The Slant Protocol v0.1


You are Slant!

We realize that opinion data is one of the most controversial values of mankind. With SLANT, we are creating the foundation of how we and future generations define the value of opinion data, how we form opinion, who has access to it, how controversies and discussions around opinion are structured and how consensus can be found. We want to offer a decentralized open source network and invite a wide range of people and groups to participate in our conversation and efforts to develop the standard in collecting, structuring and organizing opinion data for the next generation of the web.

How to get involved:

To foster the conversation we are using RAWR, our app based on SLANT.


Every time you find blue highlighted text we have specific questions on the highlighted concept. Please let us know what u think and contribute your arguments through rawr’s conversation widgets. It’s really simple. You can also submit and promote your own questions by filling out the contact form underneath each rawr.


If you want to commit new ideas or concepts or help us to decide on the roadmap and priorities of slant, please join the steering committee.


And of course, if you really know your game, please become a committer. Please chat to any of the existing committers and find out how to get involved.

The Protocol:

This protocol aims to be the number one standard in scrobbling, structuring and organizing opinion data in the next generation of the web.



The Vision

We believe in an empowered society where opinion is an inevitable part of value creation.

The Big Picture

In human history fundamental events such as the agricultural revolution changed the long term prospect of our society. People started to cultivate land and domesticate animals. For the first time, people began to structure resources forming a society characterized by social stratification. Another event was the industrial revolution. Human labor got enriched by machines. For the first time, economic growth outpaced the growth of the population, resulting in more income for the society.


Today, we all experience a third fundamental event, which will change the long term prospect of our society yet again – the information revolution. In a similar way as the industrial revolution enriched human labor through machines, the information revolution enriches human labor with information. This has many advantages, but it also means, that human labor is further removed from the economic productivity factor and will increasingly be focused on the bare minimum – decision making. This trend is massively fuelled by autonomous agents and artificial intelligence. As a consequence, today we are witnessing the beginning of the failing traditional, productivity centric economic models. Inflationary monetary policy and financial crisis are only the first signs of our collapsing economic model.


With the Slant protocol, we are proposing a new economic model which reflects a new concept of labor. It is centered on decision making and opinion as the most fundamental human right to evolve the labor based concept of work. It is designed to turn opinion into a valuable and transferrable digital asset which represents the labor factor of the information economy. If the slant protocol is successful we will live in a society, where opinion is transactional and sovereign at the same time. Forming opinion and making informed decisions becomes a fundamental source of income for each individual. Having access to the opinion market will be more substantial for us than having access to the labor market. We can’t even start to explain how big this is.

Why web3.0?

During the web2.0 period, Michael Breidenbruecker, one of the initiators of Slant, founded,  an opinion network for music. In 2003, financial and mostly legal pressure on ltd. was so heavy, that the future of the legal entity was more than in question. In this situation, Michael was developing scenarios how the service could be maintained and how user data would not become the collateral of legal and financial battles. A phenomenon that is even more dramatic today giving recent data misuse scandals of other social networking platforms. What was the real problem?


Similar to all other web 2.0 projects, stored data on a centralized architecture and fostered the economic value of the data through a legal entity in order to maintain the centralized architecture, provide services to its users and pay everyone on the payroll as well as investors and shareholders. In other words, not only but the whole of web2.0 in general wasn’t just built on centralized technical architectures but also centralized financial architectures. The real problem was the centralization of data and financial value.

One of the scenarios Michael developed was to decentralise the architecture and keep the service running on a decentralised network. This network would need to guarantee the supremacy of opinion data and at the same time enable the exchange of opinion data on a trusted basis. This network would also need to incentivise all involved parties and distribute financial value. In 2003, this was simply not possible. Interestingly the biggest problem of web2.0 has now become the biggest feature of web3.0. Lets get it right this time guys!

Web 3.0 isn’t just replacing the need for a centralized technical architecture but also the need for a centralized financial architecture. We are pretty sure that the Slant protocol will only work on a decentralized technical and financial architecture.

The Token

The Slant Token

Similar to the labor market contributors in opinion forming and decision making are earning slant tokens. These tokens represent the value of the contributed information and increase the value of the slant network and economy. In order to access or read contributed information tokens need to be paid. In other words, tokens are reading rights which are mined by contributing to the opinion forming and decision making process and burned by consuming information. This is a super important concept behind the slant economics.

In order to provide a working ecosystem and avoid fraud and inflation, the contribution side as well as the consumption side need to implement specific mechanisms which are described in this chapter.


