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Little piggy banking system
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Furthur develop idea of knowledge block-chain system #3

Open sjinko opened 2 years ago

sjinko commented 2 years ago

Annotation of Nakamoto, Satoshi, 2008. “Bitcoin: A Peer-to-Peer Electronic Cash System”. White paper published on October 31: https://bitcoin.org/bitcoin.pdf.

We propose a solution to the double-spending problem using a peer-to-peer network. The network timestamps transactions by hashing them into an ongoing chain of hash-based proof-of-work, forming a record that cannot be changed without redoing the proof-of-work. The longest chain not only serves as proof of the sequence of events witnessed, but proof that it came from the largest pool of CPU power. As long as a majority of CPU power is controlled by nodes that are not cooperating to attack the network, they’ll generate the longest chain and outpace attackers.

The core issue mentioned by Nakamoto is thus the double-spending problem. The principl of “proof-of-work” is the solution proposed. The idea that the largest pool of CPU power controls the mining of the chain is already projected. Finally, Nakamoto warns on the risk that cooperation between nodes can lead to an attack of the system.

To some extend, Nakamoto proposes a model that requires adversity between groups of nodes that form the pools of CPU power, since cooperation can lead to an attack on the system. The system, which requires nodes to compete rather than cooperates leads to the need to increase the difficulty of the proof-of-work, and thus CPU power, coalitions of nodes into pools and energy consumption. As noted on Wikipedia, “In 2014 mining pool Ghash.io [Headquartered in the Neatherlands] obtained 51% hashing power which raised significant controversies about the safety of the network. The pool as voluntarly capped their hashing power at 39.99% and requested other pools to act responsibly for the benefit of the whole network."

While the system [of financial instituions serving as trusted third parties to process electronic payments] work well enough for most transactions, it still suffers from the inherent weakness of the trust based model. Completely non-reversible transactions are not really possible, since financial institutions cannot avoid mediating disputes. The cost of mediation increases transaction costs, limiting the minimum practical transaction size and cutting off the possibility for small casual transactions, and there is a broader cost in the loss of ability to make non-reversible payments for non-reversible services. These costs and payment uncertainties can be avoided in person by using physical currency, but no mechanism exists to make payments over a communication channel without a trusted party.

What is needed is an electronic payment system based on cryptographic proog instead of trust, allowing any two willing parties to transact directly with each other without the need for a trusted third party.

This situation resembles the one of research publication in which the institution or editor acts as a trusted third party. The main difference being that currency makes financial capital, unlike knowledge, agnostic. Value of the financial capital is fixed by its purchasing power of the currency. Knowledge, on the other hand, is non-transactional because it does not hold a single currency. Using a blockchain-like system, we could develop a currency of knowledge acquisition and production. NFTs could also be used to claim knowledge stewardship. The system should however be designed so to not exclude inviduals based on their display of capacities. For example, digital literacy should be be a discriminatory factor, the same way it might be in other block-chain systems. Likewise, various forms of knowledge and know-how, and not just ”Western scientific knowledge” should exist within the system.

We define an electronic coin as a chain of digital signatures. Each owner transfers the coin to the next by digitally signing a hash of the previous transaction and the public key of the next owner and adding these to the end of the coin. A payee can verify the signatures to verify the chain of ownership.

The same principle could be applied to knowledge transmission. Each transmission would be 'signed' by the transmitter. Knowledge, in this case, would behave the same way that a good would, with the risk that its value lowers with decay or increase due to higher demand. Yet, because knowledge is non-material, its sharing does not negatively impact the transmitter, who maintains their possession of the knowledge. It is however affected by decay or inconsistency, and requires encoding and recording onto material supports such as written notes.

only coins issued directly from the mint are trusted not to be double-spent. The problem with this solution is that the fate of the entire system depends on the company running the mint, with every transaction having to go through them, just like a bank [and the centralization of power and capital in this third party].

Here again, we could see a paralelle with the scientific publication industry which requires trust in the publisher to avoid “double-publication” (or previous publication of the same knowledge). Ironically, this task is then delegated to “trusted” reviewers who take the responsability with nothing but a very small compensation in status capital.

The only way to confirm the absence of a transaction is to be aware of all transactions. [...] To accomplish this without a trusted party, transactions msut be publicly announced, and we need a system for participants to agree on a single history of the order in which they were received.

The systems, which Nakamoto proposes, resembles again the one of academic publication which should guarantee the order in which knowledge is produced. But because knowledge is shared and not owned, it is difficult to think of a system that would truely produce a single history of that order.

The solution we propose begins with a timestamp server. [...] Each timestamp includes the previous timestamp in its hash, forming a chain, with each additional timestamp reinforcing the ones before it.

The proof-of-work also solves the problem of determining representation in majority decision making. [...] Proof-of-work is essentially one-CPU-one-vote. [...] If the majority CPU power in controlled by honest nodes, the honest chain will grow the fastest and outpace any competing chains.

The steady addition of a constant of amout of new coins is analogous to gold miners expending resources to add gold to circulation. In our case, it is CPU time and electricity that is expended.

The consumption of electricity and the need for more and more CPU power was indeed foreseen.

To facilitate this without breaking the block’s hash, transactions are hashed in a Merkle Tree, with only the root included in the block’s hash. Old blocks can then be compacted by stubbing off branches of the tree. The interior hashes do not need to be stored.

As such, the verification is reliable as long as honest nodes control the network, but is more vulnerable is the network is overpowered by an attacker. While network nodes can verify transactions for themselves, the simplified method can be fooled by an attacker’s fabricated transactions for as long as the attacker can continue to overpower the network.

