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In Blockchain we trust
An interesting article has appeared in TNW where Rohit Mamoria explains why blockchains help strangers trust each other online:
The very act of getting something recorded by thousands of strangers provides the trust. The statements are locked using math in such a manner that no one can ever modify it.
The author then proposes that this trust-building capability of blockchains can facilitate a new type of communities:
Blockchain shows early but promising signs of powering an entirely new kind of organizations called Decentralized Autonomous Organization …It means the organization without hierarchy, not even implied, will be possible. The enterprise will only be responsible to define the constitution of the community and put it in the code
The important decisions in the community is not taken by the top of the pyramid (remember, there’s no pyramid like hierarchy) but by everyone. Every proposal gets submitted in the form of a Smart Contract on which everyone can vote. If the threshold defined in the constitution is met, the proposal gets activated for the community.
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Even the contracts to unanimously assign certain responsibilities to an individual is possible. The members vote in to assign a role to an individual but if the person doesn’t fulfill his/her job well (or behave like a total jerk), the votes can be withdrawn, making the role taken away.
Is voting a valid use case for the blockchain?
The issue of whether distributed ledger technologies (DLTs) can contribute to how people vote – how they cast their votes, how they count them, or even, how they make them count – is not a new one. Nasdaq was one of the most decisive movers in this sphere, introducing a PoC of blockchain-backed e-voting within the scope of their shareholder governance structures, with a view to digitise Annual General Meetings through the use of DLTs.
With different blockchains offering new and exciting consensus mechanisms, such as those modelled closely after the concept of representative (parliamentary) democracy, we see an increase of reasonably high-stake PoCs realising different, often very creative approaches to voting. The Estonia e-voting pilot is one such example where the DLT is used in a rather traditional way to record the ownership of securities, then based on those assets, “voting rights assets” and “voting token assets” are issued for each holder. A participant may “spend” their “voting token asset” to cast their vote if they also “own” the “voting right asset”. This was a seminal model that successfully demonstrated a successful use of DLTs in a non-settlement context.
To keep things in perspective, voting should not be understood narrowly as the technical process or a procedure that serves some abstract bureaucracy flourish. Quite on the contrary, voting, in its wide meaning, is how we make decisions and express ourselves in large groups – it is how organisations, businesses and nations define themselves and their very futures. Considering the impact of smart contracts, we can expect these early approaches to voting to become more refined and user-friendly in the nearest future, so as to serve their stakeholders better. Some interesting apps to look out for include http://democracy.earth and MiVote. In fact, the developer of MiVote ponders on whether our democracy could become fairer if we thought about it as a product that needs to be managed?
If that is indeed the right way to look at it, then the “e-voting” feature for the “democracy” package should really be shipped in the next big update. And DLTs could make that big update shippable much sooner that it was technically possible before their advent.
Criteria for classifying blockchains
The following is supposed to be a starting point for listing criteria that can be helpful in classifying blockchains, so as to understand which blockchain features can be beneficial towards which use cases.
Permissioning (public, private, hybrid)
Private block chains like Corda are increasingly gaining ground. This phenomenon may seem counterintuitive, as the main motivation behind the original blockchain was public, distributed and verifiable data. At the same time, PwC predict that by the 2020s, many enterprises outside banking and financial services may well have adopted private blockchains for various digital business flows.
Asset modelling (fungible, non-fungible, hybrid)
See my previous post about this topic
Smart contracts (Turing completeness vs oracles)
With Ethereum’s smart contracts being a massive improvement over Bitcoin’s primitive scripts, empowering anyone to run any stateless code on the block chain (for a fee), we have now seen new startups like Legalese promising that real-life contracts can be compiled and executed on distributed ledgers.
Consensus mechanism (pluggable, non-pluggable)
Building consensus is a way for diverse groups to make decisions without conflict.
The mechanisms here are quite diverse and include Proof of Work (PoW), Proof of Stake (PoS), delegated Proof of Stake (think parliamentary democracy) as used by BitShares, Paxos / Raft algorithms, PBFT (The difference between PBFT and Paxos is motivated by having to tolerate Byzantine (arbitrary) failures), N2N, multi-level consensus algorithm as used by BigChainDB
Block size
Blocktimes / throughput
Energy usage
With the proof-of-work mining mechanism being extremely energy intensive, there is a great need towards greener block chains, which conserve energy usage.
Extensibility ( channels )
Federation (sidechains)
See for example: Strong Federations: An Interoperable Blockchain Solution to … – arXiv
How is transaction finality handled (Casper, proof-of-work)
How “liquid” is it (can assets be moved into and out of the chain)
How are signatures managed
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Especially for democracy use cases, we will also need to measure usability and user experience (so as to improve accessibility and remove social barriers to participation) and the next couple of posts will focus on these areas.
Also look at this fantastic cheat-sheet from Bits On Blocks :
Fungibility on the blockchain
Fungibility is the idea that an orange can just be an orange (in a platonic way) and not “this specific orange”. If it becomes distinguishable, eg. because of its provenance or history, it is no longer fungible.
There seems to be much disagreement on whether fungibility lies on a spectrum or if it’s purely binary. Objectively, universal fungibility is never possible, because there can never exist two items that are exactly the same in the physical sense. Hence, only relational fungibility is possible, subject to a particular use in a specific context. It also does seem to lie on a spectrum. For instance, we can talk about physical currency being fungible. Yet, every single fiver note has a serial number on it. Some notes are in better shape than others. Some are discoloured. Yet we all agree that a fiver can be exchanged with another fiver. Physical cash seems to be “fungible enough” for everyday purposes.
