Quadratic voting


Quadratic voting is a collective decision-making procedure where individuals allocate votes to express the degree of their preferences, rather than just the direction of their preferences. By doing so, quadratic voting helps enable users to address issues of voting paradox and majority-rule. Quadratic voting works by allowing users to 'pay' for additional votes on a given matter to express their support for given issues more strongly, resulting in voting outcomes that are aligned with the highest willingness to pay outcome, rather than just the outcome preferred by the majority regardless of the intensity of individual preferences. The payment for votes may be through either artificial or real currencies. Quadratic voting is a variant of cumulative voting in the class of cardinal voting. It differs from Cumulative voting by altering "the cost" and "the vote" relation from linear to quadratic.
Quadratic voting is based upon market principles, where each voter is given a budget of vote credits that they have the personal decisions and delegation to spend in order to influence the outcome of a range of decisions. If a participant has a strong support for or against a specific decision, additional votes could be allocated to proportionally demonstrate the voter's support. A vote pricing rule determines the cost of additional votes, with each vote becoming increasingly more expensive. By increasing voter credit costs, this demonstrates an individual's support and interests toward the particular decision. If money is used, it is eventually cycled back to the voters based upon per capita. Both Weyl and Lalley conducted research which they claim to demonstrate that this decision-making policy expedites efficiency as the number of voters increases. The simplified formula on how quadratic voting functions is:
Number of votes"Vote credit" cost
11
24
39
416
525

The quadratic nature of the voting suggests that a voter can use their votes more efficiently by spreading them across many issues. For example, a voter with a budget of 16 vote credits can apply 1 vote credit to each of the 16 issues. However, if the individual has a stronger passion or sentiment on an issue, they could allocate 4 votes, at the cost of 16 credits, to the singular issue, effectively using up their entire budget. This mechanism towards voting demonstrates that there is a large incentive to buy and sell votes, or to trade votes. Using this anonymous ballot system provides identity protection from vote buying or trading since these exchanges cannot be verified by the buyer or trader.

Properties of quadratic voting

Efficiency

By contrast, majority rule based on individual person voting has the potential to lead to focus on only the most popular policies, so smaller policies would not be placed on as much significance. The larger proportion of voters who vote for a policy even with lesser passion compared to the minority proportion of voters who have higher preferences in a less popular topic can lead to a reduction of aggregate welfare. In addition, the complicating structures of contemporary democracy with institutional self-checking will continue to expand its policies, so quadratic voting is responsible for correcting any significant changes of one-person-one-vote policies.

Robustness

Robustness of a voting system can be defined as how sensitive a voting scheme is to non-ideal behavior from either voters or outside influence. The robustness of QV with respect to various non-idealities has been studied, including collusion among voters, outside attacks on the voting process, and irrationality of the voters. Collusion is possible in most voting schemes to one extent or another, and what is key is the sensitivity of the voting scheme to collusion. It has been shown that QV exhibits similar sensitivity to collusion as one-person-one-vote systems, and is much less sensitive to collusion than the VCG or Groves and Ledyard mechanisms. Proposals have been put forward to make QV more robust with respect to both collusion and outside attacks. The effects of voter irrationality and misconceptions on QV results have been examined critically by QV by a number of authors. QV has been shown to be less sensitive to 'underdog effects' than one-person-one-vote. When the election is close, QV has also been shown to be efficient in the face of a number of deviations from perfectly rational behavior, including voters believing vote totals are signals in and of themselves, voters using their votes to express themselves personally, and voter belief that their votes are more pivotal than they actually are. Although such irrational behavior can cause inefficiency in closer elections, the efficiency gains through preference expression are often sufficient to make QV net beneficial compared to one-person-one-vote systems. Some distortionary behaviors can occur for QV in small populations due to people stoking issues to get more return for themselves, but this issue has not been shown to be a practical issue for larger populations. Due QV allowing people to express preferences continuously, it has been proposed that QV may be more sensitive than 1p1v to social movements that instill misconceptions or otherwise alter voters' behavior away from rationality in a coordinated manner.

