Blockchain Upgrade as a Coordination Game P2PFISY 2018 Stephanie - PowerPoint PPT Presentation

Blockchain Upgrade as a Coordination Game P2PFISY 2018 Stephanie Hurder Prysm Group July 27, 2018

Motivation Blockchain organizations are struggling with how to design decentralized governance systems • Salient example: EOS governance Long history in economics of studying social choice : how best to design a decision-making system for a group (Arrow (1951), Mueller (2003)) Unlike most standard governance settings, blockchain can experience hard forks • An unhappy group of users can secede from the chain and start its own chain • Bitcoin had many major policy-driven hard forks (Cash, Gold, Private, ...) • The DAO hack → Ethereum hard fork (Classic) The founders of a blockchain platform face two novel questions 1. How to evaluate when hard forks are socially optimal and should occur 2. How to design a governance system so that forks only happen when they are socially optimal P2PFISY 2018 | July 27, 2018

This Paper We build a game-theoretic model of policy choice on a blockchain • Community is choosing between a status quo policy or a policy upgrade • Blockchain exhibits network effects : I get more utility from a blockchain when there are more other users on my chain (Shapiro and Varian (1999)) • Users who don’t like the policy choice on the main chain can fork We classify under what conditions a hard fork is an equilibrium, and in what cases it is socially optimal for a community We explore in what circumstances standard voting mechanisms (majority vote, quadratic voting) would guide the community to the socially optimal outcome P2PFISY 2018 | July 27, 2018

Results 1. Hard fork is an equilibrium if the policy change is sufficiently big, and if both policies have sufficient support 2. Hard fork can be socially optimal, but can also occur as coordination failures (everyone has ex post regret) 3. Once hard forks are an equilibrium, which governance system is better is sensitive to hard-to-observe population parameters 4. The most realistic method to prevent suboptimal hard forks is to change the policy proposal process P2PFISY 2018 | July 27, 2018

Unit mass of users v ij (x): Value to user i of participating on chain j with fraction of the ➔ The math community x ➔ Results under individual ● No utility without other users: v ij (0) = 0 choice ● Network effects: v’ ij (x) >0 ➔ When is forking socially optimal ➔ Performance of standard Two types of users: governance systems ● Type A: Prefer status quo policy given fixed x (Fraction � ) ● Type B: Prefer upgrade policy given fixed x (Fraction 1- � ) P2PFISY 2018 | July 27, 2018

What happens in a community with no governance? Individual users choose between two chains: status quo and upgrade ➔ Model set-up ➔ Independent strategic q j : Fraction of community on status quo chain s.t. type j is indifferent chain choice between status quo and upgrade (Lemma 1) ➔ When is forking socially optimal Proposition 1: Nash equilibria are ➔ Performance of standard ● Everyone on the status quo chain governance systems ● Everyone on the upgraded chain ● If � ∈ [q B , (1 - q A )]: ○ Users who prefer status quo on status quo chain ○ Users who prefer upgrade on upgrade chain P2PFISY 2018 | July 27, 2018

Two common measures of social welfare: ● Total surplus maximization: Maximize the sum of the value of the user base ➔ Model set-up ● Pareto Optimality: Can’t make one group better without making ➔ Results under individual another group worse choice Results: ➔ When is forking socially ● Everyone on a single chain is always Pareto Optimal optimal ● One single-chain equilibrium dominates the other in total surplus ➔ Performance of standard ● A hard fork can be governance systems ○ Nash Equilibrium for a range of � (Prop 1) ○ Pareto Optimal for smaller range of � (Prop 4) ○ Surplus maximizing for even smaller range of � (Prop 5) P2PFISY 2018 | July 27, 2018

Two common measures of social welfare: ● Total surplus maximization: Maximize the sum of the value of the user base ● Pareto Optimality: Can’t make one group better without making ➔ Model set-up another group worse ➔ Results under individual choice � = Fraction of users who prefer the status quo ➔ When is forking socially ❴ optimal ➔ Performance of standard governance systems 0 1 Total surplus max. Pareto Optimal Nash Equilibrium P2PFISY 2018 | July 27, 2018

