Money, Blockchains, and Social Scalability
Money, blockchains, and social scalability





Money, blockchains, and social scalability





Introduction 

Blockchains are all the rage. The
oldest and biggest blockchain of them all is Bitcoin,
which over its eight-year history so far starshipped in value from 10,000 bitcoins per
pizza (before there were exchanges that priced bitcoin in traditional
currencies) to over $1,000 per bitcoin. As of this writing Bitcoin has a market
capitalization of over $16 billion. Running non-stop for eight years, with
almost no financial loss on the chain itself, it is now in important ways the
most reliable and secure financial network in the world. 


The secret to Bitcoin’s success
is certainly not its computational efficiency or its scalability in the
consumption of resources.  Specialized Bitcoin
hardware is designed by highly paid experts to perform only one particular
function – to repetitively solve a very specific and intentionally very
expensive kind of computational puzzle. That puzzle is called a proof-of-work,
because the sole output of the computation is just a proof that the computer
did a costly computation. Bitcoin’s puzzle-solving hardware probably consumes
in total over 500 megawatts of electricity. 
And that is not the only feature of Bitcoin that strikes an engineer or
businessman who is focused on minimizing resource costs as highly quixotic. Rather
than reduce its protocol messages to be as few as possible, each
Bitcoin-running computer sprays the Internet with a redundantly large number of
“inventory vector” packets to make very sure that all messages get accurately through
to as many other Bitcoin computers as possible. 
As a result, the Bitcoin blockchain cannot process as many transactions per second as a
traditional payment network such as PayPal or Visa. Bitcoin offends the
sensibilities of resource-conscious and performance-measure-maximizing
engineers and businessmen alike.

Instead, the secret to
Bitcoin’s success is that its prolific resource consumption and poor
computational scalability is buying something even more valuable: social
scalability. Social scalability is the ability of an institution –- a
relationship or shared endeavor, in which multiple people repeatedly
participate, and featuring customs, rules, or other features which constrain or
motivate participants’ behaviors -- to overcome shortcomings in human minds and
in the motivating or constraining aspects of said institution that limit who or
how many can successfully participate. Social
scalability is about the ways and extents to which participants can think about
and respond to institutions and fellow participants as the variety and numbers
of participants in those institutions or relationships grow.  It's about
human limitations, not about technological limitations or physical resource
constraints. There are separate engineering disciplines, such as
computer science, for assessing the physical limitations of a technology itself,
including the resource capacities needed for a technology to handle a greater
number of users or a greater rate of use. Those engineering scalability
disciplines are not, except by way of contrast with social scalability, the
subject of this essay.

Even though social scalability
is about the cognitive limitations and behavior tendencies of minds, not about
the physical resource limitations of machines, it makes eminent sense, and
indeed is often crucial, to think and talk about the social scalability of a
technology that facilitates an institution. The social scalability of an
institutional technology depends on how that technology constrains or motivates
participation in that institution, including protection of participants and the
institution itself from harmful participation or attack.  One way to estimate the social scalability of
an institutional technology is by the number of people who can beneficially
participate in the institution. Another way to estimate social scalability is by
the extra benefits and harms an institution bestows or imposes on participants,
before, for cognitive or behavioral reasons, the expected costs and other harms
of participating in an institution grow faster than its benefits.  The cultural and jurisdictional diversity of
people who can beneficially participate in an institution is also often
important, especially in the global Internet context. The more an institution
depends on local laws, customs, or language, the less socially scalable it is.

Without institutional and
technological innovations of the past, participation in shared human endeavors
would usually be limited to at most about 150 people – the famous “Dunbar number”.  In the Internet era, new innovations continue
to scale our social capabilities. In this article I will discuss how
blockchains, and in particular public blockchains that implement
cryptocurrencies, increase social scalability, even at a dreadful reduction in
computational efficiency and scalability.








