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When users initiate a DAO, they will be asked to choose from some structural pre-sets. DAOs can encounter issues with scalability and resilience, and there are different approaches to solve these problems.
Highest resilience is not very scalable. The extreme example is an absolute majority voting mechanism: every member must vote on every decision, and at least 51% in favor would be a passing outcome. Requiring too much attention from a large number of DAO members makes the system unscalable which is why organizations typically become less effective at decision making as they grow. Having everyone vote on every decision is slow and doesn't always follow a logical path or vision. As a DAO grows in size (number of agents), and scope (which comes with more fund allocation decisions), the DAO decision-making system must scale to allow for a higher number of effective decisions in a given period of time.
The problem is, focusing only on scalability is not very resilient. When very few members get to represent the larger majority's decisions, there is a high chance those decisions won’t align well with the opinion of the majority. Requiring too little input from the majority creates a potential for a lack of resiliency to faulty decisions.
Since not everyone can give their full attention to every vote, scalable resilience is when the DAO decisions closely resemble the global opinion of all members, but where votes do not require attention from everyone. To try and find balance between these trade-offs, Paideia will offer various governance structures.
When Paideia is first released (the MVP on Ergo), the base governance option will be either standard voting with quorum. The platform will add more options as funding allows.
Optimistic governance is a system where only whitelisted individuals can create proposals, and all proposals will be passed by default unless challenged by token holders. If a proposal is challenged, there will be a vote available to all DAO members to determine whether the proposal passes or not.
This system is highly scalable because there can be a small number of individuals who create proposals, and as long as those proposals are not unreasonable, the majority voters will likely not challenge them. Anything unchallenged passes automatically, so a vote is not required. This is why its very scalable. It maintains some level of resilience because anyone in the DAO can challenge a proposal.
One drawback can be that if a malicious actor holds a whitelist position, they could submit many proposals to try to sneak through one that is not in the best interest of the DAO. It is difficult for everyone to monitor all proposals. So to mitigate that, each proposal submitted by whitelisted individuals requires them to pay a collateral. If the proposal goes through unchallenged, the collateral is returned to the proposer. However, if someone wishes to challenge a proposal, they must put up an equal collateral. The outcome of the vote determines who gets to keep the collateral, and the losing side's collateral is distributed to voters.
This means that a malicious voter can't just block all proposals for the fun of it, since they must put up their own money to do so. It also means a malicious proposer will be financially disincentivized to submit proposals that likely won't pass.
Originally proposed by Ralph C. Merkle, this form of governance attempts to eliminate several of the known drawbacks found in the modern democratic voting process.  Because this system is significantly more complex than the others, it will not be offered in the first iteration of Paideia, but will be added later as the details are worked out.
Holographic consensus connects a prediction market to the democratic process, and rather than having individuals vote on proposals, it allows them to rate their satisfaction with the decisions based on how they feel those decisions affect their individual welfare.
The system can be rather complicated to explain, and thus is beyond the scope of this document. A future document explaining Holographic Consensus will be produced and shared with the community prior to this functionality being added to the Paideia platform.