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Announcing World Trade Francs: The Official Ethereum Stablecoin 01st April, Ethereum scalability research and ethereum blog dao subsidy programs 02nd January, All of these technologies remedy key deficiencies of the blockchain design with respect to centralized servers: However, there is one piece of the puzzle that all approaches so ethereum blog dao have not yet managed to crack: Bitcoin brings to its users a rather unique set of tradeoffs with respect ethereum blog dao financial privacy.

Although Bitcoin does a substantially better job than any system that ethereum blog dao before it at protecting the physical identities behind each of its accounts — ethereum blog dao than fiat and banking infrastructure because ethereum blog dao requires no identity registration, and better than cash because it can be combined with Tor to ethereum blog dao hide physical location, the presence of the Bitcoin blockchain means that the actual transactions made by the accounts are more public than ever — neither the US government, nor China, nor the thirteen year old hacker down the street even need so much as a warrant in order to determine exactly which account sent how much BTC to which destination ethereum blog dao what particular time.

In general, these two forces pull Bitcoin in opposite directions, and it is not entirely clear which one dominates. With Ethereum, the situation is similar in theory, but in practice it is rather different.

Ethereum blog dao is a blockchain intended for currency, and currency is inherently a very fungible thing. There exist techniques like merge avoidance which allow users to essentially pretend to be separate accounts, with their wallet managing the separation in the background. Hence, Ethereum, as it stands today, will in many cases inherit the transparency side of blockchain technology much more so than the privacy side although those interested in using Ethereum for currency can certainly build higher-privacy cash protocols inside of subcurrencies.

Even if we solve scalability and blockchain data assets, will the lack of privacy inherent to blockchains mean that we simply have to go back to trusting centralized servers? Or can we come up with a protocol that offers the best of both worlds: What is this protocol? To skip the fun technical details and go straight to applications, click here. Secret computation networks rely on two fundamental primitives to store information in a decentralized way.

The first is secret sharing. Secret sharing essentially allows data to be stored in a decentralized way across N parties such that any K parties can work together to reconstruct the data, but K-1 parties cannot recover any information at all. N and K can be set to any values desired; all it takes is a few simple parameter tweaks in the algorithm.

The simplest way to mathematically describe secret sharing is as follows. We know that two points make a line:. To implement 3-of-N secret sharing, we just make a parabola instead, and give people points on the parabola:.

Parabolas have the property that any three points on a parabola can be used to reconstruct the parabola and no one or two points sufficeso essentially the same process applies. And, more generally, to implement K-of-N secret sharing, we use a degree K-1 polynomial in the same way.

There is a set of algorithms for recovering the polynomial from a sufficient set of points in all such cases; they are described in more details in our earlier article on erasure coding.

This is how the secret sharing DAO ethereum blog dao store data. Instead of every participating node in the consensus storing a copy of the full system state, every participating node in the consensus will store a set of shares of the state — points on polynomials, one point on a different polynomial for each variable that makes up part of the state. Now, how does the secret sharing DAO do computation? For this, we use a set of algorithms called secure multiparty computation SMPC.

The basic principle behind SMPC is that there exist ways to ethereum blog dao data which is split among N parties using secret sharing, perform computations on it in a decentralized way, and end up with the result secret-shared between the parties, all without ever reconstituting any of the data on a single device. SMPC with addition is easy. Thus, we have a rule: Multiplication by a known constant value works the same way: Multiplication of two secret shared values, unfortunately, is much more involved.

First, suppose that there exist values a and bsecret shared among parties P[1] … P[n]where a[i] represents the ith share of a and same for b[i] and b. We start off like this:. The answer is, surprisingly, yes, but with a ethereum blog dao problem: Hence, if we do multiplication more than once, the polynomial would become too big for the group of N to store.

To avoid this problem, we perform ethereum blog dao sort of rebasing protocol where we convert the shares of the larger polynomial into shares of a polynomial of the original degree. The way it works is as follows. Thus, P[j] now has c[i][j] for all i. Given this, P[j] calculates c[j]and so everyone has secret shares of con a polynomial with the ethereum blog dao degree as a and b.