Cognitive capacity – here in the form of the relative size of a
species’ neocortex – set limits on how large primate groups can be.  Maintaining animal or intimate human groups
requires extensive emotional communications and investments in relationships,
such as grooming in primates and gossiping, humor, story-telling, and other
conversations, songs, and play in traditional human groups. Overcoming human
cognitive limits to who or how many people can participate in an institution –
the famous “Dunbar number” of around 150 people -- requires institutional and
technological innovation. (Source) 
 







Innovations in social
scalability involve institutional and technological improvements that move
function from mind to paper or mind to machine, lowering cognitive costs while
increasing the value of information flowing between minds, reducing vulnerability,
and/or searching for and discovering new and mutually beneficial participants.  Alfred North Whitehead said, "It is a profoundly erroneous truism, repeated by all copy-books and
by eminent people when they are making speeches, that we should cultivate the
habit of thinking what we are doing. The precise opposite is the case.
Civilization advances by extending the number of important operations which we
can perform without thinking about them." Friedrich Hayek added: “We make
constant use of formulas, symbols, and rules whose meaning we do not understand
and through the use of which we avail ourselves of the assistance of knowledge
which individually we do not possess. We have developed these practices and
institutions by building upon habits and institutions which have proved
successful in their own sphere and which have in turn become the foundation of
the civilization we have built up.”  

A wide
variety of innovations reduce our vulnerability to fellow participants, intermediaries,
and outsiders, and thereby lower our need to spend our scarce cognitive
capacities worrying about how an increasingly large number of increasingly
diverse people might behave. Another class of improvements motivates the
accurate collection and transmission of valuable information between an
increasing number and variety of participants. Yet other advances enable a
wider number or variety of mutually beneficial participants can discover each
other.  All these kinds of innovations have
over the course of human prehistory and history improved social scalability,
sometimes dramatically so, making our modern civilization with its vast global
population feasible. Modern information technology (IT), especially by making
use of the historically recent discoveries of computer science, can often
discover many more mutually beneficial matches, can improve motivations for
information quality, and can reduce the need for trust within certain kinds of
institutional transactions, with respect to an increasingly large number and
variety of people, thereby further increasing social scalability in some very important
ways.

Information flows between minds
– what I have called intersubjective protocols – include spoken and written words, custom (tradition), the contents of law
(its rules, customs, and case precedents), a variety of other symbols (e.g.
“star” ratings common in online reputation systems), and market prices, among many others.

Trust minimization is reducing
the vulnerability of participants to each other’s and to outsiders’ and
intermediaries’ potential for harmful behavior.  Most institutions which have undergone a
lengthy cultural evolution, such as law (which lowers vulnerability to
violence, theft, and fraud), as well as technologies of security, reduce, on
balance, and in more ways than the reverse, our vulnerabilities to, and thus
our needs to trust, our fellow humans, compared with our vulnerabilities before
these institutions and technologies evolved. In most cases an often trusted and
sufficiently trustworthy institution (such as a market) depends on its
participants trusting, usually implicitly, another sufficiently trustworthy
institution (such as contract law). These trusted institutions in turn traditionally
implement a variety of accounting, legal, security, or other controls that make
them usually and sufficiently, at least for facilitating the functionality of
their client institutions, trustworthy, by minimizing vulnerability to their own
participants (such as accountants, lawyers, regulators, and investigators). An
innovation can only partially take away some kinds of vulnerability, i.e.
reduce the need for or risk of trust in other people. There is no such thing as
a fully trustless institution or technology. 


The nonexistence of complete
trustlessness is true even of our strongest security technology, encryption. Although
some cryptographic protocols do guarantee certain specific data relationships with
astronomically high probability against opponents with astronomically high
computing power, they do not provide complete guarantees when accounting for
all possible behaviors of all participants. For example, encryption can
strongly protect an e-mail from direct eavesdropping by third parties, but the
sender still trusts the recipient to not forward or otherwise divulge the
contents of that email, directly or indirectly to any undesired third parties.
As another example, in our strongest consensus protocols harmful behavior by
certain fractions of participants or intermediaries well short of 100% (as
measured by their computing power, stake-holding, or individuation and
counting) can compromise the integrity of transactions or information flows
between participants and thereby on balance harm the participants.  The historically recent breakthroughs of
computer science can reduce vulnerabilities, often dramatically so, but they
are far from eliminating all kinds of vulnerabilities to the harmful behavior
of any potential attacker.

Matchmaking is facilitating the
mutual discovery of mutually beneficial participants. Matchmaking is probably
the kind of social scalability at which the Internet has most excelled. Social
networks like Usenet News, Facebook, and Twitter facilitate the mutual
discovery of like-minded or otherwise mutually entertaining or mutually
informing people (and even future spouses!). After they have allowed people
more likely to be of mutual benefit to discover each other, social networks
then facilitate relationships at various levels of personal investment, from
casual to frequent to obsessive. Christopher Allen among others has done some interesting and detailed analyses about group size
and time spent mutually interacting in online games and associated social
networks.

eBay, Uber, AirBnB, and online financial exchanges have
brought social scalability via often great improvements in commercial matchmaking:
searching for, finding, bringing together, and facilitating the negotiation of
mutually beneficial commercial or retail deals. 
These or related services also facilitate performances such as payment
and shipping, as well as verification that other obligations undertaken by
strangers in these deals have been performed and communication about the
quality of such performances (as with “star rating” systems, Yelp reviews, and
the like).

