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This article is by Featured Blogger Richie Etwaru from his LinkedIn page. Republished with the author’s permission.
This is part one of a three-part series, I “hoping” to find the time to finish writing all three by end of October.
Trust as we have come to realize is one of the most important ingredients of commerce, I have to trust you to transact with you.
We as the collective human species start every transaction with a subliminal automatic assumption that the counter party cannot be trusted. And we should, because some members of our species are not completely trustworthy.
As a result of this subliminal automatic assumption we have built mechanisms to manufacture trust enabling the 7+ billion of us currently on the planet to transact over 100 trillion dollars with each other annually.
How do we do it? We use intermediaries, we use familiarity, and we use contracts.
Intermediaries have a purpose in our species thus far, but are they still needed? Banks are exemplary intermediaries for financial data, the department of motor vehicles are fantastic intermediaries for identity data, Yelp is a crappy intermediary for reputation data, Amazon is a commendable intermediary for inventory data, the New York stock exchange a decent intermediary for pricing and market data, the legal system is a somewhat function intermediary for agreement data, and the state a Delaware is a great intermediary for cooperate bylaws.
Intermediaries store, broker, and steward trust between those that are looking to trust others and those that are looking to be trusted. But are they still needed?
The time may have come in commerce, to change the model from one that is intermediary-dependent to one that is intermediary-free.
Much like we changed from kingdoms and servants to slavery, and from slavery to indentured servantship, and from indentures servantship to the model of commerce we are in today, commerce is about to change again.
This change in commerce, is being somewhat forced (there is little choice) by a small technological invention that uses asymmetric cryptography and distributed databases in a novel way to create a business network paradigm called blockchain.
Blockchains do three things, and they do these three things exceptionally well.
They manufacture trust in datasets (this will be the focus of post 1 of 3)
They engender consensus between parties familiar with said datasets (this will be the focus of post 2 of 3)
They facilitate autonomous markets on said datasets between unfamiliar parties (this will be the focus of post 3 of 3)
It is that simple, no biggie right?
LET’S TALK ABOUT TRUST
If we take any dataset that currently has or need an intermediary and put it on a blockchain, it will significantly lower the need for said intermediary. Here is why.
Non-blockchained data does not come with a fast and inexpensive way for virtually anyone to interrogate said data to know if it was tampered with, edited, or massaged. You can mess with, change significantly, or completely re-present non-blockchained data with reckless disregard because it is difficult for others to interrogate non-blockchained data to know what ill intended changes were made to a dataset.
See a simplified explanation of "chaining" here in my TEDx talk.
On the other hand, blockchained data has a construct where a combination of private and public keys via asymmetric cryptography are used to “chain” every new record in a dataset to every prior record that came before with an algorithm. This chaining of records creates a condition where if a single byte of a single record is change or reordered in a dataset on a blockchain, a derived algorithm can be used by virtually anyone to easily “test” the dataset to know if/when/where/how it was tampered with. And, in some cases, who did the tampering.
Essentially today non-blockchained data arrives at your doors and says, “I am data, you should trust me, trust me” – while tomorrow blockchained data will arrive at your doors and say, “I am data, here is the algorithm to easily test that I am trustworthy”.
For the first time in our history, we have a realistic opportunity to move from a species that lives with data that we cannot trust inherently and hence we depend on intermediaries – to – a species that lives with data that comes with an algorithm that enables virtually anyone to easily, quickly, and inexpensively test to verify that the data is trustworthy.
Think about any dataset in our businesses or lives today that requires verification by some third-party or an intermediary and imagine if that dataset can be blockchained – and re-imagine your business or life without that third-party verification or intermediary, and that’s a potentially decent blockchain use case.
I know you’re dubious, so was I. Think about datasets in our businesses or lives today that do not have third party verification or intermediaries, but desperately need them!
Now we are starting to get somewhere.
Remember we said blockchains do three things and do them very well.
They manufacture trust in datasets
They engender consensus between parties familiar with said datasets
They facilitate autonomous markets on said datasets between unfamiliar parties
Most of the conversation and evidence around blockchain this far has been on trusted financial data. After almost two years of research which culminated in the book Blockchain, Trust Companies I’ve devised a maturity model for how blockchain may evolve through commerce from Bitcoin to Trusted Commerce as we start to move past talking about financial data.
Bitcoin is to blockchains what AOL Chat was to the Internet.
On the y-axis is the list of the three things that blockchains do and do very well, and on the x-axis, are the data sets I believe will somewhat sequentially be blockchained.
Blockchain Maturity Model (Blockchain Trust Companies, page 168)
Bitcoin is in cell 1A above, and trusted commerce is around cell 7C. As you can see, I believe we are now getting started. Bitcoin is to blockchains what AOL Chat was to the Internet, just one instantiation of the protocol, an important instantiation but certainly not the most interesting instantiation that would come.
Bitcoin is just a trusted segment of all financial datasets.
Before we start to discuss uses cases of consensus and autonomy, let us start to think about what happens when we put datasets other than financial data and blockchain them.
1. Financial Data – already blockchained, how many more coins will we launch? Here we see banks as intermediaries that are somewhat effective, but expensive, and wildly inefficient and inconveniencing; and hence banks beginning to be unseated.
2. Identity Data – what happens to your business or lives when identity data does not require a third party to verify, or an intermediary such as the department of motor vehicles, or an embassy? Here we see intermediaries that are barely effective, highly flawed and filled with fraud, and massively in need of automation.
3. Reputation Data – we live in a world where the reputation of a business or a product is some combination of stars ranging from of one star to five stars often derived by ratings from identities that cannot be verified. What percentage of Yelp reviews are fake? Here we see intermediaries that are derived from a network or community, that lack integrity and fidelity yet massively depended on. As an aside, the reputation of a human being (FICO scores) has three intermediaries (three credit reporting agencies) and because they are often wrong, we take the average of the three in order to calculate human reputation.
4. Inventory Data – how do we know that limited-edition items that carry premium pricing are really limited? Or that vaccines that we are issued are not counterfeit even though they have unique serial numbers on them? Here we see little or no presence of an intermediary, creating conditions where we are often misled.
5. Market Data – here is a dataset where its currently too expensive to build the infrastructure for third party verification of pricing, and too cumbersome to have an intermediary to verify and surveil inappropriate manipulation of supply and demand.
6. Agreement Data – think about a legal agreement document that endured several rounds of negotiation and changes leading up to signatures; now what if at the time of a dispute a judge and jury can see the various rounds of negotiation of the document before signature. Here we see a gap in the journey to an agreement where intermediaries may be desperately needed.
7. Cooperate Data – I am going to spare you the pain … just notice that I am suggesting cooperate data as in the cooperate bylaws, not corporate data.
As you can see, just on the dimension of trust, blockchain may enable new datasets other than financial datasets (coins) to move from being data that arrives at your doors and says, “I am data, you should trust me, trust me” – to data arrives at your doors and says, “I am data, here is the algorithm to easily test that I am trustworthy”.
I will cover consensus in blog 2 of 3, and autonomous transactions in blog 3 of 3.
For now, I look forward for your comments as we start this discussion on social networks.