Vitalik Buterin: The good and bad sides of collaboration
By Vitalik Buterin& NBSP;
Original: https://vitalik.ca/general/2020/09/11/coordination.html
Mabe lab
"Collaboration" -- the ability of a large group of actors to work together for their common good -- is one of the most powerful forces in the universe. It is embodied in a king who USES an oppressive dictatorship to comfortably rule a country, while the people can rise up and overthrow him. It can be seen in allowing global temperatures to rise by 3-5°C on the one hand, and in working together to stop them from rising a little when they do. Collaboration is the key to keeping companies, countries and any social organization of a certain size functioning.
Collaboration can be many ways to improve: information spread faster, better specifications to determine which behavior is classed as cheating and impose a more efficient way of punishing, stronger or more powerful organization and contract tools such as intelligence, allowing low-trust scenarios interaction, governance, technology (vote, shares, decision market...) , and more. And the fact is that every decade, we're getting better at collaboration.
But collaboration also has a dark side that is philosophically very counter-intuitive: While "everybody working with everybody" is a much better outcome than "everybody working for themselves," that doesn't mean that everyone taking a step toward more collaboration is necessarily beneficial. If collaboration is enhanced in an unbalanced way, the results can easily be harmful.
We can present this problem on a map, but there are actually many, many dimensions on the map, instead of two drawn.
In the lower left corner, "Everybody for themselves," is where we don't want to be. And on the top right, "Full collaboration," which is ideal, but probably not possible. But the vast expanse in the middle, far from being a gentle ascent, is full of reasonably safe and productive places that might be ideal for us to settle in and avoid many deep, dark pits.
Hobbesian Hobbesian holds that human nature ACTS out of selfishness and that society is an unrestricted, selfish and brutal competitive situation. From "Leviathan", by Thomas Hobbes, a 17th-century British political philosopher.
What are the dangerous forms of "partial collaboration" now, in which someone collaborates with a particular group but not with others, leading to the abyss? It is best illustrated by an example:
The citizens of a country died heroically in war for the good of the country... And this country is World War II Germany or Japan
The lobbyist bribed a politician in return for his adoption of the lobbyist's preferred policy
Someone sells his vote in an election
All the sellers of the product in the market collude to raise prices at the same time
A large blockchain miner colluded to launch 51% of the attacks
In all of these cases, what we've seen is a group of people coming together and cooperating with each other, to the great detriment of the group outside the circle of collaboration, to the substantial detriment of the world as a whole. In the first case, all are victims of aggression from the above-mentioned countries, who are outside the circle of cooperation and have suffered great losses as a result; In the second and third cases, people affected by decisions made by corrupted voters and politicians; In the fourth case, it's the customer; In the fifth case, there are uninvolved miners and blockchain users. This is not a mutiny of individuals against a group, but a mutiny of a group against a wider group, often the whole world.
This kind of local collaboration is often referred to as "collusion," or "collusion," but it's important to note that the scope of what we're talking about is quite broad. In normal contexts, the term "collusion" is often used to describe relatively symmetric relationships, but in many of these cases, there is a strong asymmetry. Even a restrictive relationship (" Vote for my favorite policy or I'll publicly expose your affair ") is a form of collusion in this sense. For the rest of this article, we will use the word "collusion" (or, perhaps more appropriately, "collusion") in general to refer to this type of "undesirable collaboration."
Evaluate intentions, not actions (!)
An important feature of lesser collusion cases, in particular, is that one cannot determine whether an action is an unexpected conspiracy simply by looking at the action itself. The reason is that the actions a person takes are the result of a combination of the person's internal knowledge, goals and preferences and the external incentives imposed on the person, so that actions taken in collusion tend to overlap with actions taken voluntarily (or in benign collaboration).
Consider, for example, collusion among sellers (a type of antitrust violation). If they operate independently, the three sellers may each set the price of a certain product at between 5 yuan and 10 yuan. The price difference within the range reflects factors such as sellers' internal costs, differences in wage willingness, supply chain problems and so on. But if the sellers conspire, they may set the price between 8 yuan and 13 yuan. Again, this price range reflects different possibilities regarding internal costs and other hard-to-see factors. If you see someone selling the product for $8.75, are they doing something wrong? You can't tell without knowing if they're working with other sellers! It is not a good idea to have a law saying that the product will sell for more than $8, and perhaps it is reasonable that the current price must be high. But having a law against collusion, and successfully enforcing it, has the desired result -- if the price has to be that high to cover the seller's costs, you get $8.75, but if the factors driving the price up are naturally low, you don't get that price.
This is also true in cases of bribery and vote-trafficking: it is likely that some people voted orange legally, but others voted Orange because they were bought. From the point of view of the people who decide the rules of the voting system, they don't know in advance whether the Orange Party is good or bad. But what they do know is that a voter who votes on the basis of what he really feels does a pretty good job, but a voter who is free to buy and sell a ballot does a pretty bad job. This is because vote-trafficking is a "tragedy of the Commons" : each voter gets only a small share of the benefits from the right vote, but if they vote according to the briber's wishes, they get the whole bribe. The bribe needed to attract each voter would therefore be far less than the cost of actually compensating the public for any policy the bribers wanted. So a vote to allow vote-selling would soon collapse into Plutocracy.