History of quadratic voting

The primary motivation for the creation of QV was that an optimal voting mechanism for decisions involving public goods was created in the 60's and 70's by Vickrey, Clarke, and Groves. Despite high initial excitement about this mechanism, including Vickrey receiving a Nobel Prize for the work, the VCG mechanism was not sufficiently robust and practical to be implemented, and the mechanism found almost no practical adoption. Quadratic voting was intended by its inventors to deliver similarly optimal outcomes as the VCG mechanism while being easier for people to use and understand, and being more robust with respect to collusion and other practical considerations. A mechanism closely resembling quadratic voting was first published in 1977 by Groves and Ledyard, with a similar mechanism being proposed by Hylland and Zeckhauser in 1980. More recently, E. Glen Weyl has done research on the mechanism, invented the name, and extensively promoted the mechanism. After circulating working papers on the idea starting in 2012, Weyl worked on QV with Steven Lalley and Eric Posner to further refine the formalism of quadratic voting and its applications.
Many experiments at various scales and simulations, and theoretical analyses have been done on quadratic voting since 2012. A major step in the adoption of quadratic voting for political purposes happened in April 2019, when the Democratic caucus of the Colorado House of Representatives used quadratic voting to make budgetary decisions. The experiment in Colorado was generally viewed as successful in that the budget allocations were reported to be reasonable, and the process was smooth. Several organizations and communities have formed to promote adoption of quadratic voting concurrent with its continued academic research, including , , and .

Criticisms of quadratic voting mechanisms

The most common objection to QV using real currency is that although it efficiently selects the outcome for which the population has the highest willingness to pay, willingness to pay is not directly proportional to the utility gained by the voting population. More specifically, the wealthy can afford to buy more votes relative to the rest of the population. This would distort voting outcomes to favor the wealthy in situations where voting is polarized on the basis of wealth. While the wealthy having undue influence on voting processes is not a unique feature of QV as a voting process, the direct involvement of money in the QV process has caused many to have concerns about this method.
Several proposals have been put forward to counter this concern, with the most popular being QV with an artificial currency. Usually, the artificial currency is distributed on a uniform basis, thus giving every individual an equal say, but allowing individuals to more flexibly align their voting behavior with their preferences. While many have objected to QV with real currency, there has been fairly broad-based approval of QV with an artificial currency.
Other proposed methods for ameliorating objections to the use of money in real currency QV are:
Many areas have been proposed for quadratic voting, including corporate governance in the private sector, allocating budgets, cost-benefit analyses for public goods, more accurate polling and sentiment data, and elections and other democratic decisions.
Quadratic voting was conducted in an experiment by the Democratic caucus of the Colorado House of Representatives in April 2019. Lawmakers used it to decide on their legislative priorities for the coming two years, selecting among 107 possible bills. Each member was given 100 virtual tokens that would allow them to put either 9 votes on one bill and 3 votes on another bill or 5 votes each on 4 different bills. In the end, the winner was , the Equal Pay for Equal Work Act, with a total of 60 votes. From this demonstration of quadratic voting, no representative spent all 100 tokens on a single bill, and there was delineation between the discussion topics that were the favorites and. The computer interface and systematic structure was contributed by , which is an open-source liquid democracy platform to foster governmental transparency.

Quadratic funding

in collaboration with Zoë Hitzig and E. Glen Weyl proposed quadratic funding, a way to allocate the distribution of funds based on quadratic voting, noting that such a mechanism allows for optimal production of public goods without needing to be determined by a centralized legislature. Weyl argues that this fills a gap with traditional free markets - which encourage the production of goods and services for the benefit of individuals, but fail to create outcomes desirable to society as a whole - while still benefiting from the flexibility and diversity free markets have compared to many government programs.
The Gitcoin Grants initiative is an early adopter of quadratic funding. Led by Kevin Owocki, Scott Moore, and Vivek Singh, the initiative has distributed more than $2,000,000 to open-source software development projects as of early 2020.