English token money: a brief history

English token money is perhaps an old example of peer-to-peer money – money created and circulated without a central authority. The system emerged for the first time around the English civil war, in 1642, and lasted until 1672. The Government stopped producing small change due to political turmoil and problems with counterfeiting, leading to an emergency in the supply of normal money. Merchants in need began to strike their own coins from copper, and other base metals. They were cheaply made, and their metallic content was worth far less than their nominal value, hence the name “token money.”

Tokens were issued by shop-keepers, grocers, coffee houses, inns and apothecaries in London and other major cities, and sometimes by civic corporations and town halls. There were thousands of different coins in circulation, and they were commonly accepted and used by the public. Most had a name and visual representation of the issuing business, and an address where the coin could be redeemed.

Tokens were not intended for general circulation; they were used within a circumscribed area by local people who knew and trusted the business who had issued them. Coffee tokens coincided with the emergence of the first coffee houses in London, new meeting places where artists and intellectuals exchanged news, gossip and debated politics.  The 17th century diarist Samuel Pepys passed his time in one of the first coffee houses in Cornhill, where he “found much pleasure in the diversity of company and discourse.”

Copper trade token from Stonyer’s coffee house, London (17th century)

The first wave of English token money came to an end in 1672, when the restored monarch Charles II took control of the money supply again. Some demonetised coins ended up in the New World, transported by migrant Quakers who resold them at face value.

18th Century Token Money and the Industrial Revolution

… if our Governmt will not make a new copper coinage we shall force them to it by coining for our Selves such copper penys

Matthew Boulton, a Birmingham metal-worker

Around 1790, the industrial revolution saw great numbers of workers moving into cities and wage labour for the first time. Industrial leaders needed small change to pay them with, and struck their own copper coins. The practice spread to smaller businesses, and was common again within a few years.

By the late 1790s, coins were being struck for collectors, as well as to advertise the wares of issuing businesses. Issuing coinage had also become a new kind of vanity project. The English radical Thomas Spence issued his tokens through his book-stall in High Holborn. His unpopular ideas, including abolishing the artistocracy, common ownership of land and children’s rights, landed him in prison for High Treason in 1794.

Token money disappeared once again in 1797, when George III gave a royal coinage monopoly to a single token issuer.

19th Century Token Money

The last period of the token money system started for similar reasons in the 19th century – a shortage of low denomination coins. This time coins were not only issued by businesses, but town halls, civic corporations and workhouses, for the relief of the poor. When token money was finally banned by Parliament in 1817, the Bill granted a temporary exception for workhouse tokens from Birmingham and Sheffield. Eliminating them, it recognised,

would be attended wit great Loss to the said Township … and to the Holders thereof, who are for the most part Labourers and Mechanics [factory workers], as with great Inconvenience to the Inhabitants


English merchant tokens

Samuel Pepys Diary December 1660

London Numismatic Club Meeting, 3 October 2006

Seventeenth Century Patent Farthings and Trade Tokens: Introduction

Notes on Digital Money Unconference NY

I was lucky enough to be able to attend the Digital Money Unconference today, held at Google’s office in downtown Manhattan. The event was organised by NYPAY and Consult Hyperion, the latter of which also organise the annual Digital Money Conference (not an unconference) in London. (You can see a 15m presentation on #PunkMoney at that event here.) Here are my notes on the day…


Dave Birch, director of Consult Hyperion and master of ceremonies, began the event with some comments on the coming disruption to payments and money. He drew an interesting historical parallel between now and the mid 17th century in Britain, at the onset of the industrial revolution. At the time, he suggested, most people’s predictions about the future of money would have been wildly off the mark. Instead of better quality coins, a monetary revolution took place: the Bank of England was created in 1694, government debt was monetised, and Bank of England notes began to circulate for the first time as a medium of exchange. In 1696, the Government enacted the Great Recoinage, following Isaac Newton’s advice (the modern day equivalent of putting Stephen Hawking in charge of the Fed.) By 1717 Britain was on a gold standard, and its monetary system was virtually unrecognisable compared to what it had been a few decades earlier. The transition to industrial-era money had been completed.