Understand game theory
We can go further and look at this from a game theory perspective. In the version of "game theory" that focuses on personal choice -- that is, assuming that every participant is NBSP; Independent & have spent There is a mathematical proof of the version of the decision not to allow groups of agents to work for their common good: there must be at least one stable Nash equilibrium in any game. In fact, the mechanism designer has a great deal of freedom to NBSP; Design & have spent Play to achieve specific results. But in a version of game theory called cooperative game theory, which allows for the possibility of alliance cooperation (such as "collusion"), we can show that there is a large class of games that does not have any stable outcome (called "Core" (game theory terminology: Core)). In this kind of game, no matter what the current situation is, there are always some leagues that can profit from it.
Note: This conclusion is called the Bondareva -- Shapley theorem.
An important part of this inherently unstable set of Games is the Majority Games. The majority game is formally described as an agent game in which any subset of the more than half of the agents are paid a fixed sum and given to themselves -- an arrangement eerily similar to many other situations in corporate governance, politics and human life. That is, if there is some kind of fixed resource pool and some kind of current established resource allocation mechanism, 51% of the participants are NBSP; Inevitably & NBSP; Conspiracies to seize control of resources, no matter what the current allocation is, will always produce conspiracies that are profitable for the participants. However, this plot is vulnerable to potential new plots, which may include a combination of former conspirators and victims... And so on.
The fact that the instability of majority games in cooperative game theory, as a simplified general mathematical model, is grossly underestimated is why there is likely to be no "end of history" in politics, and no system that has proved entirely satisfactory; Personally, I think it is much more useful than the more famous Arrow theorem.
Arrow's Theorem, also known as Arrow's paradox, means that there is no ideal election mechanism holding the three principles of fairness, pareto efficiency, non-dictatorship and independence.
Again, the core dichotomy here is not "individuals and groups"; For a mechanism designer, "individuals and groups" are surprisingly easy to deal with. "The group and the wider group" is the challenge.
Decentralisation as anti-collusion
But there is another, brighter, more operational conclusion from this line of thinking: if we want to create stable mechanisms, we know that an important factor is to find ways to make collusion, especially large-scale collusion, harder to happen or sustain. In the voting scenario, we have a "secret ballot" -- which ensures that voters have no way to prove their vote to a third party, even if they want to. (MACI is a project that attempts to use cryptography to extend the principle of secret voting to an online environmentNote [1]). This undermines trust between voters and bribers and severely limits the possibility of unwelcome collusion. In the case of antitrust and other corporate malfeasance, we tend to rely on whistleblowers, and even reward them, with clear incentives for participants in harmful collusion to defect. And in the broader public infrastructure, we have that very important concept: decentralization.
One naive view of why decentralisation is valuable is that it reduces the risk of a single point of technical failure. This is often true in traditional "enterprise" distributed systems, but in many other cases we know that this is not enough to explain what is happening. Look at the blockchain. A large pool publicly showing how they distribute their nodes and network dependencies internally will do little to quell community members' fears of mining centralization. And a picture like this, showing 90 percent of the bitcoin hash power at the time on the same conference panel, is pretty scary:
But why is this picture so scary? From a "decentralized, fault-tolerant" perspective, large miners can talk to each other without doing any harm. But if we think of "decentralization" as barriers to harmful collusion, that picture becomes pretty scary, because it shows that those barriers are not as strong as we think. Now, the fact that those barriers are far from zero, that those miners can collaborate easily and are probably all in the same WeChat cluster, doesn't mean that bitcoin is "actually no better than a centralized company."
So what are the remaining barriers to collusion? Some of the major obstacles include:
Moral barriers: In Liars and Outliers, Bruce Schneier reminds us that many "security systems" (door locks, warning signs that people will be punished...) It also has the moral function of alerting potential wrongdoers that they are about to commit serious violations that they should not do if they want to be a good person. Decentralisation serves this function.
Internal negotiations fail: Individual companies may start demanding concessions in return for participation in collusion, which can lead to an outright stalemate (see "the hostage problem" in economics).
Anti-collaboration: A system is decentralized, which makes it easy for non-complicit actors to make a fork, strip off the conspiratorial attackers, and then continue running the system from there. The threshold for users to join the bifurcation is very low, and the intention of decentralization will form the moral pressure in favor of participating in the bifurcation.
Risk of defection: It is much harder for five companies to join forces for evil than it is for uncontroversial or benign purposes. The five companies don't know each other very well, so it's possible that one of them refuses to participate and blows the whistle quickly, making it difficult for participants to judge risk. Individual employees within the company may also whistle.
Taken together, these obstacles are indeed substantial -- often substantial enough to deter a potential attack, even if all five companies are perfectly capable of coordinating quickly to do something legitimate. For example, ethereum miners are perfectly capable of collaborating to increase the GAS cap, but that doesn't mean they can so easily collude to attack the blockchain.
The experience of blockchain shows that designing protocols as institutional decentralized structures is often a very valuable thing, even when it is known in advance that most activities will be dominated by a small number of companies. The idea is not limited to blockchain; it can also be applied in other contexts (see antitrust applications, for example)Note [2]).