To this, Nakamoto provides a “solution” by having notes create an alert when they detect an invalid block. Another strategy could be to limit the capacity for pools to hash two blocks in a row. This “latency” could also secure a more fair distribution of proof-of-work to a variety of pools.

Privacy can still be maintained by breaking the flow of information in another place: by keeping public keys anonymous. The public can see that someone is sending an amount to someone else, but without information linking the transaction to anyone.

The setup of privacy in Bitcoin is a concern for allowing illegal financial transactions to take place. To solve this issue, we could imagine a system in which identities of parties is not anonymous, but in which the amount of the trasaction is unknown. This, obviously, would limit the attractivity of the digital currency, since it‘s potential use in illegal financial transactions partially explains its popularity.

Originally posted by @sjinko in https://github.com/sjinko/purcel/issues/2#issuecomment-981151260

sjinko commented 2 years ago

The systems, which Nakamoto proposes, resembles again the one of academic publication which should guarantee the order in which knowledge is produced. But because knowledge is shared and not owned, it is difficult to think of a system that would truely produce a single history of that order. (@sjinko in #2 comment)

At the same time, what the blockchain does is to create a “single history” out of millions of transactions, each having their own histories. It is not necessary for the blockchain to create common sense or shared meaning out of the transactions, but simply to record each “voices”.

sjinko commented 2 years ago

The core issue mentioned by Nakamoto is thus the double-spending problem. The principle of “proof-of-work” is the solution proposed. The idea that the largest pool of CPU power controls the mining of the chain is already projected. Finally, Nakamoto warns on the risk that cooperation between nodes can lead to an attack of the system. (@sjinko in #2 comment)

Could we think of a system in which scientific research and essays would constitute the “proof-of-work" of a intellectual currency? By completing the “proof-of-work”, contributors to the system would then get some amount of the currency, while allowing for its’ transactions. Among others, there is one conceptual difference between the Bitcoin’s blockchain model and this intellectual currency, which needs to be addressed.

In the Bitcoin, all pools work towards solving the same problem, which is preset, while in research and other knowledge production activities, teams and individuals do not necessarily work towards the same problem. In fact, research requires to create problems before solving them. Could the “proof-of-work” consist in creating knowledge problems, rather than solving them?

This thus raise the following questions of what would be the proof-of-work in the knowledge blockchain, and what would be the currency, who would constitute the pools, and how could translate the CPU into a knowledge blockchain?

In Nakamoto’s model, the largest pool of CPU controls the mining of the chain. Would the equivalent be that the largest pool of people working together to control the mining of knowledge? What would be the implication of such a system (which in fact resembles pretty much how knowledge is already being produced), and more specifically, what would we account for principles of equity, diversity and inclusion in such “majoritarian” logic?

sjinko commented 2 years ago

Another conceptual difference between the application of the blockchain to Bitcoin and to the production of knowledge stems from the problem Nakamoto is trying to address. In their paper, Nakamoto states first-hand that the problem he is trying to solve with Bitcoin is twofold. At the core of the problem stands the issue of double-spending. Because double-spending poses a threat to the digital transactional economy, Nakamoto argues that we delegate responsibility of blocking this possibility to financial institutions, so-called third parties. For Nakamoto, the blockchain principle behind Bitcoin is a substitute to the third-party solution by allowing two-party transactions without the need for a third party.

In fact, there is a third party involved even in Bitcoin transaction, the community of miners. Pools of miners act as a third party by providing the proof-of-work required by the system's architecture to validate the transaction. The main difference is that the implication of the third party does not revolve around trust (which it actually does like we see in the 51%+ limitations of the pooling system), but mostly around computational limitations. What secures the system is our "trust" in that the proof-of-work is, as its name indicates, a difficult task to accomplish, and a task that can be accomplished by several antagonist actors, the mining pools. In addition, our trust in that one actor does not have the necessary computational power, is asked necessary for the system to function.

This displacement of trust, from state-approved institutions that are the banks, to a common knowledge-based trust, could be seen as a positive thing-in-itself. It does not mean, however, that the system cannot be cheated, and our trust deceived, but that the ontology of trust has changed, making it stronger in certain regards and weaker in others.

sjinko commented 2 years ago

To conceive a blockchain of knowledge, we need to think of who are the actors and what are the components of the system.

In the Bitcoin, actors are:

The components are:

Correspondingly, in the blockchain of knowledge, the actors would be:

For the Bitcoin, additional miners joined the system by providing CPU power to pools. These CPU efforts, which are now designed specifically for this activity, were first redirected from other computation tasks or simply put to use when in latency periods.

For researchers, each publication could provide proof-of-work, but how could the entire system validate this work, just like the solving of the problem in blockchain?

sjinko commented 2 years ago

Scientific publication ontology

General Fin. Xchnge Bitcoin Sci Pub.
Trusters Traders Invest. Researchers
Trustee Banks Pools Editors
Capital Elec. money Bitcoin Knowledge

In this model, I am not sure that the capital is for scientific publications is knowledge or authorship. In the financial system, trust serves to preserve the value of capital.

In scientific publication, there is two levels of trust. Trust of the quality of the research, guaranteed by peer-reviewing, and trust of authorship, guaranteed by publications. For the latter, systems such as DOI can replace editors, but the community is still reliant on trust towards international organization such as DOI.org. A third level of trust provided by editors and libraries guarantees that the knowledge that is published by academic shall not be lost.

In summary, academics need trust in the content, in the authorship and in the archiving of scientific knowledge.