Seven months of intense activity have passed since the release of Blockchain 2018 Myth vs. Reality article. As a follow-up to that blog post, I would like to take the opportunity to analyse in further detail the impact that this new technology has on our perceptions of asset ownership and value, how we are continuously exploring new forms of transactional automation and then conclude with the challenge to deliver safe and fair governance.
Since the topic to cover is vast, I have decided to divide it into two separate blog posts, the first of which will cover how the meaning and perception of ownership is changing, while the second will discuss how Smart Contract automation can help deliver safe, fair, fast, low-cost, transparent and auditable transactional interoperability.
My intention is to provide an abstract and accessible summary that describes the state-of-the-art of blockchain technology and what motivations have led us to the current development stage. While these posts will not focus on future innovation, they will serve as a prelude to more bold publications I intend to release in the future.
Digital Asset Ownership, Provenance and Handling
How we value Digital vs. Physical Assets
In order to understand how the notion of ownership is currently perceived in society, I propose to briefly analyse the journey that has brought us to the present stage and the factors which have contributed to the evolution of our perceptions.
Historically people have been predominantly inclined to own and trade physical objects. This is probably best explained by the fact that physical objects stimulate our senses and don’t require the capacity to abstract, as opposed to services for instance. Ownership was usually synonymous with possession.
Let us try to break down and extract the fundamentals of the economy of physical goods: we originally came to this world and nothing was owned by anyone; possession by individuals then gave rise to ownership ‘rights’ (obtained through the expenditure of labour — finding or creating possessions); later we formed organisations that exercised territorial control and supported the notion of ownership (via norms and mores that evolved into legal frameworks), as a form of protection of physical goods. Land and raw materials are the building blocks of this aspect of our economy.
When we trade (buy or sell) commodities or other physical goods, what we own is a combination of the raw material, which comes with a limited supply, plus the human/machine work required to transform it to make it ready to be used and/or consumed. Value was historically based on a combination of the inherent worth of the resource (scarcity being a proxy) plus the cost of the work required to transform that resource into an asset. Special asset classes (e.g. art) soon emerged where value was related to intangible factors such as provenance, fashion, skill (as opposed to the quantum of labour) etc.
We can observe that even physical goods contain an abstract element: the design, the capacity to model it, package it and make it appealing to the owners or consumers.
In comparison, digital assets have a stronger element of abstraction which defines their value, while their physical element is often negligible and replaceable (e.g. software can be stored on disk, transferred or printed). These types of assets typically stimulate our intellect and imagination, as our senses get activated via a form of rendering which can be visual, acoustic or tactile. Documents, paintings, photos, sculptures and music notations have historical equivalents that predate any form of electrically-based analog or digital representations.
The peculiarity of digital goods is that they can be copied exactly at very low cost: for example, they can be easily reproduced in multiple representations on heterogeneous physical platforms or substrates thanks to the discrete nature in which we store them (using a simplified binary format). The perceivable form can be reconstructed and derived from these equal representations an infinite number of times. This is a feature that dramatically influences how we value digital assets. The opportunity to create replicas implies that it is not the copy nor the rendering that should be valued, but rather the original digital work. In fact, this is one of the primary achievements that blockchain has introduced via the hash lock inherent to its data structure.
If used correctly the capacity to clone a digital item can increase confidence that it will exist indefinitely and therefore maintain its value. However, as mentioned in my previous blog post (Blockchain 2018 — Myth vs. Reality) the immutability and perpetual existence of digital goods are not immune from facing destruction, as at present there is a dependence on a physical medium (e.g. hard disk storage) that is potentially subject to alteration, degradation or obsolescence.
A blockchain, such as that of the Bitcoin network, represents a model for vast replication and reinforcement of digital information via so-called Distributed Ledger Technology (DLT). Repair mechanisms can intervene in order to restore integrity in the event that data gets corrupted by a degrading physical support (i.e. a hard disk failure) or a malicious actor. The validity of data is agreed upon by a majority (the level of majority varying across different DLT implementations) of peer-to-peer actors (ledgers) through a process known as consensus.
This is a step in the right direction, although the exploration of increasingly advanced platforms to preserve digital assets is expected to evolve further. As genetic evolution suggests, clones with equal characteristics can all face extinction by the introduction of an actor that makes the environment unfit for survival in a particular form. Thus, it might be sensible to introduce heterogeneous types of ledgers to ensure their continued preservation on a variety of physical platforms and therefore enhance the likelihood of survival of information.