To do this, we used a clever trick of secret sharing: This allows us ethereum blog dao move from a higher-degree polynomial to a lower degree polynomial but avoid revealing the values in the middle — instead, the middle step involved both layers being applied at the same time.

With addition and multiplication over 0 and 1, we have the ability to run arbitrary circuits inside of the SMPC mechanism. Hence, we can run whatever programs we want, although with one key limitation: There are two ways around this problem.

Second, as we will see, if we implement if statements inside the EVM, and run the EVM inside SMPC, then we can resolve the problem, leaking only the information of how many steps the EVM took before computation exited and if we really care, we can reduce the information leakage further, eg. The secret-sharing based protocol described above is only one way to do relatively simply SMPC; there are other approaches, and to achieve security there is also a need to add a verifiable secret sharing layer on top, but that is beyond the scope of this article — the above description is simply ethereum blog dao to show how a minimal implementation is possible.

Now that we have a rough idea of how SMPC works, how would we use it to build a decentralized currency engine? Now, since the blockchain is not transparent, we might expect the ethereum blog dao for two kinds of transactions that users can send into the SMPC: We define the two types of requests as follows:.

Essentially, the database is stored as a set of 3-tuples representing accounts, where each 3-tuple stores the owning pubkey, nonce and balance. To send a request, a node constructs the transaction, splits it off into secret shares, generates a random request ID and ethereum blog dao the ID and a small amount of proof of work to each share. The proof of work is there because some anti-spam mechanism is necessary, and because account balances are private there is no way if the sending account has enough ethereum blog dao to pay a transaction fee.

The nodes then independently verify the shares of the ethereum blog dao against the share of the public key supplied in the ethereum blog dao there are signature algorithms that allow you to do this ethereum blog dao of per-share verification; Schnorr signatures are one major category. If a given node sees an invalid share due to proof of work or the signatureit rejects it; otherwise, it accepts it. Transactions that are accepted are not processed immediately, much like in a blockchain architecture; at first, they are kept ethereum blog dao a memory pool.

At the end of every 12 seconds, we use some consensus algorithm — it could be something simple, like a random node from the N deciding as a dictator, or an advanced neo-BFT algorithm like that used by Pebble — to agree on which set of request IDs to process and in which order for simplicity, simple alphabetical order will probably suffice. So what does this formula do? It consists of three stages.

First, we extract the owner pubkey of the account that the request is trying to get the balance of. Because the computation is done inside of an SMPC, and so no node actually knows what database index to access, we do this by simply taking all the database indices, multiplying the irrelevant ones by zero and taking the sum.

Finally, we use the same database getting primitive to get the balance, and multiply the balance by the validity to get the result ie.

First, we compute the validity predicate, consisting of checking that 1 the public key of the targeted account is correct, 2 the ethereum blog dao is correct, and 3 the account has enough funds to send. Note that all of these can be parallelized.

This is once again trivial using boolean logic gates, but even if ethereum blog dao use a finite field for efficiency ethereum blog dao do exist some clever tricks for performing the check using nothing but additions and multiplications. In all of the ethereum blog dao we saw two fundamental limitations in efficiency in the SMPC architecture.

First, reading and writing to a database has an O n cost as you pretty much have to read and write every cell. Doing anything less would mean exposing to individual nodes which subset of the database a read or write was from, opening up the possibility of statistical memory ethereum blog dao. Second, every multiplication requires a network message, so the fundamental bottleneck here is not computation or memory but latency. Because of this, we can already see that secret sharing networks are unfortunately not God protocols; they can do business logic just ethereum blog dao, but they will never be able to do anything more complicated — even crypto verifications, with the ethereum blog dao of a select few crypto verifications specifically tailored to the platform, are in many cases too expensive.

Now, the ethereum blog dao problem is, how do we go from this simple toy currency to a generic EVM processor? Well, let us examine the code for the virtual machine inside a single transaction environment.