Whereas the main social scalability benefit of the Internet
has been matchmaking, the predominant direct social scalability benefit of
blockchains is trust minimization. A blockchain can reduce vulnerability by locking
in the integrity of some important performances (such as the creation and
payment of money) and some important information flows, and in the future may
reduce the vulnerability of the integrity of some important matchmaking
functions.  Trust in the secret and
arbitrarily mutable activities of a private computation can be replaced by
verifiable confidence in the behavior of a generally immutable public
computation. This essay will focus on such vulnerability reduction and its
benefit in facilitating a standard performance beneficial to a wide variety of
potential counterparties, namely trust-minimized money. 


Money and Markets 

Money and markets directly benefit the participants in each
particular trade by the market matching a buyer with a mutually beneficial
seller and by a widely acceptable and standardized counter-performance (money).  I use markets here in the sense Adam Smith
used the term: not as a specific place or service where buyers and sellers are
brought together (although it might sometimes involve these), but rather the
broad set of typically pairwise exchanges whereby the supply chain that makes a
product is coordinated.

Money and markets also incentivize creation of more accurate
price signals that reduce negotiation costs and errors for participants in
other similar exchanges.  The potent combination
of money and market thereby allowed a far higher number and variety of
participants to coordinate their economic activities than previous exchange
institutions, which more resembled bilateral monopolies than competitive markets.

Markets and money involve matchmaking (bringing together
buyer and seller), trust reduction (trusting in the self-interest rather than
in the altruism of acquaintances and strangers), scalable performance (via
money, a widely acceptable and reusable medium for counter-performance), and
quality information flow (market prices).

The greatest early thinker about money and markets was Adam
Smith.  At the dawn of the industrial revolution in
Britain, Smith observed in The Wealth of Nations how making even the most humble of products depended,
directly and indirectly, on the work of large numbers of a wide variety of
people:




Observe
the accommodation of the most common artificer or day-laborer in a civilized
and thriving country, and you will perceive that the number of people of whose
industry a part, though but a small part, has been employed in procuring him
this accommodation, exceeds all computation. The woolen coat, for example,
which covers the day laborer, as coarse and rough as it may appear, is the
produce of the joint labor of a great multitude of workmen. The shepherd, the
sorter of the wool, the wool-comber or carder, the dyer, the scribbler, the
spinner, the weaver, the fuller, the dresser, with many others, must all join
their different arts in order to complete even this homely production. How many
merchants and carriers, besides, must have been employed in transporting the
materials from some of those workmen to others who often live in a very distant
part of the country! How much commerce and navigation in particular, how many
shipbuilders, sailors, sail makers, rope makers, must have been employed in
order to bring together the different drugs made use of by the dyer, which
often come from the remotest corners of the world! What a variety of labor,
too, is necessary in order to produce the tools of the meanest of those
workmen! To say nothing of such complicated machines as the ship of the sailor,
the mill of the fuller, or even the loom of the weaver, let us consider only
what a variety of labor is requisite in order to form that very simple machine,
the shears with which the shepherd clips the wool. The miner, the builder of
the furnace for smelting the ore, the feller of the timber, the burner of the
charcoal to be made use of in the smelting-house, the brick maker, the brick layer,
the workmen who attend the furnace, the millwright, the forger, the smith, must
all of them join their different arts in order to produce them. Were we to
examine, in the same manner, all the different parts of his dress and household
furniture, the coarse linen shirt which he wears nest his skin, the shoes which
cover his feet, the bed which he lies on, and all the different parts which
compose it, the kitchen grate at which be prepares his victuals, the coals
which he makes use of for that purpose, dug from the bowels of the earth, and
brought to him perhaps by a long sea and a long land carriage, all the other
utensils of his kitchen, all the furniture of his table, the knives and forks,
the earthen or pewter plates upon which he serves up and divides his victuals,
the different hands employed in preparing his bread and his beer, the glass
window which lets in the heat and the light, and keeps out the wind and the
rain, with all the knowledge and art requisite for preparing that beautiful and
happy invention, without which these northern parts of the world could scarce
have afforded a very comfortable habitation, together with the tools of all the
different workmen employed in producing those different conveniences; if we
examine, I say, all these things, and consider what a variety of labor is employed about each of them, we
shall be sensible that without the assistance and co-operation of many
thousands, the very meanest person in a civilized country could not be provided,
even according to what we may falsely imagine the easy and simple manner in
which he is commonly accommodated. 

