanism design utilizing a privacy-first (individual centric) framework. Today we will be going over the intuition and concept behind this design.
Access the full lightpaper on Reputation Power Matrix:
The web is currently contained in what’s called a “resource-bound socioeconomic environment” dictated by the concept of the “rule of scale.” This means that power is given to whoever has a higher concentration of resources. We have a defined, finite amount of resources, and whoever has the greatest number will have the greatest power.
In our current age, this can be seen with big tech companies that collect and own user data. Web applications that we use on the daily — social media, search engines, popular websites — give us incentives to “create data.” This includes creating a new profile on a website, clicking a link to fill out a form- anything that leaves a digital footprint.
With all of this “created data,” this all lies in the ownership of huge corporations owning the applications. We’ve unintentionally created a centralized system where we’re now dealing with privacy issues. The Facebook-Cambridge Analytica data privacy scandal is one example of the consequences of this system.
How do we solve this? We need to design effective mechanisms for a fair distribution of economic value that is generated by user data. The goal of RPM is to allow an individual to hold onto their data’s economic value generated through accessing the web.
This will become necessary with our transition into Web3 where our surroundings will be multidimensional with the Metaverse. New dimensions of data creation and consumption will be introduced, far more complex than what occurs today.
The relationship between user data and big tech organizations can be seen as predatory with unfair use, while enhancing total control. On the other hand, our goal is to enforce a symbiotic relationship between RPM and user data, where individuals can gain back control to their own data with the help of this system.
In decentralized systems, the concept of “creativity” is encouraged with creating DApps, voting, generating transactions, etc. In our centralized system with the web, resource-bound forces (such as the concept previously introduced as the rule of scale) are dominant.
We can see that
Our goal is to employ creativity (giving and sharing) to counter these resource-bound forces in order to form Web3.
Value from the web almost always comes in the form of data. In this scenario, we can say that value = data. Economic value can be viewed as entities of resources.
Right now data from our web can be classified as resource-based economic value. It is also zero-sum in nature, and can be represented as zero-sum value. This forms centralized power structures, as seen with web2, and we must find an alternative.
This is where we apply that creativity component. Mind-bound value is an alternative to resource-bound, and is also referred to as generative value.
We also introduce the concept of pre-value, which is what we are currently dealing with and is susceptible to centralization. Post-value, on the other hand, is a measure of mind-bound / generative value. It is accurate, stable, and resistant to manipulation.
Reputation Power (RP) is a type of post value. Reputation Power Matrix (RPM) is a web value data framework and a measure of mind-bound / generative value entity.
Let’s also introduce the concept of data. Data is essentially the foundational substance of digital society. Value entities can be referred to as value data within this specific realm. A value data framework (VDF) is essential to support the value data economic cycle (VDEC), which would ideally be decentralized. In today’s world, web applications can be seen as the frameworks for large corporations to profit from. The cycle for the corporations to make profit from is between them, users, and the application.
The RPM is a type of VDF used to drive a version of Web3’s decentralized VDEC. Our intent is to design a RPM in such a way with a specific mind bound / generative value entity representing a decentralized web.
Our economy is dominated by these resource-bound, zero-sum value entities making centralized organization structures. We can see this with the web, our government, and many large corporations.
Today’s decentralized systems are still semi-decentralized because user identities are still contained in a boundary. The boundary encompasses the system the user is part of. This boundary can be viewed as a container.
We can compare this to a biosphere that contains plants, animals, insects, and all other living organisms that require both each other and the ecosystem to function. The boundary can also be compared to the cell membrane, a protective layer that holds all the parts necessary for the cell’s functions, including the mitochondria, nucleus, lysosome, ribosomes, etc.
In order to get to a stage for “true decentralization” the boundary must be moved from the container to the individual themselves. This is referred to as an individual-centric DAO where privacy is contained in the individual (privacy first).
Today, there is an imbalance of this data value distribution. The boundaries only support the growing concentration of power for big tech companies. As previously discussed, individual web users don’t have control over their online profiles because they do not own their privacy data.
With the privacy-first regime in RPM comes two purposes:
In doing so, we can accomplish decentralized identity (DI) where users can take back control of their own data.
In the design for the system, we have to first adopt the idea of individuality instead of identity. Identity implies centralization due to the need to be a member of some organization. If you identify yourself as a software developer, you are part of a group of millions of other developers and likely work at a larger organization. If you identify yourself as a teacher, you are likely part of a school or institution.
These are just some examples. We should now adopt the concept of individuality in web3, which is more multifaceted in nature. Individuality in the privacy-first regime means an individual’s ability to control their privacy data in the VDEC.
The RPM is a multi-dimensional value entity shaped as an individual’s privacy data storage/collection unit. The RPM VDF is where the privacy data is accessed and utilized inside the RPM data collection.
Let’s look at the value of identity in a centralized regime. Its reputation is a value proposition associated with the centralized regime’s identity. Reputation can be turned into a measurable value representation with pre-value reputation power, under a resource-bound / zero-sum value entity. This is similar to money or credit with non-transferable value, for example, airplane miles when you travel.
The value of identity differs in a decentralized regime. We instead have post-value reputation power to be used as an incentive device in order to foster the “creativity” component previously discussed. This is within the RPM and is in design, an algorithmically guaranteed mechanical proof that certain functions have been carried out.
An individual’s generated data, protected by cryptography, is stored and never leaves the individual boundary. All the functions of the RPM such as storage, data generation, processing operations, all happen inside the individual boundary.
Web DApps employed by the DAO or DAC that the individual is part of must send their algorithmic devices to the individual in order to carry out the necessary computations for the individual boundary to be maintained. Privacy-preserving computation schemes can then be employed.
In generating post-value reputation power, a sampling or tracing function is sent to each individual RPM. The computations of the post-value reputation power functions are carried out inside the RPM. The technical result is a nonempty set of numbers, while also having reduced dimensionality which can be a reference to other datasets. More details will be provided in an upcoming paper relating to the technical implementation of RPM.
As emphasized by the lightpaper, reputation power can be seen as a “cut” with a reputation power matrix as the “pie.” The pie can be cut in many ways- this is one out of many approaches for an effective web3 mechanism design.
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