Contributing decsisions to the Slant network can be done through many different ways. No matter how the contribution looks like, it adds information to the Slant network and mines tokens which get distributed to the whole contributor chain.




In the beginning of this paper, we mentioned three core principles which are the basis for our architectural decisions. These core principles are very important for the struture of the Slant ecosystem. Altough every contribution on Slant mines tokens, the amount of tokens mined varies depending on specific factors. All those factors are designed in order to fulfill those core principles:

  1. forming opinion and making informed decisions is work/labor
  2. similar to the labor market, the decision market reflects the dynamics of offer and demand
  3. similar to labor, decisions have different qualities

Decision Quality


Let’s start with number 3: Similar to labor, decisions have different qualities. Contributors get rewarded for forming informed decisions. But decisions don’t have the same qualities. At Slant, the qualitiy of one decision is defined through three factors:


  • Proof of Work


The quality of a decision is depending on the brainwork which was done in order to form it. Brainwork is done by consuming information around specific decision topics. Slant registers every article, argument or piece of information which is consumed before the publication of a decision. The proof of work mechanism allows Slant to calculate the amount of tokens which are mined in a fair manner and helps us to avoid fraud. Since people need to proof that they worked for their decisions, we can work against bots, publishing random decisions.


  • Proof of Person


Another functionality to avoid fraud is the Proof of Person mechanism. We want to incentive contributors to verify their identity as detailed as possible which is why the amount of tokens one can mine is also depending on the identity verification the contributor went through while creating a Slant profile. There are different Proof of Person stages, contributors can go through to increase their mining power:

Tier Level Mining Power
Tier 0 No verification 0
Tier 1 Email verification 1
Tier 2 SMS verification 2
Tier 3 Identity Provider (Civic) 4

  • Privacy Level


There is one more factor which has influence on the quality of individual decisions. Slant profiles include advanced privacy settings through which the contributors have the full control over their information. In those privacy settings, contributors can decide, which information they want to make accessible for others. To increase the value of the Slant network as well as make it attractive for consumers, we want to incentivize contributors to publish much of their information. That’s why we came up with different privacy levels which have an influence on the quality of individual decisions:

Tier Level Mining Power
Tier 0 basic information (arguments, articles) 0
Tier 1 background information (age, zip code, gender) 1
Tier 2 meta data (online behaviour, general interest) 2

Decision Topic Value


Decision topics are the topics, articles or questions, on which contributors publish their decisions. If someone for example publishes his/her decision on a question regarding the political situation in the USA, the question is one decision topic. The amount of tokens which are mined are also depending on the value of the decision topic they are contributing to. The value of a decision topic is defined through three factors:


  • Quantity of Information


We want to incentivise the community to work towards unique decision topics by contributing their decisions to one decision topic. In order to avoid duplicates, the value of a decision topic increases with each contribution. With this mechanism, contributing to one decision topic which has many contributions also means you mine more tokens.


  • Information Quality


Same as the quantity of information, the quality of information on a decision topic has an influence on it’s value. Information quality is important in order to avoid biased and one sided decision topics. The quality of decision topics is defined through

  1. the decision quality of the individual decisions (see chapter “decision quality”)
  2. the balance of decisions. Decision topics which contain decisions from different angles are valued higher than decisions with one sided decisions.


  • Bidding


Consumers who are interested in Slant information can incentivise contributors to contribute to specific decision topics by increasing the mining for individual decision topics. If a marketer for example is creating a decision topic on which he wants actual and relevant information, he can increase the mining value. The bidding mechanism also leads to a higher value of the whole Slant network, since it always guarantees freshest information for everyone.




In order to explain the importance of demand in the mining process, we again want to stress one of our core principles: similar to the labor market, the decision market reflects the dynamics of offer and demand. When there is much demand on a specific decision topic, we want to incentivize everyone to contribute. That’s why we included a mechanism which increases the mining for specific decision topics which have higher demand. This means: contributing on a decision topic which has a high demand makes you mine more tokens.


Mining/Burning Ratio


We want to avoid high in- or deflation and ensure a stable inner value of the Slant network. Let’s remember the utility of our token as reading rights which get burned right after redeeming (chapter “The Token”). This means, that a high demand on information causes a high burning rate. To avoid deflation when the burning rate is high, we implemented a mechanism which balances the Mining/Burning ratio in our network. This mechanism increases the token mining as soon as there is a high demand in tokens and decreases token mining if there is less demand.


Let’s take a look at the token mechanics and incentives of the consumption side. Slant information can be consumed by everyone who owns tokens. This can be contributors as well as several interest groups, AI companies, marketers, political parties, activists and so on.