And this was before the many successive waves of industrial
revolution and globalization between 1776 and now that refined, elaborated, and
extended the division of labor many times more. Rather than trusting in the unlikely
altruism of so many strangers, markets and money create many pairings of mutual
benefit and thus motivate this large network of mutually oblivious people to
act in our interests:
 In civilized society man stands at all times
in need of the cooperation and assistance of great multitudes, while his whole
life is scarce sufficient to gain the friendship of a few persons…[In contrast
to other animals, man has an almost constant occasion for the help of his
brethren, and it is vain for him to expect it from their benevolence only.  [Exchange is the] manner in which we obtain
from another the far greater part of those good offices which we stand in need
of. It is not from the benevolence of the butcher, the brewer, or the baker,
that we expect our dinner, but from their regard for their own interest. 









Smith goes on to describe how division of labor, and thus
labor productivity, depends on the extent of the network of pairwise exchanges:
“As it is the power of exchanging that gives occasion to the division of labor,
so the extent of this division must always be limited by the extent of that
power, or, in other words, by the extent of the market”.  As the exchange network around a country and
around the globe grows, involving a greater number and variety of producers, so
grows the division of labor and thereby labor productivity.

Money
facilitates social scalability by increasing the opportunities for this
exchange. By lowering coincidence problems (coincidence-of-wants in exchange
and coincidence-of-want-and-event in unilateral transfers), via a widely
acceptable and reusable form of wealth storage and transfer, money greatly
lowered transaction costs, making possible more exchanges of a greater variety
of goods and services involving exchanges and other wealth transfer
relationships with a much larger number and much wider variety of people.


A wide variety of media, from oral language itself, clay,
paper, telegraph, radio, and computer networks, have served to communicate
offers, acceptances, and the resulting deals and prices, as well as performance
monitoring and other business communications. One of the most
knowledgeable observations of the price network produced by markets and money can
be found in Friedrich Hayek’s essay, “The Use of Knowledge in Society”: 
 In a system in which the knowledge of the relevant facts
is dispersed among many people, prices can act to coordinate the separate
actions of different people…in any society in which many people collaborate,
this planning, whoever does it, will in some measure have to be based on
knowledge which, in the first instance, is not given to the planner but to
somebody else, which somehow will have to be conveyed to the planner. The
various ways in which the knowledge on which people base their plans is
communicated to them is the crucial problem for any theory explaining the
economic process, and the problem of what is the best way of utilizing
knowledge initially dispersed among all the people is at least one of the main
problems of economic policy—or of designing an efficient economic system…The mere fact that there is one price for any commodity—or
rather that local prices are connected in a manner determined by the cost of
transport, etc.—brings about the solution which (it is just conceptually
possible) might have been arrived at by one single mind possessing all the
information which is in fact dispersed among all the people involved in the
process…The marvel is that in a case like that of a scarcity of one raw
material, without an order being issued, without more than perhaps a handful of
people knowing the cause, tens of thousands of people whose identity could not
be ascertained by months of investigation, are made to use the material or its
products more sparingly; i.e., they
move in the right direction….The price system is just one of those formations
which man has learned to use (though he is still very far from having learned
to make the best use of it) after he had stumbled upon it without understanding
it. Through it not only a division of labor but also a coordinated utilization
of resources based on an equally divided knowledge has become possible…a
solution is produced by the interactions of people each of whom possesses only
partial knowledge.


The Social Scalability of Network Security 


Where long ago we used clay, and more recently paper, today
programs and protocols running on our computers and data networks implement
most of our commercial dealings. While this has greatly improved matchmaking
and information flow, it has come at the cost of an increase in vulnerability
to harmful behavior. 