Fork as anti-collaboration
But we cannot always be effective in preventing harmful collusion. And to deal with the cases where harmful collusion does occur, it would be better to make the system more resistant to it -- more expensive for the collaborator and easier for the system to recover from.
We can do this through two core operating principles. (1) Support anti-collaboration, and (2) bear interest risk "Skin in the game". The idea behind anti-collaboration is this: We know that we can't design systems to be passively robust against collusion, in large part because there are so many ways to organize collusion that there's no passive mechanism to detect it, but what we can do is actively respond to collusion and do it -- NBSP; Counterattack.
The owner of a horse has a "Skin in the game". They have the best say in the outcome of the race.
In digital systems, such as blockchain (which can also be applied to more mainstream systems, such as DNS), a major and key form of anti-collaboration is "bifurcation".
If a system is taken over by a pernicious alliance, the dissenters can get together and create an alternative version of the system that has (mostly) the same rules, except that it eliminates the power to attack the alliance control system. In the context of open source software, forks are easy; The main challenge in creating a successful fork is usually to gather the required "legitimacy" (" common sense "in game theory) and get everyone who disagrees with the direction of the main alliance to follow you.
It's not just theoretical; It has been successfully implemented, most notably by the Steem community's resistance to hostile takeover attempts, resulting in a new blockchain called Hive, in which the original antagonist has no rights.
The market and Skin in the game
Another type of strategy for resisting collusion is the concept of "Skin in the game". In this case, "Skin in the game" basically refers to any mechanism that holds individual contributors in the decision solely responsible for their contributions. If a group makes a bad decision, those who approve it must suffer more than those who try to dissent. This avoids the "tragedy of the Commons" inherent in the voting system.
Forking is a powerful form of disharmony precisely because it introduces "Skin in the game." In Hive, Steem's community fork that sets aside hostile takeover attempts, COINS used to vote for a hostile takeover are largely deleted in the new fork. It also affected individuals who were key players in the attack.
Markets in general are very powerful tools precisely because they maximize Skin in the game. Decision market (forecast market used to guide decision making; Also called & have spent futarchyNote [3]) is an attempt to extend this benefit of the marketplace to organizational decisions. Still, decision-making markets can solve only a few problems; In particular, they don't tell us which variables should be optimized in the first place.
Note: Futarchy is a form of new government proposed by the economist Robin Hanson, in which elected officials make policies and the public bet on different policies by speculating in the market, thus producing the most effective choices. See v. Buterin's article "On Collusion" [4].
Structured collaboration
All of which gives us an interesting view of what people who build social systems do. One of the goals of building an effective social system is to determine the structure of collaboration: which groups, and in what configurations, can come together to advance their group goals, and which groups cannot?
Different collaboration structures result in different results
Sometimes more collaboration is good: it is better when people can work together to solve their problems collectively. At other times, more collaboration is dangerous: a small number of participants may use collaboration to disenfranchise others. At other times, more collaboration is needed for another reason: to enable wider societies to "fight back" against collusion in attacking systems.
In all three cases, these objectives can be achieved through different mechanisms. Of course, it's very difficult to block communication directly, and it's very difficult to make collaborative work perfect. But there are many choices between the two that can produce powerful results.
Below are several possible collaborative structuring techniques.
Privacy technologies and norms that make it difficult to prove how you behave (secret voting, MACI, and the like).
Consciously decentralize, assigning control of a mechanism to a large group of people who are known to have poor coordination.
Decentralization of physical Spaces, separating different functions (or different shares of the same function) into different locations (for example, see Samo Burja on the link between urban decentralization and political decentralization).
Decentralizing between role-based constituencies, separating different functions (or different shares of the same function) from different types of participants (for example, in the blockchain, "core developers", "miners", "coin holders", "application developers", "users").
Schelling points allow large groups of people to collaborate quickly around a path forward. Complex Schelling Points might even be implemented in your code (for example, how to recover from a 51% attack).
Use a common language (or split control between multiple supporters using different languages).
makeVote by person rather than by currency/share to greatly increase the number of people needed to influence decisions through collusion.
Encourage and rely on defectors to alert the public to impending collusion.
Note: Schelling points are proposed by The American economist Thomas Schellin in his book "Conflict Strategies". In the absence of communication, if people know that others are trying to do the same thing, their actions will tend to converge on a conspicuous focus. For example, if two people meet in New York without communicating in advance, they will choose Grand Central Station with great probability, which forms a natural Schelling Point.
None of these strategies are perfect, but they can be used in a variety of situations and with varying degrees of success. Furthermore, these techniques can and should be combined with mechanism designs that attempt to make harmful collusion as unprofitable and risky as possible; "Skin in the Game" is a very powerful tool in this respect. Which combination works best depends on your case.
[1] https://github.com/appliedzkp/maci
[2] https://papers.ssrn.com/sol3/papers.cfm? abstract_id=3597399
[3] https://blog.ethereum.org/2014/08/21/introduction-futarchy
[4] https://vitalik.ca/general/2019/04/03/collusion.html
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