Re-architecting Trust Models
and the implications on ecosystem building
Blockchain technology is often conflated with enabling trustlessness. Popular opinion pieces, such as that of Goldman Sach’s primer on blockchain technology, titled “Blockchain - The New Technology of Trust”, is an example in how trustlessness can be conflated with blockchain technology as a trust enabler:
Goldman’s paper goes on to state, “A blockchain needs to do two things: gather and order data into blocks, and then chain them together securely using cryptography. .. Because blockchains establish trust, they provide a simple, paperless way to establish ownership of money, information and objects. .. Blockchain could be a revolution in the way everyone—businesses, governments, organizations and individuals—work together. It provides a simple, secure way to establish trust for virtually any kind of transaction, helping simplify the movement of money, products or sensitive information worldwide.”
However, the statement that “blockchains establish trust” is not entirely accurate. Software engineer Jill Burrows writes:
“Generating trust from nothing is one of the first major feats blockchain is hyped to do, but blockchain itself doesn’t generate trust out of nothing. It actually derives from the system in which blockchain is used. A blockchain is actually just a chain of blocks of data having a particular structure which ensures its self-integrity, it can only be used to guarantee the data written to the chain was done so in a certain way. Multiple blockchains can be created with the same data up to a certain point — in fact, Bitcoin does this all the time in the mining process and the fork stays around until a majority of nodes choose the fork which grows longest. …
It is important to note this scheme only creates trust in the distributed ledger and the authenticity of each token on the network. It doesn’t keep track of bad misbehaving nodes, it simply discards any attempts to write to the ledger from misbehaving nodes. .. It has nothing to say about the identity or trustworthiness of any actor on the network outside of the veracity of each token and transaction in the ledger.
What then, should the right terminology be? American computer scientist and cryptographer Nick Szabo defines blockchain technology as “trust minimized, not trustless”. This is a small but important distinction in defining how trust models are architected with blockchain technology:
In his August 2020 blog post on trust models, Vitalik shares a similar opinion and offers a definition for trust:
“Blockchain applications are never fully trustless, but some applications are much closer to being trustless than others. If we want to make practical moves toward trust minimization, we want to have the ability to compare different degrees of trust.
First, my simple one-sentence definition of trust: trust is the use of any assumptions about the behavior of other people.”
On the role of founding blockchain designers in trust minimization, Nick Szabo makes the following assumption of ceding control:
Blockchain has enabled a new trust model for verification or trust minimization to be architected. Wharton Professor Kevin Werbach outlines four different trust architectures in his book titled Blockchain and The New Architecture of Trust, and the evolution of the distributed trust model with blockchain technology:
Peer-to-peer trust, i.e. a gentleman’s agreement
Leviathan trust, which is institutional and involves contracts
Intermediary trust, like PayPal or credit cards that make a transaction work
Distributed trust, i.e. smart contracts, which execute in an expected way without needing to rely on a specific actor
On this distributed trust model, American cryptographer Bruce Schneier writes:
What blockchain does is shift some of the trust in people and institutions to trust in technology. You need to trust the cryptography, the protocols, the software, the computers and the network. In the context of public blockchains, the three elements that make public blockchains work are:
The ledger, which is the record of what happened and in what order
The consensus algorithm, which ensures all copies of the ledger are the same
The token, which is the currency
All the pieces fit together as a single system, and whether they can achieve anything gets back to the issue of trust. Most blockchain enthusiasts have a unnaturally narrow definition of trust. They’re fond of catchphrases like “in code we trust,” “in math we trust,” and “in crypto we trust.” This is trust as verification. But verification isn’t the same as trust. ..
In his trust models post, Vitalik breaks down trust into four dimensions in the context of blockchain protocols:
How many people do you need to behave as you expect?
Out of how many?
What kinds of motivations are needed for those people to behave? Do they need to be altruistic, or just profit seeking? Do they need to be uncoordinated?
How badly will the system fail if the assumptions are violated?
In addressing the matter that trust cannot be replaced with verification alone, as Schneier and Burrows mentioned above, the question then depends on the intent of the network participants. Alignment of incentives need to be in place to prevent bad actors and / or a tragedy of the commons issue. The Tezos whitepaper addresses this issue through a proof of stake mechanism alignment with system flexibility for smart contract usage, where by:
the miners are the stakeholders, and are thus interested in keeping the transaction costs low. .. [F]or the blockchain to be secure, all the active nodes need to validate the transaction. In practice though, most of the interesting smart contracts can be implemented with very simple business logic and do not need to perform complex calculations. Our solution is to cap the maximum number of steps that a program is allowed to run for in a single transaction. Since blocks have a size limit that caps the number of transactions per block, there is also a cap on the number of computation steps per block. This rate limitation foils CPU-usage DoS attacks. Meanwhile, legitimate users can issue multiple transactions to compute more steps than allowed in a single transaction, though at a limited rate. Miners may decide to exclude too long of an execution if they feel the included fee is too small. Since the Tezos protocol is amendable, the cap can be increased in future revisions and new cryptographic primitives included in the scripting language as the need develops.
Behavioral assumptions of participants in blockchain design are based on the self-sovereignty of nodes and network decentralization. This design embodies the real essence of blockchain protocols, which is a fundamental departure from founder control — and distributing control to the ecosystem. On ecosystem building, McKinsey Digital writes:
How do ecosystems work? For starters, they create value along two dimensions. They allow participants to consolidate a range of customers, often across sectors. Think of this as the horizontal vector. On the vertical vector, ecosystem participants strengthen or even dominate touch points along customer journeys (both B2C and B2B). Of course, ecosystem participants don’t try to do this by building everything they need in-house. Instead, ecosystem organizers provide incentives to and partner extensively with other participants, who may be within their traditional industry boundaries or outside of them. These moves can unleash distributed innovation and create new efficiencies along value chains to improve customer experiences while opening new avenues of value creation for a wide range of participants.
To participate successfully in ecosystems, [companies] may venture beyond in an effort to serve customers from one end of the customer journey to the other. For instance, opportunistic companies in the housing market—such as the United Kingdom’s ZPG—are trying to create end-to-end ecosystems that may span search, property comparisons, mortgage shopping, household moving, switching phone and cable companies, and access to home-improvement professionals. In fact, we estimate that at least a dozen sectors, including B2B services, mobility, travel and hospitality, health, and housing, are reinventing themselves as vast ecosystems, networks of networks that could add up to a $60 trillion integrated network economy by 2025.
All ecosystems grow and strengthen through continual interaction of all stakeholders. But all need an aligned vision around a shared body of open source knowledge for mainstream adoption. One key to the success of an ecosystem is for participants to demonstrate the ability to build collaborative relationships that extend beyond traditional industries, such as a startup developing new commercial applications that can be adapted into existing industrial value chains. Public blockchain communities have been building with a collaborative, ecosystem-first approach. This provides an engagement framework that enables open source technologies to achieve network effects at scale, relative to traditional industries undergoing digital disruption.