As networks grow, more people with
fewer mutually understood habits of and constraints on behavior are added.  Security via root-trusting access control,
designed for small and chummy offices like Bell Labs where co-workers were well
known and income and expenditures well controlled by paper procedures rather
than performed on these office computers, breaks down as an efficient and
effective security mechanism as organizations become larger, as organizational
boundaries are crossed, and as more valuable and concentrated resources such as
money are put on or activated via the computers. The more strangers one
receives emails from, the more likely one is likely to get a phishing attack or
a malware-laced attachment.  Traditional
computer security is not very socially scalable. As I describe in The Dawn of Trustworthy Computing:


When we currently use a smart phone or a laptop
on a cell network or the Internet, the other end of these interactions
typically run on other solo computers, such as web servers. Practically all of
these machines have architectures that were designed to be controlled by a
single person or a hierarchy of people who know and trust each other. From the
point of view of a remote web or app user, these architectures are based on
full trust in an unknown "root" administrator, who can control
everything that happens on the server: they can read, alter, delete, or block
any data on that computer at will.  Even data sent encrypted over a
network is eventually unencrypted and ends up on a computer controlled in this
total way. With current web services we are fully trusting, in other words we
are fully vulnerable to, the computer, or more specifically the people who have
access to that computer, both insiders and hackers, to faithfully execute our
orders, secure our payments, and so on. If somebody on the other end wants to
ignore or falsify what you've instructed the web server to do, no strong
security is stopping them, only fallible and expensive human institutions,
which often stop at national borders.









Many server computers are not valuable enough for insiders
or outsiders to attack. But an increasing number of others contain valuable
concentrations of resources, motivating attack. Centralized root-trusting
security scales poorly. As the resources controlled by computers become more
valuable and more concentrated, traditional root-trusting security becomes more
like the “call the cop” security we are used to in the physical world.  Fortunately, with blockchains we can do much
better for many of our most important computations.


Blockchains and
Cryptocurrencies

Scalable markets and prices require scalable money. Scalable
money requires scalable security, so that a greater number and variety of
people can use the currency without losing its integrity against forgery,
inflation, and theft.

An individual or group communicating under the name “Satoshi
Nakamoto” brought Bitcoin to the Internet in 2009. Satoshi’s breakthrough
with money was to provide social scalability via trust minimization: reducing vulnerability
to counterparties and third parties alike. By substituting computationally
expensive but automated security for computationally cheap but institutionally
expensive traditional security, Satoshi gained a nice increase in social
scalability. A set of partially trusted intermediaries replaces a single and fully
trusted intermediary.








Financial
controls on computational steroids: a blockchain as an army of robots, each checking
up on each other’s work.
 





When we can secure the most important
functionality of a financial network by computer science rather than by the traditional
accountants, regulators, investigators, police, and lawyers, we go from a
system that is manual, local, and of inconsistent security to one that is
automated, global, and much more secure. Cryptocurrencies, when implemented
properly on public blockchains, can substitute an army of computers for a large
number of traditional banking bureaucrats. “These
block chain computers will allow us to put the most crucial parts of our online
protocols on a far more reliable and secure footing, and make possible
fiduciary interactions that we previously dared not do on a global network.” (Source) 

The
characteristics most distinctively valuable in blockchain technology in
general, and Bitcoin in particular — for example

independence from existing institutions for its basic operations

ability to operate seamlessly across borders


come from the
high levels of security and reliability a blockchain can maintain without human
intervention. Without that high security it’s just a gratuitously wasteful
distributed database technology still tied to the local bureaucracies it would
have to depend upon for its integrity.








Since the mid-20th
century computing has increased in efficiency by many orders of magnitude, but
humans are using the same brains. This has created plenty of possibility for
overcoming human limitations, and institutions based solely on human minds,
with computational capabilities, including in security, doing what they do
best, with human minds doing what they still do best. As a result, humans have
no more raw mental ability to scale up our institutions than we ever have. But
there is plenty of potential for improving social scalability by replacing some
human functions with computational ones. (An important note – this argument
depends on the slope, not the absolute position, of the human ability line.  The absolute position shown above is
arbitrary and depends on what human “computation” we are measuring).


A new
centralized financial entity, a trusted third party without a “human
blockchain” of the kind employed by traditional finance, is at high risk of
becoming the next Mt. Gox; it is not going to become a trustworthy financial
intermediary without that bureaucracy.

Computers and networks are cheap.  Scaling computational resources requires
cheap additional resources. Scaling human traditional institutions in a
reliable and secure manner requires increasing amounts accountants, lawyers,
regulators, and police, along with the increase in bureaucracy, risk, and
stress that such institutions entail. Lawyers are costly. Regulation is to the
moon. Computer science secures money far better than accountants, police, and
lawyers.