The evolution of services and their automation
In the previous paragraph, we briefly introduced a distinction between physical assets and goods where the abstraction element is dominant. Here I propose to analyse how we have started to attach value to services and how we are becoming increasingly demanding about their performance and quality.
Services are a form of abstract valuable commonly traded on the market. They represent the actions bound to the contractual terms under which a transformation takes place. This transformation can apply to physical goods, digital assets, other services themselves or to individuals. What we trade, in this case, is the potential to exercise a transformation, which in some circumstances might have been applied already. For instance, a transformed commodity, such as refined oil, has already undergone a transformation from its original raw form.
Another example is an artefact where a particular shape can either be of use or trigger emotional responses, such as artefacts with artistic value. Service transformation in the art world can be highly individualistic (depending on the identity of the person doing the transforming (the artist; the critic; the gallery etc) or the audience for the transformed work. Thus, Duchamp’s elevation (or, possibly, degradation) of a porcelain urinal to artwork relied on a number of connected elements (i.e. transformational actions by actors in the art world and beyond) for the transformation to be successful — these elements are often only recognised and/or understood after the transformation has been affected.
Even the rendering from an abstract form, such as with music notation or a record, the actual sound is a type of transformation that we consider valuable and commonly trade. These transformations can be performed by humans or machinery. With the surge of interest in digital goods, there is a corresponding increasing interest in acquiring services to transform them.
As these transformations are being automated more and more, and the human element is progressively being removed, even services are gradually taking the shape of automated algorithms that are yet another form of digital asset, as is the case with Smart Contracts. Note, however, that in order to apply the transformation, an algorithm is not enough, we need an executor such as a physical or virtual machine.
In Part 2 we will analyse how the automation of services has led to the evolution of Smart Contracts, as a way to deliver efficient, transparent and traceable transformations.
Sustainability and Access to resources
Intellectual and imagination stimulation is not the only motivator that explains the increasing interest in digital goods and consequently their rising market value. Physical goods are known to be quite costly to handle. In order to create, trade, own and preserve them there is a significant expenditure required for storage, transport, insurance, maintenance, extraction of raw materials etc.
There is a competitive and environmental cost involved, which makes access to physical resources inherently non-scalable and occasionally prohibitive, especially in concentrated urban areas. As a result, people are incentivised to own and trade digital goods and services, which turns out to be a more sustainable way forward.
For example, let us think about an artist who lives in a densely populated city and needs to acquire a canvas, paint, brushes, and so on, plus studio and storage space in order to create a painting. Finding that these resources are difficult or impossible to access, he/she decides to produce their artwork in a digital form.
Services traditionally require resources to be delivered (e.g. raw material processing). However, a subset of these (such as those requiring non-physical effort, for instance, stock market trading, legal or accounting services) are ideally suited to being carried out at a significantly lower cost via the application of algorithmic automations.
Note: this analysis assumes that the high carbon footprint required to drive the ‘Proof of Work’ consensus mechanism used in many DLT ecosystems can be avoided, otherwise the sustainability advantage can be legitimately debated.
The Generative Approach
The affordable access to digital resources, combined with the creation of consistently innovative algorithms has also contributed to the rise of a generative production of digital assets. These include partial generation, typically obtained by combining and assembling pre-made parts: e.g. Robohash derives a hash from a text added to the URL that leads to a fixed combination of mouths, eyes, faces, body and accessories.
Other approaches involve Neural Net Deep Learning: e.g. ThisPersonDoesNotExist uses a technology known as Generative Adversarial Network (GAN) released by NVidia Research Labs to generate random people faces, Magenta uses a Google TensorFlow library to generate Music and Art, while DeepArt uses a patented neural net implementation based on the 19-layer VGG network.
Project DreamCatcher also uses a generative design approach that leverages a wide set of simulated solutions that respond to a set of predefined requirements that a material or shape should satisfy.
When it comes to Generative Art, it is important to ensure scarcity by restricting the creation of digital assets to limited editions, so an auto-generated item can be traded without the danger that an excess of supply triggers deflationary repercussions on its price. In Blockchain 2019 Part 2 we will describe techniques to register Non Fungible Tokens (NFT) on the blockchain in order to track each individual replica of an object while ensuring that there are no illegal ones.
Interesting approaches directly linked to Blockchain Technology have been launched recently such as the AutoGlyphs from LarvaLabs, although this remains an open area for further exploration. Remarkably successful is the case of Obvious Art where another application of the GAN approach resulted in a Generated Artwork being auctioned off for $432,500.