As you could read in the last chapter, contribution defines the mining of Slant tokens. Consumption of information in the Slant network on the other side, means burning of Slant tokens. In order to offer a safe and trusted ecosystem which is valuable for consumers, the burning process needs to include specific economic mechanisms and incentives. The following chapters describe different factors which define the prices of information and decision topics for consumers. To understand those factors, we’d like you to remember point three of our core principles: similar to labor, decisions have different qualities. This not only plays a big role on the contributor’s side but is also important for the pricing of information.


Information Level


The Slant network offers a broad range of valuable information to consumers. As we already explained in the chapter “Decision Quality”, Slant implements many token incentives for contributors to offer detailed information. The prices of information depend on their level of detail:

Level Description Multiplier
Basic Information e.g. arguments or a piece of information (article) x1
Decision Topic Results e.g. general results of one decision topic (all arguments & votes) x2
Personalized Information decision topic results with personalized meta data of contributors x3

Decision Topic Value


In the last chapter, we were already talking about the value of decision topics for the contributor side (please see chapter “contribution”). The value of decision topics also plays a big role when it comes to the consumption of information from the Slant network. Same as the mining on decision topics, the pricing for a specific decision topic is depending on it’s value. A decision topic with a higher amount of information and with high quality information is therefor more expensive than decision topics with less information or lower quality.




As in most economic models, prices on Slant are depending on demand. In order to always increase the value of the Slant network, decision topics with high demand are priced higher than others. This mechanism enables us to mine more tokens on the contributor side and to create additional incentives to contribute on decision topics with high demand (see “Demand” chapter in “Contribution”).


Mining/Burning Ratio


Same as on the contribution side, the mining/burning ratio is adapted on the consumption side. In order to avoid de- or inflation, the Slant network adapts the token prices for decision topics depending on the amount of tokens which are mined. This means, if there is a high mining rate (more contributions than consumptions), this mechanism is creating a high burning rate through adapting the token prices for decision topics.


Fiat/Slant Ratio


Because we can’t guarantee a stable token value, it is very important to implement the fiat/slant ratio as factor in the pricing mechanism for Slant information. Prices for Slant information will always be orientated on their acutal fiat value. The token prices for decision topics will vary depending on the current fiat/Slant ratio.

To give an example:

Let’s say, one Slant token is worth 1 dollar. The calculated price for one specific decision topic is 20 tokens, meaning 20 dollars. If the value of Slant tokens now doubles through external trades or an increasing network value, the token price of this decision topic will decrease to 10 tokens (which still is 20 dollars).

This means: to avoid extreme pricing fluctuations, the token price for decision topics decreases, if the fiat/slant ratio increases and increases if the fiat/slant ration decreases.



 t time variable

  • t=0 opinion event starts
  • t=τ moment of mining (token distribution to user or app developer)

nu(t) amount of users, who took part at opinion event at moment τ

nC amount of customers, who bought opinion data until moment t=τ

t(c) moment when customer c ∈ 1, . . . , nC bought data

0<α<1 amount of token income distributed to slant


0<β<1 amount of tokens distributed to the app developer


0 < π(u) < 1 amount of tokens distributed to user


\( \sum_{u=1}^{nu} = 1 \)


  • with π(u) = ​\( \frac{1}{nu} \)​, every user, who is participating at the opinion event is getting an equal amount of tokens

Amount which a customer  c∈1,…,nC paid for data:

p(c) = γ0 + φ(nU (t(c)) (a monotonically increasing, but concave φ(.)

  • if there are more users at the point when a customer buys data, the data are more expensive. Increase of cost is degressive
  • e.g.: ​φ(x) = ​​​\( \sqrt{x} \)​ or ​φ(x) = γ ln(x)
  • another possibility is to increase the price for the data when bought too early. In this case, would need to decrease and increase afterwards

Income at opinion events at moment t = τ:


E = ​​\( \displaystyle\sum_{c=1}^{nc} p(c) \)



E·α are the tokens being generated at an opinion event and stored at SLANT

E · (1 − α) are the tokens being generated at an opinion event and distributed to the app developers and the users

E · (1 − α) · β distribution to the app developer

E·(1−α)·(1−β) distribution to the users

E·(1−α)·(1−β)·π(u) distribution to user u



This is a very first approach to an ecosystem calculation. We are currently working on this topic. Feel free to get in touch if you are a rockstar in that area!


Request for Comments

More to come soon!


In the meanwhile:

Contact us to get to know more details and join the Slant community on Telegram!

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