In computer
science there are fundamental security versus performance tradeoffs. Bitcoin's automated
integrity comes at high costs in its performance and resource usage. Nobody has
discovered any way to greatly increase the computational scalability of the
Bitcoin blockchain, for example its transaction throughput, and demonstrated
that this improvement does not compromise Bitcoin’s security.

It is probable that no such big but integrity-preserving performance improvement is
possible for the Bitcoin blockchain; this may be one of these unavoidable
tradeoffs.  Compared to existing financial IT, Satoshi made radical
tradeoffs in favor of security and against performance. The seemingly wasteful
process of mining is the most obvious of these tradeoffs, but Bitcoin also
makes others.  Among them is that it requires high redundancy in its
messaging.  Mathematically provable integrity would require full broadcast
between all nodes.  Bitcoin can’t achieve that but to even get anywhere
close to a good approximation of it requires a very high level of redundancy.
 So a 1 MB block consumes far more resources than a 1 MB web page, because
it has to be transmitted, processed, and stored with high redundancy for
Bitcoin to achieve its automated integrity.

These
necessary tradeoffs, sacrificing performance in order to achieve the security
necessary for independent, seamlessly global, and automated integrity, mean
that the Bitcoin blockchain itself cannot possibly come anywhere near Visa
transaction-per-second numbers and maintain the automated integrity that
creates its distinctive advantages versus these traditional financial systems.
Instead, a less trust-minimized peripheral payment network (possibly Lightning )
will be needed to bear a larger number of lower-value bitcoin-denominated
transactions than Bitcoin blockchain is capable of, using the Bitcoin
blockchain to periodically settle with one high-value transaction batches of peripheral network transactions.

Bitcoin supports a lower rate
transactions than Visa or PayPal, but due to its stronger automated security
these can be much more important transactions. Anybody
with a decent Internet connection and a smart phone who can pay $0.20-$2
transaction fees – substantially lower than current remitance fees -- can
access Bitcoin any where on the globe. 
Lower value transactions with lower fees will need to be implemented on
peripheral bitcoin networks.

When it comes
to small-b bitcoin, the currency, there is nothing impossible about paying
retail with bitcoin the way you’d pay with a fiat currency —
bitcoin-denominated credit and debt cards, for example, with all the chargeback and transactions-per-second
capabilities of a credit or debit card. And there are also clever ways to do
peripheral bitcoin retail payments in which small value payments happen
off-chain and are only periodically bulk-settled on the Capital-B Bitcoin
blockchain. That blockchain is going to evolve into a high-value settlement
layer as bitcoin use grows, and we will see peripheral networks being used for
small-b bitcoin retail transactions.

When I designed bit gold I already knew consensus did not scale to large transaction throughputs securely,
so I designed it with a two-tier architecture: (1) bit gold itself, the
settlement layer, and (2) Chaumian digital cash,
a peripheral payment network which would provide retail payments with high
transactions-per-second performance and privacy (through Chaumian blinding),
but would like Visa be a trusted third party and thus require a “human
blockchain” of accountants, etc. to operate with integrity.  The
peripheral payment network can involve only small value transactions, thereby requiring
much less of a human army to avoid the fate of Mt. Gox.







Ralph Merkle: pioneer
of public-key cryptography and inventor of hierarchical hash-tree structures
(Merkle trees).
 







Money requires
social scalability in its design, via security. For example it should be very
hard for any participant or intermediary to forge money (to dilute the supply
curve leading to undue or unexpected inflation).  Gold can have value anywhere in the world and
is immune from hyperinflation because its value doesn’t depend on a central
authority.  Bitcoin excels at both these factors and runs online, enabling
somebody in Albania to use Bitcoin to pay somebody in Zimbabwe with minimal
trust in or and no payment of quasi-monopoly profits to intermediaries, and
with minimum vulnerability to third parties.

There are all
sorts of definitions of “blockchain” out there, almost all of them just
implicitly broad hand-waving amid the mountains of marketing hype. I suggest a
clear definition that can be communicated to lay people.  It is a
blockchain if it has blocks and it has chains. The “chains” should be Merkle trees or other cryptographic structures with a similar integrity functionality of
post-unforgeable   integrity.  Also the transactions and any other data whose integrity is
protected by a blockchain should be replicated in a way objectively tolerant to
worst-case malicious problems and actors to as high a degree as possible
(typically the system can behave as previously specified up to a fraction of
1/3 to 1/2 of the servers maliciously trying to subvert it to behave differently).