Dave suggested that we are at a similar juncture in history. Society is transforming itself on a similar scale to what happened in the mid 17th century, and the transformation to money will be profound: ”we’re at the beginning of post-industrial revolution using pre-industrial currency.” It was exciting to hear, and seemed to also be a consensus among conference-goers.

Dave went on to explain a bit about the unconference format. Unconferences allow anybody to suggest topics for discussion, and for people to move around between conversations as they wish. This was done by collecting Post-It notes from everybody, and organising them into themes. There were three sessions with three or four conversations taking place in and around the conference room. I’ve tried this before and it works quite well. The point is that everyone goes to what they are interested in, and can get up and leave if they don’t want to stay (“the law of two feet.”) In my experience unconferences are much more exciting and sometimes lead to serendipitous encounters of the third kind.

David Wolman

The second part of the introduction came from author and Wired journalist David Wolman, who I had met briefly before in London. His book entitled The End of Money is now a bestseller, which says something about the growing interest in the topic. He read some passages from it, which contained some nice anecdotes about money and his encounters with some colourful characters.

David’s first excerpt was about Marco Polo, who was one of the first Westerners to witness early fiat money, in 13th Century China. Marco Polo was apparently amazed by the “alchemy” of paper money issued by Government decree. Paper promises, made from Mulberry trees, were redeemable for coinage from the Government; their acceptance was enforced under penalty of death. The availability of a national currency exponentially increased opportunities for trade, and lead to a period of massive wealth and prosperity. The Chinese Emperor boldly decreed the notes valid “for all eternity.”

This contrasted with the view of Mervyn King, Governor of the Bank of England. David related some recent comments by King, in which he said that the perceived value of paper money depended on people’s trust in institutions. It is essentially confidence in institutions which currently keeps money and the economy from collapsing – the acceptance of money depends entirely on the belief that it has value. Once confidence goes, the consequences for society would be calamitous. King’s job is to reassure us that the Emperor still has his clothes on.

Finally, David shared an anecdote about meeting up with an Icelandic coin collector, whose collection included a 1969 10p coin from Ireland, issued by the UVF (Ulster Volunteer Force) – essentially defaced coinage designed to protest Republicanism. Physical money, though it may be becoming obsolete, continues to have an “unusual power,” with its cultural and political resonances.

Audience questions

There were some questions for David Wolman at this point, with Dave Birch joining in for some of the answers.

Before beginning, David said that entering into this topic was like “stepping onto the hornet’s nest,” as he had been the bout of some vitriol online. Dave Birch asked him to explain more about why digital money was seen to be threatening, especially in the US. David’s answer was that physical cash was closely associated with the right to privacy in the US (mistakenly believed to be a right to anonymity, which is never mentioned in the constitution.) Digital money is viewed as possibly paving the road to eliminating the privacy of cash, and allowing the prying eyes of the state into people’s private lives. Another factor are the many conspiracy theories about how the elimination of cash is part of a masterplan to create a single world currency. Dave Birch remarked that given the current problems with the Euro, such a project would likely never work anyway.

Another audience member touched on the fact that her parents had grown up in the depression, and were unlikely to trust anything except physical money as a result. It would be hard to convince many people, particularly from this generation, that digital money was safe. Dave Birch commented that this was a “cruel trick,” as people who hold physical cash pay higher transaction costs, owing to inflation and risk of theft. David Wolman called people who love physical cash a member of the “tactillians,” the same people who prefer physical books to eBooks. The decline of physical money is in fact part of a wider digitisation of objects, and a threat for tactillians in general. While not necessarily a rational prejudice, I also count myself as a bit of a tactillian – there is something reassuring about the physical contact with an object.

A question about government power over the money supply led David to point out that he would have liked to have written a whole chapter on Bitcoin, the peer-to-peer cyrpto-currency which is still around, despite a chorus of predictions that it would fail. Another audience member said that Americans simply had a passion for physical currency, and this was partly based on the possibility of “self reinvention,” as was the case with criminals who went West to create new identities and livelihoods for themselves with their ill-gotten cash. David Wolman however concluded that physical cash was old-fashioned technology, and would eventually become obsolete, regardless of cultural or political attachments to it.

