Procedural Votes:

One of the features of the legislative process (in US, at least) is that legislation is first considered in committees and after several procedural votes, the entire legislative body can cast a “yes” or “no” vote. The last part is what most people see or hear in the news and is what’s implemented in most DAOs.

Having procedural votes is helpful to ensure that all legislation have been considered in the same manner and meets certain requirements. For example, budget related bills can be required to have an independent audit before it can be considered for a full vote.

Why is this important? Not ever member of the DAO will have time to read every proposal in detail. Having standardized processes ensure that when proposals comes up for a vote, there are no surprises.

Example: Congressional Budget Resolutions cannot enact spending budgets, but sets targets for other groups to follow. If you don’t care about reading through the full budget, but do care about your priorities getting funding, just make sure to attend the budget setting meeting and vote there, instead of looking at every single proposal for items related to you.

Implementation:

A simple implementation of procedure vote is to have to classes of proposals, process proposals and execution proposals. The purpose of process proposals is to advance an proposal through a process that the DAO determines to be warranted while the purpose of an execution proposal is to execute the decision of the DAO.

For example, if the DAO have a budget. A simple process proposal could be to require at least N people to have sign the proposal. A more complicated process would be to at least N% of people sign the proposal with “I’m not opposed to this” (see previous article on what types of votes to cast). Members don’t have to support a budget proposal at the initial stage, they just have to not oppose it. Why? The proposed budget might have nothing to do with what a member is interested in, but you’d still want people to provide oversight of the budgeting process.

After the “not opposed vote”, the proposal could turn into an execution proposal. For execution proposals, the voting requirement might be 75% of the votes (doesn’t have to be 1 person, 1 vote) PLUS an executive of the DAO to approve. After which, the execution now falls under that particular executive.

Another example, an investment club might require limited partners to support and general partners to execute. The result of the investments could be distributed first to the executing general partner and voting limited partners, before distributing to the entire investment club as a whole. This creates an incentive for people to vote. How to avoid people voting “yes” on everything? Those who have voted will have to contribute a little more to the budget.

Summary:

DAOs are the perfect vehicles for implementing logic based procedures that can be used for governance. Unlike in real life, where it’s hard to keep track of who has voted and what was the result, smart contracts can effectively keep track of what’s the status of proposals.

A simple implementation would be to require proposals with budgets to have no major opposition before an actual vote to execute the budget. This setups a nice check and balance system to ensure the DAO is functioning efficiently.

That’s it for this article. Stay tuned for the last one on thoughts on representation. That is, how does one person, one vote work if a voting entity is another DAO?!

TLDR: Using multiple vectors as a data structure for votes increase complexity, but can potentially be more revealing of voter preferences, which is the ultimate desire of voting.

Introduction

Votes historically has been a binary, “aye” vs “nay”, or a multiple choice “this one”. This allowed for easy summarization and decision making. This reductionist approach to decision making allows for clean outcomes and clearer next steps. In forgoing a more complicated voting mechanism, we get easier consensus and incremental progress, both of which is preferable to no decision at all.

However, with DAOs, we have both the computing power and the ability to express complex logic. Therefore, this series tries to explore ways to improve decision making process while reducing the cost of added complexity

Quick Summary of this Series:

• Representation of votes as a data structure: vectorize preferences

• Separation of data and compute: Decision making logic with richer data 

• Proxy and Republics: Participation and individual cost of voting

Votes as Data Structure

The goal of voting and governance is to act according to some preference of the electorate. A simple “yes” “no” is the most direct form of preference.

However, we can also outline (at least) the following dimensions to describe the relationship between a potential voter and a simple pass/no pass issue:

• How important is this issue to me?

• How supportive am I of this issue and want to see it passed?

• How happy/not happy would I be if this issue were to pass?

• How happy/not happy would I be if this issue were to fail?

For each dimension, there is also a range of “very”, “neutral”, to “not very” (calling this a vectored vote).

Why increase the complexity of voting when the current system is already perfectly good at directing governance?

Binary votes (“Yes”, “No”), strictly speaking, is not a preference, but instead an instruction. Some will say that instructions are the most direct form of preferences and therefore the best.

However, the issue with direct instructions is that many governance issues tend to be resource allocation problems, which are ill suited for “do” “not do” instructions. For example, an electorate can choose “do” for multiple fiscal programs, but the total amount of expenditures is beyond the capabilities of the treasury. Often, what happens after is not another election to determine what are the priorities, but a murky process to “accomplish” some of the instructions at the expense of others that is often not privy to public discussion.

With a multidimensional and vectored voting structure, we have more data to assess the predicated outcomes of different actions with a focus on maximizing welfare of the most amount of people. The predicated outcomes can themselves be subject to a governance vote (“accept only packages where my utility is > 60”) as a final step. With delegation and proxy voting, the process can be very streamlined compared with in-real-life runoff elections.

Lastly, The issue of “the tyranny of the masses” will be addressed in a later piece when we discuss how to make decisions with richer data.

Conclusion

The current performance of competitive electoral processes leaves much to be desired. A strict “do”, “not do” approach to governance is unambitious, but delivers subpar results, specially when taking into account various electoral procedural “features” that doesn’t benefit the electorate.

By disaggregating voter preferences and using a vectorized approach, we hope electoral preferences might be better expressed. And though a more complex expression of electoral preferences, we hope more modern governance structures, such a DAO, might make decisions that result in better outcome for its participants.