Policy decisions are at the core of all governance models. Organizations must make decisions on which policies to implement in order to maximize future welfare. For a government, this could mean deciding budget allocation. Should a portion of the budget be allocated for infrastructure projects or for education? Which will result in greater GDP? Within a corporation, disputes could arise over whether or not to acquire a company. Metrics on share price or future revenue may be the deciding factors. In most cases of governance, such decisions are made using a range of Democratic or Autocratic processes. The former involves a voting process in which members of an organization or government cast votes (allocated through an egalitarian or proportional representation) where a plurality, majority, or supermajority is required to implement a decision. The latter involves a hierarchical model in which designated individuals make absolute decisions over their areas of control. Both of these models suffer from information inefficiencies, often resulting in the implementation of policies that poorly optimize future welfare.
Futarchy offers an alternative market based approach to governance.
In Futarchy, markets are used to decide on and implement policies. These markets follow a general form of “What will a future welfare metric be if a policy is implemented?” For example, a corporation could ask, “What will our Q4 revenue be if we fire our CEO?” and conversely, “What will our Q4 revenue be if we don’t fire our CEO?” Following this, speculators who believe they hold unique insights into the outcome of firing or keeping the CEO are incentivized to participate in these markets. If they think that revenue will be maximized by firing the CEO, then they will buy long shares in the expected revenue if the CEO is fired and short shares in the expected revenue if the CEO is not fired. Upon market closure, a decision is made corresponding to the greater expected outcome. In our CEO example, if the market value for expected Q4 revenue if the CEO is fired is greater than the revenue if CEO is not fired market, then the organization fires the CEO. Market participants are then rewarded depending on their accuracy in predicting future revenue.
In this model governance is both marketized and automated. Policies are determined by values found on an open market and implemented through bound delegates or an automated process. Prediction markets have shown to be the most efficient information aggregation tool leading to the prediction that Futarchy can more accurately identify policies that will optimize outcomes while also lowering bureaucratic overhead.
Futarchy holds the potential to revolutionize governance in a wide variety of institutions
Nearly all existing organizations can improve their model of governance by using an implementation of Futarchy. State governments can allow citizens to democratically vote on which metrics to optimize for and create markets to let the wisdom of the crowd inform how to reach those goals. Corporations can overhaul stockholder decision making using Futarchy while also reducing the need for high level management. Perhaps most interesting to the Ethereum and Blockchain ecosystem is the ability for Futarchy to provide a governance model for Decentralized Autonomous Organizations which is both effective and less reliant on centralized trust and decision-making processes.
Robin Hanson, the inventor of Futarchy and father of modern prediction markets, argues that
Futarchy seems promising if we accept the following three assumptions:
1. Democracies fail largely by not aggregating available information.
2. It is not that hard to tell rich happy nations from poor miserable ones.
3. Betting markets are our best known institution for aggregating information.
The first of these conditions has become evident through political gridlock between parties, as well as yellow and captured journalism leading to a poorly informed populace. The second condition is provided by widely available metrics such as income per capita and GDP, and the last is a conclusion of the efficient market hypothesis. Primary barriers to Futarchy adoption are lack of real world case studies, lack of general purpose Futarchy solutions, and entrenched institutions that are resistant to new models. We plan to address the first of these problems by creating a general purpose Futarchy solution using a combination of Gnosis markets and Boardroom governance tools.
Thanks to a generous grant from the Ethereum foundation, Gnosis will be running a series of experiments to test the viability of Futarchy. Over the next two months we will be running at least three experiments that will test foundational assumptions toward the successful implementation of Futarchy. The first two experiments will test the ability of actors to manipulate the outcome of markets when incentive is provided. In the first of these experiments, a market will be created which is resolved by a smart contract verified to output 5 at a particular time. In the second experiment, the smart contract will resolve to either 0 or 10 dependent on a random seed. In each of these markets, an incentive will be provided to manipulators if they are able to push market values away from their expected outcomes. By providing this reward we simulate market participants who have incentive (likely by being shareholders in an organization) to misinform a Futarchy market and will be able to provide quantitative information regarding the viability of such schemes. In the third market, we will simulate Futarchy more directly with markets determined by Ethereum blockchain difficulty at a time in the future. Through these experiments and general tools which we plan to create on Gnosis, we aim to forge a solid platform for DAOs (and other types of organizations) to use Futarchy to inform and automate their decision making.
by Matt Liston