Open Spaces

The open spaces then followed. I attended three sessions, so I can only give a partial account of the rest of the day.


The first session I attended was about Bitcoin (or ‘Bitcoin Bitcoin Bitcoin!’ as someone had written on a Post-It note.) The first thing that was surprising was the number of people sitting at the table: about 10-15 if I remember correctly, including journalists, people working in banks, consultants and other professional people. A couple of years ago this would have been very odd indeed, now Bitcoin seems to be accepted by the mainstream at least as an idea.

The Bitcoin discussion veered in different directions, and wasn’t the most focused. A common objection was made that Bitcoin would never be able to replace the US Dollar (or other political currency) as a “dominant currency.” David Wolman pointed out that Bitcoin could simply be one part of a rainbow of currencies, and didn’t need to become dominant to be successful. This view seems correct to me: it’s an anachronism of Industrial-era thinking that any single currency has to be the “dominant one,” and replace what went before it.

It was noted that Bitcoin is not completely anonymous, because transactions can always be traced in the public block chain. It is however possible to protect your identity by keeping it separate from your Bitcoin address, as well as using various mixing services to scramble payments through multiple nodes in the network.  An interesting discussion followed about privacy, and why it was a desirable feature of Bitcoin. One person said they didn’t care what the government or credit card companies knew about them. Another Bitcoin advocate suggested buying bacon in a community where it was forbidden could be a good use of Bitcoin. Perhaps another example of why privacy matters could be concealing political donations in a politically repressive country. To me, the most important point was that Bitcoin offers a degree of privacy as a feature, and some users think that makes it worth using.

Somebody else noted that it was incredibly hard to produce a fake Bitcoin (you would need more processing power that the fastest supercomputer on the planet.) Would it be possible, they asked, to apply this same counterfeiting technology to the US dollar? Jon Matonis – a libertarian Bitcoin guru – saw this comment on Twitter and amusingly compared it to “copyright offices hosting torrents.” Apart from this, there was some discussion about how to incentivise adoption, with some people thinking it was necessary to push merchant adoption first, and others consumer adoption. Someone mentioned the wildcat era of US Banking, and that counterfeiting had been the reason for its collapse — it seemed that Bitcoin at least solved this problem, and so has a greater chance of sticking around. The case for Bitcoin was also stronger in the developing world, where payment infrastructure is lacking.

The three main issues faced by Bitcoin are likely to be momentum (how to achieve it?,) making it convenient to use (perhaps with solutions like Bitcoin prepaid card BitInstant,) and trust. There have been numerous trust issues since the currency started, including cloud wallet providers running off with people’s money, or getting hacked.

What to do in the case of a Tsunami?

I thought this would be a popular open space, but only two people showed up to it. The main question here was: what happens to digital money when some catastrophic event causes a power failure, or an internet outage. In sum, the robustness of digital money seems to be an issue: unlike seashells or bank notes, it needs infrastructure to work.

We looked at MintChip, a Canadian Government project to create a digital wallet container allowing peer-to-peer transfers, as well as a cloud wallet. (See Jon Matonis’s takedown here.) My view of MintChip is that it was quite an interesting attempt at making a digital money solution which could actually be adopted: it supports transactions in Canadian dollars (and other currencies,) integrates with mobile and is platform independent. (There are some apps which have been designed for MintChip viewable here.) If a Tsunami hit where you were living, it would be better to have MintChip than Bitcoin, since transactions can be performed without needing access to the network for verification.

In summary, we found that the ability of a digital money system to work offline was an important feature, and that there were different levels of robustness to consider. We also thought the distinction between an electronic transaction and electronic money is important to maintain: electronic money could still be used offline, if it is contained in a storage device which can be verified, like a Micro SD card.

Path to Cashless Society

The Third open space session I attended was on the likely path to a cashless society. By “cashless,” I assumed the title of the session referred to physical cash. For this session we were asked to produce a narrative summary at the end, rather than a set of bullet points.