Some blockchain platforms— such as BigChainDB — model assets as non-fungible objects. That comes in very handy for tracking the supply chain of the asset that’s being represented. Everledger is a network for tracking physical diamonds using BigChainDB. Everledger’s early successes include exposing blood diamonds and highlighting a huge amount of fraud happening along the supply chain.
However, this fungibility, regardless of its benefits, comes at a cost of overhead and would be detrimental in modelling certain high-frequency use cases like tracking the value of certain stock markets. One can imagine that in those scenarios, assets would be better represented as simple balances that can be updated on the ledger. This is exactly why some platforms, for example chain.com, model assets as fungible objects, allowing them to scale . We can call those type of assets “tokens” or “dematerialised assets”.
Yet another form of blockchain (such as Hyperledger Fabric) would be those platforms that are capable of running smart contracts that, together with their resulting outputs, are persisted to a blockchain. The purpose of smart contracts is that custom logic can be run and validated by multiple nodes at the same time, possibly affecting fungibility. One could also make a case for one more form of blockchain — such as Ethereum — that not only models the assets but also allows for manipulation of their storage state by smart contracts. On an even more selective distributed ledger such as R3’s Corda, only the parties relevant to the smart contract run the code, and create consensus on the results of the code between those who are affected.
Transparency Without Accountability
Jennifer Shkabatur’s particularly insightful article in Yale Law & Policy Review argues that existing transparency policies do not actually strengthen public accountability. The current technology set-up reinforces the traditional pitfalls of transparency policies, allowing agencies to retain control over which data they choose to publish, whilst also prioritising quantity over quality of disclosures. Moreover, a “data divide”emerges in favour of established organisations and those individuals who possess programming and/or data science skills.
As a result, the supply of the data published on governmental websites does not necessarily meet public demand. It is not clear who is served by the voluminous information available on agencies’ websites, let alone how this information can improve public accountability.
The author proposes that a closer look should be given to the role of technology in the administrative state and its capacity to alter existing institutional structures. Accordingly, Shkabatur suggests that the content of online transparency policies (not just their rhetoric) should focus on accountability. Agencies should be pressed to release structured information on their decision making processes and on their performance. Moreover, this transparency regime should be complemented by effective enforcement measures—a basic element that is surprisingly missing. Civil society and nongovernmental users should be awarded more influence on how these policies are structured. To that end, it is suggested that more focus should be placed on accessibility and removing usability barriers. The current reliance on raw datasets that require professional processing and programming skills should therefore be reconsidered.
What should Openness look like?
“The liberties of a people never were, nor ever will be, secure, when the transactions of their rulers may be concealed from them.”
Patrick Henry
In their 2012 paper , Princeton researchers Harlan Yu and David G. Robinson concluded that even the most draconian governments can call themselves “open“, as long as they embrace some recent technology to disclose even a minuscule amount of official data. “Openness” as such is difficult to quantify. It follows that “open government data” could refer to data that makes the regime substantially more accountable to the public, but might equally well refer to politically neutral disclosures that ignore, or even obscure, core decisions-making processes and their outcomes.
The implementation of “openness” is thus increasingly being steered by trigger-happy technologists who advocate “going digital” as the ultimate government roadmap. In the UK, it was David Cameron’s government who hijacked the openness agenda to support the politics of austerity (the government advocated that citizens “join in” the hunt for the savings, as if they could redeem themselves that way).
In his excellent critique of this approach, Jonathan Gray proposes that what matters is not openness per se, but:
how this openness is used to improve the lives of citizens by reducing inequality and poverty, tackling corruption and injustice, increasing access to education and healthcare, mitigating the effects of climate change, and so on.
Open government talks would benefit from being less procedural and more substantive, highlighting issues rather than instruments, values rather than processes, and engaging more fully with citizens and campaigners – who usually have little say in forming open government policy – about the transparency and accountability challenges they face.
Openness vs. Transparency
“The very word ‘secrecy’ is repugnant in a free and open society”
John Fitzgerald Kennedy
Secrecy
Transparent and accountable decision-making is the essence of democracy. Secrecy is its enemy and produces distrust and disengagement among citizens.
The terms “openness” and “transparency” stand in stark contrast to secrecy and may both seem interchangeable as they’re frequently used in the same context. There are, however, some key differences in these terms.
Transparency
“Transparency” is used to mean that the decision-making process is transparent – that it should be clear who makes decisions, when, where, and arguably – why. As you can imagine, this requires the mechanisms by which decisions are being made to be well-defined and arguably – well-understood. Each such decision-making mechanism needs to have an accessible audit trail for it to be deemed “transparent”.
Openness
On the other hand, “openness” is used in EU contexts to describe the citizen’s right to access documents. An “open” government is one that provides “open” data sets and audit trails, i.e. facilities in place to easily access and retrieve the information that is of interest to the citizens.
“Openness” may sometimes have an even broader meaning of allowing the citizens to freely interact with the mechanisms described above, by having read-write access rather than just read-only access. This is because where a citizen sees a problem (because they’ve been offered “open” access to a “transparent” mechanism), they should also be afforded an opportunity to rectify this problem – which requires their own input to be heard and ultimately processed.