Dates and Deliverables from Blockchain
Peter writes the following from his personal perspective as an author, lecturer, and an implementer of various computing projects over a period of more than 35 years. His comments are not an official position or an indication of future offerings from salesforce.com inc.
Exhibiting massive mindshare growth over just the past five years, the concept of blockchain data management has seized the stage of global discussion, in disciplines ranging from finance to industry to scientific research. Bankers look to it for acceleration of transactions, shrinking days to seconds. Manufacturers and shippers look to it for improved consistency and reduced costs in supply chain management. Researchers look to it for reduction of data falsification, saying that the general model’s four main properties: identity, timestamping, content, and immutability, could play a valuable role in addressing the diminishing trust in science and scientists due to high-profile cases of questionable (or even fraudulent) data manipulation.
It’s easy to say that blockchain is the future, but it’s been observed that people who describe the future are merely futurists. “Those who can tell when a technology will reach the market? We call them Billionaires.” Can we say anything useful, and even slightly rigorous, about when this will matter to a larger group than technology’s chattering classes?
In 2015, the World Economic Forum’s Global Agenda Council on the Future of Software & Society published a report entitled Deep Shift: Technology Tipping Points and Societal Impact. Unlike most futurist overviews, its forty-four pages were admirably specific in their identification and definition of “21 dazzling technology shifts.”
These were all potential developments, foreseeable without taking any science-fiction liberties, that might affect business, industry, the economy, and global society. A sample of 800 executives and subject matter experts were invited to put these foreseeable innovations on a time line, prospectively dating their arrival as noteworthy parts of our lives.
The single most transformative word, perhaps, on that long list of shifts was “blockchain.”
Conversations Depend on Definitions
Before we go any farther into the when and why, let’s make sure we have something resembling agreement on the what. Blockchain’s appeal is largely based on a vision of shared understandings, but many conversations around the idea often fail to share common meanings of the words they use.
A huge fraction of the occurrences of the word “blockchain” should probably be globally searched-and-replaced with something like “distributed, synchronous ledger, enabling concurrent global access to trusted shared truth without reliance on a central authority.” This won’t happen, because it would become far too difficult to write headlines for articles like “Banks Replaced With Blockchain at International Food Program” (Bloomberg Technology, February 2018) or “Could blockchain run a city state?”
What complicates these conversations is that a subset of them are about the use of blockchain-type distributed ledgers: concisely, as shared data repositories in which “unrelated transactions are bundled into blocks, which are chained together using hashes and (in most cases) broadcast to all participating entities for batch processing.” A smaller fraction of news items and commentaries are specifically about what we might call the Blockchain: the data store for the Bitcoin cryptocurrency.
We might usefully say “distributed ledger” when we mean the general idea; blockchain, with no capitals, when discussing the subset; and Blockchain with a capital B to represent only the Bitcoin data store. Such distinctions may remind some observers of the earliest days of packet-switched networks, back when that was a novel and far from generally accepted idea. We might likely have said “an internet,” back in the mid-1960s, to mean any assembly of multiple networks sharing some common packet protocol for interoperability – but soon, “the Internet” was appropriated as the label of the global TCP/IP net-of-nets after that protocol suite was standardized in 1982.
We do well to acknowledge that twenty years from now, the protocol we call blockchain today may be only a footnote in the saga of mid-2000s data models, much as NCP or X.25 might be considered almost historical networking terms today (by the relative few who know of them at all). The virtues and the feasibility of the general family of distributed-ledger models, rather than the rightness or wrongness of today’s implementations, should probably be the focus of most discussions – as will be the case in what follows here.
How Much, How Soon
With our terms at least somewhat clarified, we can note that the WEF Deep Shift study uses the word blockchain as part of two separate entries: Shift 16, “Bitcoin and the Blockchain,” and Shift 18, “Governments and the Blockchain.” Regardless of any cavils at the use of the ‘B’ word, these shifts are still defined with useful precision.
In the first case, WEF defined the Shift 16 tipping point as 10 percent of global gross domestic product (GDP) stored on blockchain technology. To get a sense of whether that’s a high bar to clear, the report helpfully estimated (reminder: in 2015) that “Currently, the total worth of bitcoin in the blockchain is around $20 billion, or about 0.025 percent of global GDP of around $80 trillion.” Such an expansion through the WEF’s projected occurrence of this milestone, in 2027, would entail an overall growth of 400-fold over a period of twelve years: an average compound growth rate of 65 percent per year.
Is that kind of growth plausible? We might compare that figure against the Moore’s Law growth rate, in many people’s minds the benchmark for an amazingly rapid but nonetheless sustained ascent of a measure of technical progress. Typically stated as a factor of two every 18 months, the Moore rate annualizes to “only” 59 percent per year. At 65 percent per year, we’re therefore talking about a projected growth rate that is high up in the thin air of rapidity of change.