A simplified version of the function looks roughly as follows:. Hence, we can simply store these as records, and for every computational step run a function similar to the following:. Essentially, we compute the result of every single opcode in parallel, and then pick the correct one to update the ethereum blog dao. The alive variable starts off at 1, and if the alive variable at any point switches to zero, then all operations from that point simply do nothing. This seems horrendously inefficient, and it is, but remember: Everything above can be parallelized.

In fact, the astute reader may even notice that the entire process of running every opcode in parallel has only O n complexity in the number of opcodes particularly if you pre-grab the top few items of the stack into specified variables for input as well as output, which we did not do for brevityso it is not even the most computationally intensive part if there are more accounts or storage slots than opcodes, which seems likely, the database updates are.

In an EVM with many participants, the database will likely be the largest overhead. To mitigate this problem, there are likely ethereum blog dao information leakage tradeoffs that can be made. Ethereum blog dao example, we already know that most of the time code is read from sequential database indices. Hence, one approach might be ethereum blog dao store the code as a sequence of large numbers, each large number encoding many opcodes, and then use bit decomposition protocols to read off individual opcodes from a number once we load it.

There are also likely many ways to make the virtual machine fundamentally much more efficient; the above is meant, once again, as a proof of concept to show how a secret sharing DAO is fundamentally possible, not anything close to an optimal implementation. Additionally, we can look into architectures similar to the ones used in scalability 2.

However, blockchain protocols need to theoretically last forever, and so stagnant economic sets do not work; rather, we need to select the consensus participants using some mechanism ethereum blog dao proof of stake. To do this, an example protocol would work as follows:. All of the above handles decentralization assuming honest participants; but in a cryptocurrency protocol we also need incentives.

To accomplish that, we use a set of primitives called verifiable secret sharingthat allow us to determine whether a given node was acting honestly throughout the secret sharing process.

Essentially, this process works by doing the secret sharing math in parallel on two different ethereum blog dao Elliptic curve points are convenient because they have a commutative and associative addition operator - in essence, they are magic objects which can be added and subtracted much like numbers can.

By doing the secret sharing math on the number level and the elliptic curve point level at the same time, and publicizing the elliptic curve points, it becomes possible to verify malfeasance. For efficiency, we can probably use a Schellingcoin-style protocol to allow nodes to punish other nodes that are malfeasant. So, what do we have?

If the blockchain is a decentralized computer, a secret sharing DAO is a decentralized computer with privacy. The secret sharing DAO pays dearly for this extra property:

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Announcing World Trade Francs: The Official Ethereum Stablecoin 01st April, Ethereum scalability research and development subsidy programs 02nd January, One of the common questions that many in the crypto 2. What fundamental advantage would an organization have from its management and operations being tied down to hard code on a public blockchain, that could not be had by going the more traditional route? What advantages do blockchain contracts offer over plain old shareholder agreements?

Particularly, even if public-good rationales in favor of transparent governance, and guarnateed-not-to-be-evil governance, can be raised, what is the incentive for an individual organization to voluntarily weaken itself by opening up its innermost source code, where its competitors can see every single action that it takes or even plans to take while themselves operating behind closed doors?

There are many paths that one could take to answering this question. For the specific case of non-profit organizations that are already explicitly dedicating themselves to charitable causes, one can rightfully say that the lack of individual incentive; they are already dedicating themselves to improving the world for little or no monetary gain to themselves.

For private companies, one can make the information-theoretic argument that a governance algorithm will work better if, all else being equal, everyone can participate and introduce their own information and intelligence into the calculation — a rather reasonable hypothesis given the established result from machine learning that much larger performance gains can be made by increasing the data size than by tweaking the algorithm.

In this article, however, we will take a different and more specific route. However, substance S can only be produced by working with [a strange AI from another dimension whose only goal is to maximize the quantity of paperclips] — substance S can also be used to produce paperclips.

We have never interacted with the paperclip maximizer before, and will never interact with it again. Both humanity and the paperclip maximizer will get a single chance to seize some additional part of substance S for themselves, just before the dimensional nexus collapses; but the seizure process destroys some of substance S.