Bitcoin’s socially
scalable security, based on computer science rather than on police and lawyers,
allows, for example, customers in Africa to pay suppliers in China seamlessly
across borders. A private blockchain cannot accomplish this
feat nearly as easily, since it would require an identification scheme,
certificate authority, and PKI shared between these various jurisdictions. (Source)

Because
of this fraction, and because of the (hopefully very rare) need to update
software in a manner that renders prior blocks invalid – an even riskier
situation called a hard fork -- blockchains also need a human governance layer
that is vulnerable to fork politics. The most successful blockchain, Bitcoin,
has maintained its immutable integrity via decentralized decision-making among
experts in the technology combined with a strong dogma of immutability, under
which only the most important and rare bug fixes and design improvements, that
cannot be made any other way, justify a hard fork. Under this philosophy of
governance accounting or legal decisions (such as altering an account balance
or undoing a transaction) never justify a hard fork, but should be accomplished
by traditional governance outside of (or on top of) the system (e.g. via a
court injunction forcing a Bitcoin user to send a new transaction that
effectively undoes the old one, or confiscating the particular keys and thus
the particular holdings of a particular user).

To say that
data is post-unforgeable or immutable means that it can’t be undetectably alteredafter being committed to the blockchain. Contrary to some hype this
doesn’t guarantee anything about a datum’s provenance, or its truth or falsity,
before it was committed to the blockchain. That requires additional protocols,
often including expensive traditional controls. Blockchains don’t guarantee
truth; they just preserve truth and lies from later alteration, allowing one to
later securely analyze them, and thus be more confident in uncovering the lies.
Typical computers are computational etch-a-sketch, while blockchains are
computational amber. Important data should be committed to blockchain amber as
early as possible, ideally directly from and cryptographically signed by the device
in which it was generated, to maximize the blockchain’s benefit in securing its
integrity.









A Merkle
tree of four transactions (tx0 through tx3). Combined with a proper
replication and chains of transaction blocks protected by proof-of-work, Merkle trees can make data such as transactions post-unforgeable by consensus. In Bitcoin, a Merkle
root hash securely summarizes and is used to verify the unaltered state of all
the transactions in a block.



My own 1998 “secure property title” architecture
had Merkle trees and replication of data tolerant against an objective fraction
of arbitrarily faulty software or malicious actors, but not blocks.  It
demonstrated my theory that you could protect the integrity of globally shared
data and transactions, and use that ability to design a cryptocurrency (bit
gold). It did not have the more efficient and computationally scalable blocks-and-ledger system that Bitcoin does. Also like today’s private blockchains, secure property
titles assumed and required securely distinguishable and countable nodes.

Given the
objective 51% hashrate attack limit to some important security goals of public
blockchains like Bitcoin and Ethereum, we actually do care about the
distinguishable identity of the most powerful miners to answer the question
“can somebody convince and coordinate the 51%?

Blockchain
security is objectively limited and blockchain governance is heavily influenced
by the potential for a 51% attack.  An
attack of course does not have to be called an “attack” by the attackers;
instead they might call it “enlightened governance” or “democracy in
action”.  Indeed some kinds of software
updates needed to fix bugs or otherwise improve the protocol require a soft fork.
Some other kinds of software updates require hard forks, which in Bitcoin pose
an even greater security and continuity risks than soft forks. Blockchains,
although reducing trust far more than any other network protocols, are still
far from trustless. Miners are partially trusted fiduciaries, and those who are
not expert developers or computer scientists who have invested a great deal of
time in learning the design principles and codebase of a blockchain must place a
great deal of faith in the expert developer community, much as non-specialists
who want to understand the results of a specialized science do of the
corresponding scientists. During a hard fork exchanges can also be very
influential by deciding which fork to support with their order books and trade
symbol continuity.

Public
blockchains thus mostly but not entirely dodge the identity-is-hard bullet and
take care of its remaining problem of identifying the most powerful miners at a
higher “wet”/“social” level, where it is probably more appropriate, rather than
trying to securely map such an inherently wet (brain-based) concept onto the
protocol, as PKI (public key infrastructure) rather awkwardly tries
to do.

So I think
some of the “private blockchains” qualify as bona fide blockchains; others
should go under the broader rubric of “distributed ledger” or “shared database”
or similar.  They are all very different from and not nearly as socially
scalable as public and permissionless blockchains like Bitcoin and Ethereum.