Further, Moore’s Law might seem an especially lofty comparison, when we’re talking about whether we can drive a whole new model of asset storage and movement into general use at that kind of pace. No one objects to their computer being faster, or cheaper, or both: it’s an unmixed blessing. People can have reservations, though, about accepting greater dependence on a shared resource or a remotely provisioned service. Driving that kind of behavior change is much more difficult than merely plugging in new chips.
We can, however, note a pattern of rapid technology adoptions from starting points near zero, versus those where an installed base holds the ground. Developing markets have long been observed to skip right over the model of wired telephony, direct to wireless mobile services. In 2009, a Voice of America report found that 72 percent of Afghanistan’s population were within reach of cellular service, while only one in a hundred had a phone line – with similar figures in Ghana, Nigeria, Uganda, and Bangladesh. Compare this against data showing that even as recently as 2015 there were wired phone lines in 60 percent of United States homes. Using established markets as the basis for our forecasts could easily turn out to be a case of driving with our eyes on the rear-view mirror, rather than looking at the road ahead.
It’s Actually About the Money
In particular, we should think in terms of an enormous expansion of the global middle class, with 88 percent of the next billion new members of that group living in Asia, that seems likely to redraw the map of economic activity – and already, what’s true in emerging markets’ telephone conversations is also becoming apparent in their transactions. Mobile wallet use in Mexico, reported Forbes magazine last October, is more than double that observed in the more commonly check-writing and credit-carding United States, at 38 percent versus 17 percent of their respective populations.
Considering that two billion people on the planet today have yet to enter the world of modern money movement, there are a great many people for whom distributed-ledger money models may be their first language of financial empowerment – and among whom there may be quite rapid adoption, thanks to low costs and high efficiencies, as demonstrated by the previously mentioned United Nations World Food Program initiative that expects to achieve millions of dollars in cost reductions compared to established levels of bank transfer fees.
We also see, even in markets with deep-rooted legacy models, some other signs that people are increasingly adopting distributed services – with their inherent advantages of sharing state, rather than trying to achieve consistency through clumsy messaging.
For example, looking ahead through 2022, Gartner projects continued growth at almost 29 percent per year for usage of office suites delivered as cloud services rather than on-the-desktop (or laptop) applications. Anyone who’s grown used to the frictionless collaboration and versioning behaviors of something like Quip, or Google Docs, is surely loath to return to the emailing of attachments and the use of tools for post-facto reconciliation of different people’s changes.
Is it time for reliable mobile access, shared truth, and convenient collaboration to happen to our money, as it is already happening to our conversations, our documents, and our spreadsheets?
This is part I of a two article series from Peter Coffee. Stay tuned for part II, coming next week.
Leave your comment below, or reply to others.
Please note that this comment section is for thoughtful, on-topic discussions. Admin approval is required for all comments. Your comment may be edited if it contains grammatical errors. Low effort, self-promotional, or impolite comments will be deleted.
Read more from the Meeting of the Minds Blog
Spotlighting innovations in urban sustainability and connected technology
AI has enormous potential to improve the lives of billions of people living in cities and facing a multitude of challenges. However, a blind focus on the technological issues is not sufficient. We are already starting to see a moderation of the technocentric view of algorithmic salvation in New York City, which is the first city in the world to appoint a chief algorithm officer.
There are 7 primary forces determining the success of AI, of which technology is just one. Cities must realize that AI is not the quick technological fix that vendors sell. Not everything will be improved by creating more algorithms and technical prowess. We need to develop a more holistic approach to implementing AI in cities in order to harness the immense potential. We need to create a way to consider each of the seven forces when cities plan for the use of AI.
In New Zealand, persistent, concentrated advocacy and legal cases advanced by Māori people are inspiring biocentric policies; that is, those which recognize that people and nature, including living and non-living elements, are part of an interconnected whole. Along the way, tribal leaders and advocates are successfully making the case that nature; whole systems of rivers, lakes, forests, mountains, and more, deserves legal standing to ensure its protection. An early legislative “win” granted personhood status to the Te Urewera forest in 2014, which codified into law these moving lines:
“Te Urewera is ancient and enduring, a fortress of nature, alive with history; its scenery is abundant with mystery, adventure, and remote beauty … Te Urewera has an identity in and of itself, inspiring people to commit to its care.”
The Te Urewera Act of 2014 did more than redefine how a forest would be managed, it pushed forward the practical expression of a new policy paradigm.
Can U.S. cities transform to overcome extreme car dependency?
In summer 2019, two values driven agencies came together to see if they could incentivize change in five cities with the Made to Move Grant program. This innovative, unique, and inspirational partnership between Degree and Blue Zones is awarding $100,000 dollars to each city to redesign their neighborhoods and city-centers for active, healthy lives. The program aims to create model practices and projects that gain the attention of other cities and inspire evolutionary changes to once again focus on places for people, and design accordingly.