From our point of view, it obviously makes sense from a practical, and in this case moral, standpoint that we should defect; there is no way that a paperclip in another universe can be worth a billion lives. However, the outcome that this leads to is clearly worse for both parties than if the humans and AI both cooperated — but then, if the AI was going to cooperate, we could save even more lives by defecting ourselves, and likewise for the AI if we were to cooperate.

When there is no ability to pre-contract, laws penalize unilateral defection. However, there are still many situations, particularly when many parties are involved, where opportunities for defection exist:.

Of course, in many of these cases, people sometimes act morally and cooperate, even though it reduces their personal situation. But why do they do this?

We were produced by evolution, which is generally a rather selfish optimizer. There are many explanations. One, and the one we will focus on, involves the concept of superrationality.

Consider the following explanation of virtue, courtesy of David Friedman:. Essentially, it is cognitively hard to convincingly fake being virtuous while being greedy whenever you can get away with it, and so it makes more sense for you to actually be virtuous. Much ancient philosophy follows similar reasoning, seeing virtue as a cultivated habit; David Friedman simply did us the customary service of an economist and converted the intuition into more easily analyzable formalisms.

Now, let us compress this formalism even further. In short, the key point here is that humans are leaky agents — with every second of our action, we essentially indirectly expose parts of our source code.

If we are actually planning to be nice, we act one way, and if we are only pretending to be nice while actually intending to strike as soon as our friends are vulnerable, we act differently, and others can often notice. This might seem like a disadvantage; however, it allows a kind of cooperation that was not possible with the simple game-theoretic agents described above. In this case, the agents can adopt the following strategy, which we assume to be a virtuous strategy:.

If two virtuous agents come into contact with each other, both will cooperate, and get a larger reward. If a virtuous agent comes into contact with a non-virtuous agent, the virtuous agent will defect.

Hence, in all cases, the virtuous agent does at least as well as the non-virtuous agent, and often better. This is the essence of superrationality.

Of course, there is a class of individuals who can convincingly pretend to be friendly while actually planning to defect at every moment — these are called sociopaths , and they are perhaps the primary defect of this system when implemented by humans. This kind of superrational cooperation has been arguably an important bedrock of human cooperation for the last ten thousand years, allowing people to be honest to each other even in those cases where simple market incentives might instead drive defection.

Most people in modern civilization have benefited quite handsomely, and have also indirectly financed, at least some instance of someone in some third world country dumping toxic waste into a river to build products more cheaply for them; however, we do not even realize that we are indirectly participating in such defection; corporations do the dirty work for us. The market is so powerful that it can arbitrage even our own morality, placing the most dirty and unsavory tasks in the hands of those individuals who are willing to absorb their conscience at lowest cost and effectively hiding it from everyone else.

The corporations themselves are perfectly able to have a smiley face produced as their public image by their marketing departments, leaving it to a completely different department to sweet-talk potential customers. This second department may not even know that the department producing the product is any less virtuous and sweet than they are. The internet has often been hailed as a solution to many of these organizational and political problems, and indeed it does do a great job of reducing information asymmetries and offering transparency.

However, as far as the decreasing viability of superrational cooperation goes, it can also sometimes make things even worse. This is part of the reason why scams online and in the cryptocurrency space are more common than offline, and is perhaps one of the primary arguments against moving all economic interaction to the internet a la cryptoanarchism the other argument being that cryptoanarchism removes the ability to inflict unboundedly large punishments, weakening the strength of a large class of economic mechanisms.

A much greater degree of transparency, arguably, offers a solution. Individuals are moderately leaky, current centralized organizations are less leaky, but organizations where randomly information is constantly being released to the world left, right and center are even more leaky than individuals are. This is essentially a restatement of the founding ideology behind Wikileaks, and more recently an incentivized Wikileaks alternative, slur. However, Wikileaks exists, and yet shadowy centralized organizations also continue to still exist and are in many cases still quite shadowy.