All of the
following are very similar in requiring an securely identified (distinguishable
and countable) group of servers rather than the arbitrary anonymous membership
of miners in public blockchains. In other words, they require some other,
usually far less socially scalable, solution to the Sybil (sockpuppet) attack problem:




Private blockchains

The “federated” model of sidechains (Alas, nobody has figured out how to do sidechains with any
lesser degree of required trust, despite previous hopes or claims).  Sidechains
can also be private chains, and it’s a nice fit because their architectures and
external dependencies (e.g. on a PKI) are similar.

Multisig-based
schemes, even when done with blockchain-based smart contracts

Threshold-based “oracle” architectures for moving off-blockchain data onto blockchains




The dominant,
but usually not very socially scalable, way to identify a group of servers is
with a PKI based on trusted certificate authorities (CAs).
To avoid the problem that merely trusted third parties are security holes, reliable CAs themselves must be expensive, labor-intensive
bureaucracies that often do extensive background checks themselves or rely on
others (e.g. Dun and Bradstreet for businesses) to do so.  (I once led a
team that designed and built such a CA).  CAs also act as a gatekeeper,
rendering these permissioned systems. CAs can become singular points of
political control and failure.  "Public blockchains are automated,
secure, and global, but identity is labor-intensive, insecure, and local.” 

PKI-enabled
private blockchains are a nice for banks and some other large enterprises
because they already have mature in-house PKIs that cover the employees,
partners, and private servers needed to approve important transactions.
 Bank PKIs are relatively reliable. We also have semi-reliable CAs for web
servers, but not generally speaking for web clients, even though people have
been working on the problem of client certificates since the invention of the
web: for example advertisers would love to have a more secure alternative to
phone numbers and cookies for tracking customer identities. Yet it hasn’t
happened.  

PKI can work
well for some important things and people but it is not nearly so nice or so
easy for lesser entities. Its social scalability is limited by the traditional
wet identity bureaucracy on which it depends.








Some significant thefts in the broader bitcoin ecosystem. Whereas the Bitcoin blockchain
itself is probably the most secure financial network in existence (and indeed must remain far more secure than traditional payment networks in order to maintain its low governance costs and seamless cross-border capability), its
peripheral services based on older centralized web servers are very insecure. (Source: author)


We need more
socially scalable ways to securely count nodes, or to put it another way to
with as much robustness against corruption as possible, assess contributions to
securing the integrity of a blockchain. That is what proof-of-work and broadcast-replication
are about: greatly sacrificing computational scalability in order to improve
social scalability.  That is Satoshi’s brilliant tradeoff.   It
is brilliant because humans are far more expensive than computers and that gap
widens further each year.  And it is brilliant because it allows one to
seamlessly and securely work across human trust boundaries (e.g. national
borders), in contrast to “call-the-cop” architectures like PayPal and Visa that
continually depend on expensive, error-prone, and sometimes corruptible
bureaucracies to function with a reasonable amount of integrity.
Conclusion 
   


The rise of the Internet as seen the rise of a variety of
online institutions, among them social networks, “long-tail” retail (e.g.
Amazon), and a variety of services that allow small and dispersed buyers and
sellers to find and do business with each other (eBay, Uber, AirBnB, etc.)  These are just the initial attempts to take
advantage of our new abilities.  Due to
the massive improvements in information technology over recent decades, the
number and variety of people who can successfully participate in an online
institution is far less often restricted by the objective limits of computers
and networks than it is by limitations of mind and institution that have usually
have not yet been sufficiently redesigned or further evolved to take advantage
of those technological improvements.

These initial Internet efforts have been very centralized.  Blockchain technology, which implements data integrity via computer science rather than via “call the cops”, has so far made possible trust-minimized money -- cryptocurrencies – and will let us make progress in other financial areas as well as other areas where transactions can be based primarily on data available online.

This is not to say that adapting our institutions to our new capabilities will be easy, or indeed in particular cases anything short of difficult and improbable.  Utopian schemes are very popular in the blockchain community, but they are not viable options. Reverse-engineering our highly evolved traditional institutions, and even reviving in new form some old ones, will usually work better than designing from scratch, than grand planning and game theory. One important strategy for doing so was demonstrated by Satoshi – sacrifice computational efficiency and scalability  -- consume more cheap computational resources -- in order to reduce and better leverage the great expense in human resources needed to maintain the relationships between strangers involved modern institutions such as markets, large firms, and governments.







