Takeaways from DFINITY’s blockchain governance

DFINITY: Governance through the Blockchain Nervous System (BNS)

DFINITY is a Blockchain that distinguishes itself, among other things, by having algorithmic governance. DFINITY’s tokens are called dfinities.

Essential to DFINITY’s blockchain is its so-called Blockchain Nervous System (BNS). In order to implement a change in DFINITY, each proposed change must go through four steps.

  1. Proposal submission
  2. Voting
  3. Proposal evaluation​
  4. Proposal implementation

Proposal submission

Proposals, which fall into different categories such as „Economics“, „Policy“, or „Protocol“ are submitted by paying a submission fee. If the proposal is adopted, this submission fee is returned. This fee should prevent spam and encourage high-quality proposals.


In DFINITY Neurons (entities that have voting power; see below) vote on the submitted proposals.

DFINITY’s Neurons

In DFINIY Neurons are voting entities and are run by people using a dedicated software. Everybody can create a neuron by making a financial deposit using dfinities. This deposit regulates the neuron’s voting power. The higher the deposit, the more voting power the neuron has. Deposits can be withdrawn after a minimum of three months (duration is possibly subject to change). Deposits should incentivize good decision making; bad decisions carried out by the BNS might lead to bad network performance, in turn lowering the tokens’ value and thus the deposit’s value. Moreover, deposits are used to calculate reward. Neurons that vote are rewarded dfinities. The reward height is proportional to the deposit; the higher the deposit the higher the reward.

Neurons can vote manually or automatically.

Manual voting by manually issuing votes
The user running the neuron software can vote on proposals. For voting, she may choose between „Adopt”, „Reject”, and “Pass”. The significance of the user’s vote depends on the neuron’s deposit.

Automatic voting by following other neurons
Automatic voting is similar to liquid democracy. In this scenario, the users’ neurons copy the decisions made by other neurons. Users can configure a “follow list” for which proposal type (e.g economics, policy, or protocol) to follow which neuron’s vote. The rationale behind this delegation is that users lack expertise in certain areas and therefore give their vote to users of whom they believe that they have the right expertise. For instance, a user decides that she doesn’t want to vote on economics-related proposals because she lacks the right knowledge. Therefore, she gives her voting power to a user of whom she believes will make the right economics related decisions. In each automatic voting decision the algorithm follows the vote of the most powerful neuron in a cascading matter. That means that if the most powerful neuron from the user’s follow list has not voted, the vote of the next neuron will be copied and so on.

Proposal evaluation

In this evaluation stage, the proposal’s issues and solutions are evaluated. DFINITY has implemented three steps for this evaluation:

  1. Establishing legitimacy: Here the involved entities conduct a background check to ensure that the proposal and the originator of the proposal are legitimate. This step is cumbersome, very manual, and can even include live phone contact.
  2. Problem evaluation: In this step it is validated whether the issue identified in the proposal is really a problem.
  3. Solution evaluation: Finally, the proposed solution’s code is evaluated. The code is checked to ensure that it will fix the problem and that it won’t affect other parts of the system.

In all of these three steps the parties doing the research are rewarded by DFINITY’s BNS. This reward, however, must be paid by the entities submitting the proposal. The whole process can be expensive.

Proposal implementation

For implementation, DFINITY’s Blockchain Nervous System distinguishes between two different proposal types, namely active and passive ones.

  • Passive proposal: A passive proposal equals changing the telemetry of the system (e.g. mining reward). In this case, the new information is updated on the BNS smart contract. This is similar to Qtum’s Decentralized Governance Protocol (see below).
  • Active proposals: Here DFINITY’s BNS changes things outside its own smart contract. For such amendments, special code is required which DFINITY has added to the EVM (Ethereum Virtual Machine). One example for active proposals is the termination of certain malign smart contracts.

Built-in versioning system

One rationale behind the deposits required to create neurons is to mitigate malign behavior. If a participant votes for malign proposals and these proposals are implemented, the network will suffer. In turn, the dfinities and thus the malign actor’s dfinities suffer. (this incentivisation doesn’t, however, account for malign actors trying to short the market). Nevertheless, bad proposals that harm the network in a substantial way might get implemented (knowingly or not) anyway. To mitigate fatal changes, DFINITY has integrated a versioning system. With this versioning system users can reverse malign changes through hard forks. Furthermore, neurons that voted for that malign proposal are terminated during this fork.


  • Malign changes are inevitable. Thus, having a roll-back process in place is crucial
  • A blockchain’s own token is very useful in incentivizing good behavior, although not a perfect solution (e.g. shorting the market is still possible)​
  • Liquid democracy can prevent voting centralization but still includes many voters
  • Governance models can be improved through algorithmic decisions
  • An expensive proposal process can hinder innovation because proposals are avoided due to high costs. Finding the right balance between preventing spam and hindering innovation remains experimental.
  • Validating the identity of submitting entities and their proposals remains cumbersome and expensive. The irony is that Blockchain is supposed to remove exactly this counterparty risk.
  • Categorizing proposals (e.g economics, or policy) is helpful for refining the governance process

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