Decentralized autonomous organizations, as a concept, are unique in that their governance algorithms are not just leaky, but actually completely public. A futarchy maximizing the average human lifespan will act very differently from a futarchy maximizing the production of paperclips, even if the exact same people are running it.

Now, what would superrational cooperation using DAOs look like? First, we would need to see some DAOs actually appear. There are a few use-cases where it seems not too far-fetched to expect them to succeed: They cannot ever do anything but perhaps adjust a few of their own parameters to maximize some utility metric via PID controllers , simulated annealing or other simple optimization algorithms.

Hence, they are in a weak sense superrational, but they are also rather limited and stupid, and so they will often rely on being upgraded by an external process which is not superrational at all. DAOs with a governance algorithm capable of making theoretically arbitrary decisions. Futarchy , various forms of democracy, and various forms of subjective extra-protocol governance ie.

Once DAOs can make arbitrary decisions, then they will be able to not only engage in superrational commerce with their human customers, but also potentially with each other. What kinds of market failures can superrational cooperation solve that plain old regular cooperation cannot? Public goods problems may unfortunately be outside the scope; none of the mechanisms described here solve the massively-multiparty incentivization problem.

With public goods, the whole problem is that there is no way to exclude anyone from benefiting, so the strategy fails. However, anything related to information asymmetries falls squarely within the scope, and this scope is large indeed; as society becomes more and more complex, cheating will in many ways become progressively easier and easier to do and harder to police or even understand; the modern financial system is just one example.

Perhaps the true promise of DAOs, if there is any promise at all, is precisely to help with this. Try to determine if the other party is virtuous. If the other party is virtuous, cooperate. If the other party is not virtuous, defect. This brought it back. To prevent this would require the repayment code to have control over any possible expenditure, at which point we hit the Halting Problem and simple practicality almost instantly.

Seems a better line than attempting to be rid of Government all together. We think of transparency as always being good but if that was the case why was there a need to institute the secret ballot? So transparency is good in the sense of accountability but it also makes the transparent subject vulnerable to bribes and to intimidation.

Seems like the ideal solution is to be transparent in the execution of policy and to be secret in the process in which policy is created. The smoke-filled back room of secrecy is something people hate but people also hate the fact that lobbyists wield a lot of power relative to the money they spend to influence elections.

If you want people to vote their conscience free from intimidation and from bribes you need to shield them from the retribution which might result if they choose to vote contrary to the interests of those who have money or power. In this way they actually desire something that is contrary to their best interest. So I think this article would be really helpful if it could differentiate between policy creation and policy execution.

For the latter transparency is highly desired and for the former transparency can result those citizens with the most money and most power to lobby aka bribe and intimidate deciding how policy is created.

There is some interesting academic work on some of theses issues and I apologize for not giving here citations to some of them.. Hence the big difference in behavior. Space faring people Astronauts, Cosmonauts etc. Second, many claim that human decision making is irrational by definition. The decision itself is being made first, and the rational applied later to explain and support it.

DAOs are definitely the future, for countless reasons. We already created airplanes, cell phones and genetically modified chickens, so how hard can that be?! I wonder if you could continue the conversation on email? I think Superrationality as you said is matter of scale and this is must interesting parameter in human development when we are thinking about globalization.

Now this is my next question, how reduce the nefast effect of globalization for instance to protect our planet of ecological disaster? Is human alone is able of super Superrationality at a large scale or he needs to have a DAO to keep track of this progress? Full transparency is the only option! Privacy Is The Enemy. Is there anything more out there on this? I noticed you linked to all the other stuff. Thanks in advance — James. Few things I missunderstand: You may use these HTML tags and attributes: Superrationality and DAOs Introduction.

The Official Ethereum Stablecoin 01st April, Ethereum scalability research and development subsidy programs 02nd January, The payoff matrix is as follows: Humans cooperate Humans defect AI cooperates 2 billion lives saved, 2 paperclips gained 3 billion lives, 0 paperclips AI defects 0 lives, 3 paperclips 1 billion lives, 1 paperclip.

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