Introduce one of two standard governance systems: ● Majority rule: policy preferred by larger fraction of users is implemented ● Quadratic voting: policy that maximizes total surplus is ➔ Model set-up ➔ Results under individual implemented (Posner and Weyl, 2015) choice ➔ When is forking socially Order of events: 1. All users start on single chain optimal ➔ Performance of standard 2. Voting on which policy to implement occurs 3. Chain implements policy selected by governance process governance systems 4. Hard fork occurs (if desired) Assume naive voting: users vote assuming everyone will stay together on a single chain P2PFISY 2018 | July 27, 2018

Neither leaves Minority leaves Majority leaves Each group the other Majority’s chain Minority’s chain leaves other’s group’s chain chain Majority’s chain has ➔ Model set-up highest total value ➔ Results under individual choice Minority’s ➔ When is forking socially chain has optimal highest total value ➔ Performance of standard governance systems Hard fork has highest total value Bigger policy change P2PFISY 2018 | July 27, 2018

Neither leaves Minority leaves Majority leaves Each group the other Majority’s chain Minority’s chain leaves other’s group’s chain chain Majority’s chain has ➔ Model set-up highest total value ➔ Results under individual Forks never choice Forks are happen Minority’s ➔ When is forking socially socially chain has optimal highest total optimal and value ➔ Performance of standard always happen governance systems Hard fork has highest total value Bigger policy change P2PFISY 2018 | July 27, 2018

Neither leaves Minority leaves Majority leaves Each group the other Majority’s chain Minority’s chain leaves other’s group’s chain chain Majority’s chain has ➔ Model set-up highest total value ➔ Results under individual Forks never Fork under choice happen majority rule Minority’s Forks are ➔ When is forking socially chain has optimal and optimal highest total always value ➔ Performance of standard happen governance systems Hard fork has highest total value Bigger policy change P2PFISY 2018 | July 27, 2018

Neither leaves Minority leaves Majority leaves Each group the other Majority’s chain Minority’s chain leaves other’s group’s chain chain Majority’s Fork under chain has ➔ Model set-up quadratic highest total voting value ➔ Results under individual Forks never choice happen Minority’s Forks are ➔ When is forking socially Fork under chain has optimal and optimal highest total quadratic always value ➔ Performance of standard voting happen governance systems Hard fork has highest total value Bigger policy change P2PFISY 2018 | July 27, 2018

Neither leaves Minority leaves Majority leaves Each group the other Majority’s chain Minority’s chain leaves other’s group’s chain chain Majority’s chain has ➔ Model set-up highest total value ➔ Results under individual Forks never Governance choice happen matters Minority’s Forks are ➔ When is forking socially chain has optimal and optimal highest total always value ➔ Performance of standard happen governance systems Hard fork has highest total value Bigger policy change P2PFISY 2018 | July 27, 2018

Implications and next steps Standard governance processes do not copy-paste well to blockchain if forks are an option • Policy proposal process is just as important as the voting process Assumptions that could be relaxed in future work: • Non-transferable utility: What happens if some users can (credibly promise to) pay off the others? • Naive voting: What if voters anticipate the possibility of a fork and vote accordingly? • Social planner’s objective: What if he/she wants to keep the chain together at all costs? Open question: a more effective, yet practical governance mechanism • Vickrey-Clarke-Groves mechanism is optimal but shown difficult to implement (Rothkopf, 2007) P2PFISY 2018 | July 27, 2018

Prysm Group regularly published blockchain industry articles: For questions or for more https://medium.com/prysmeconomics information on Prysm Group, https://medium.com/mit-cryptoeconomics-lab I can be reached at stephanie@prysmgroup.io MIT Sloan Executive Education recently launched a six-week Telegram: @stephaniehurder executive course for which we were industry contributors: https://executive.mit.edu/openenrollment/program/blockc Thank you! hain-technologies-business-innovation-and-application/ P2PFISY 2018 | July 27, 2018