What prevents mass adoption of digital goods
Whereas it is sensible to forecast a significant expansion of the digital assets market in the coming years, it is also true that, at present, there are still several psychological barriers to overcome in order to get broader traction in the market.
The primary challenge relates to trust. A purchaser wants some guarantees that traded assets are genuine and that the seller owns them or acts on behalf of the owner. DLT provides a solid way to work out the history of a registered item without interrogating a centralised trusted entity. Provenance and ownership are inferable and verifiable from a number of replicated ledgers while block sequences can help ensure there is no double spending or double sale taking place within a certain time frame.
The second challenge is linked to the meaning of ownership outside of the context of a specific market. I would like to cite as an example the closure of Microsoft’s eBook store. Microsoft’s decision to pull out of the ebook market, presumably motivated by a lack of profit, could have an impact on all ebook purchases that were made on that platform. The perception of the customer was obviously that owning an ebook was the same as owning a physical book. What Microsoft might have contractually agreed through its End-User License Agreement (EULA), however, is that this is true only within the contextual existence of its platform.
This has also happened in video games where enthusiast players are perceiving the acquisition of a sword, or armour as if they were real objects. Even without the game closing down its online presence (e.g. when its maintenance costs become unsustainable), a lack of interest or reduced popularity might result in a digital item losing its value.
There is a push, in this sense, towards forms of ownership that can break out from the restrictions of a specific market and be maintained in a broader context. Blockchain’s DLT in conjunction with Smart Contracts, that exist potentially indefinitely, can be used to serve this purpose allowing people to effectively retain their digital items’ use across multiple applications. Whether those items will have a utility or value outside the context and platform in/on which they were originally created remains to be seen.
Even the acquisition of digital art requires a substantial paradigm shift. Compared to what happens with physical artefacts, there is not an equivalent tangible sense of taking home (or to one’s secure storage vault) a purchased object. This has been substituted by a verifiable trace on a distributed ledger that indicates to whom a registered digital object belongs.
Sensorial forms can also help in adapting to this new form of ownership. For instance, a digital work of art could be printed, a 3D model could be rendered for a VR or AR experience or 3D printed. In fact, to control what you can do with a digital item is per se a form of partial ownership, which can be traded. This is different from the concept of fractional ownership where your ownership comes in a general but diluted form. It is more a functional type of ownership. This is a concept which exists in relation to certain traditional, non-digital assets, often bounded by national laws and the physical form of those assets. For instance, I can own a classic Ferrari and allow someone else to race it; I can display it in my museum and charge an entry fee to visitors; but I will be restricted in how I am permitted to use the Ferrari name and badge attached to that vehicle.
The transition to these new notions of ownership is particularly demanding when it comes to digital non-fungible assets. Meanwhile, embracing fungible assets, such as a cryptocurrency, has been somewhat easier for customers who are already used to relating to financial instruments. This is probably because fungible assets serve the unique function of paying for something, while in the case of non-fungible assets there is a range of functions that define their meaning in the digital or physical space.
In this post we have discussed a major emerging innovation that blockchain technology has influenced dramatically over the last two years — the ownership of digital assets. In Blockchain 2019 — Part 2 we will expand on how the handling of assets gets automated via increasingly powerful Smart Contracts.
What we are witnessing is a new era that is likely to revolutionise the perception of ownership and reliance on trusted and trustless forms of automation. This is driven by the need to increase interoperability, cost compression, sustainability, performance (as in the speed at which events occur) and customisation, which are all aspects where traditional centralised fintech systems have not given a sufficient solution. It is worthwhile, however, to remind ourselves that the journey towards providing a response to these requirements, should not come at the expense of safety and security.
Privacy and sharing are also areas heavily debated. Owners of digital assets often prefer their identity to remain anonymous, while the benefit of socially shared information is widely recognised. An art collector, for instance, might not want to disclose his or her personal identity. Certainly, a lot more still remains to be explored as we are clearly just at the beginning of a wider journey that is going to reshape global digital and physical markets.
At Erlang Solutions we are collaborating with partners in researching innovative and performant services to support a wide range of clients. This ranges from building core blockchain technologies to more specific distributed applications supported by Smart Contracts. Part of this effort has been shared on our website where you can find some information on who we work with in the fintech world and some interesting case studies, others of which remain under the scope of NDAs.
This post intentionally aims at providing a state-of-the-art analysis. We soon expect to be in a position to release more specific and, possibly controversial, articles where a bolder vision will be illustrated. Get notification when more content gets published, simply sign up to our FinTech newsletter — you know the drill, we need your contact details — but we are not spammers!
Originally published at www.erlang-solutions.com.