One thing we agreed is that the path to a cashless society is likely to be different depending on where you live. In Kenya, where most people are unbanked and there is a risk of being killed while transporting large amounts of cash, the value of mobile payments is obvious (the M-Pesa private mobile currency is huge there.) What’s more, it doesn’t seem to matter if developing countries skip over some intermediary steps (like having ATM machines,) and go straight to the cutting edge of payments.

In a more economically developed country like the UK, the path to cashlessness is likely to be different. Successful innovations will answer consumer needs, while being future-proof and platform independent. A good example of this is the Oyster card, a magnetic card used to pay for journeys on London’s transport network. While Oyster is currently used to pay for journeys, the system has the potential to become an “open loop”, integrating shops and service providers. Since the card already exists, and the behaviour pattern of tapping to pay is already established, this could happen quite easily. It is in fact already the case in Hong Kong, which has the highly useful Octypus card.

The bigger question to me was not finding more convenient ways to pay for things with existing money (although I’m not indifferent to it,) but the possibility that technology might lead to new, more radical forms of money created in peer-to-peer networks, rather than by Governments or banks. This would be a major disruption on the path to a cashless future, and would probably lead to Government attempts to stop it, as they lose control of the money supply (a likely futile exercise described by one person as like playing whack-a-mole with currencies.) In summary, it seemed that if this ever happens, there will be a power struggle with vested interests who won’t like it.


It was a good event, and the unconference format worked well. I got to talk to a variety of people with different backgrounds (bankers, entrepreneurs, teachers) and the general consensus seemed to be that something big and disruptive was coming, and the banks aren’t prepared for it. I think Dave Birch is correct that we are like the 17th century commentators who cannot anticipate the effect technology will have on money, even if it is useful (and fun) to speculate. Thanks to Dave Birch, Consult Hyperion and NYPay for hosting this.

Proposal for a Karmic Currency

Anything which alters its environment to increase production of itself is playing the game of increasing returns. – Kevin Kelly, Out of Control

I’ve been thinking for a while about introducing a currency into #PunkMoney, which would make it possible to account for value created between its users. Such a currency could, in theory, do a lot to help #PunkMoney scale, by encouraging participation through a positive feedback loop. After some weeks of thinking, I came up with a tentative solution which I’d like to develop here.

First of all, some groundwork. I’d like this currency to adhere to certain principles – explored elsewhere on this blog:

  • It must be tied to a social gesture

Like a +1 vote or a retweet, it will be created through a simple and effortless social gesture. In #PunkMoney terms, this is likely to be a thanks tweet created ad hoc, or in reply to a specific promise. [1]

  • It must be asymmetric, and therefore, abundance-based.

There should be no material cost associated with creating and awarding this currency to another user in the network. Its creation will not entail any further obligation or commitment from the issuer. [2]

  • It must be karmic

By ‘karmic’, I mean the principle of increasing returns. Receiving this currency will make it more likely that you will, in turn, receive value back from other users. In this way, the currency will enable effort, attention and resources to flow to the people according to merit, as determined by the network’s users.

  • It must be un-gameable

It should be impossible or impractical for any conspiring group to artificially award each other this currency, and divert the network’s value to themselves as a result.

  • It must support gradients of value

It should be possible to award the currency conveniently in different amounts to different users, based on the perceived value they have delivered.

It might seem like I have defined a wish list for something so perfect it could not exist. Certainly, if this problem were to be approached from a narrow monetary perspective, it would be completely intractable. There is no way money could be created by a user without an obligation or commitment backing it. I am however using ‘currency’ in a broader sense, to describe a trusted symbol in a network which acknowledges and shapes the flow of value through it. [3]

The approach I’ll develop uses some simple secondary school maths. It’s meant to outline the bare structure of a system which could work. No doubt a mathematician with a grasp of network theory could devise a more refined version of what follows. (If you are one, I’d be grateful for some feedback.)

Thanks as social gesture

As mentioned, the basic gesture which we will use to create this currency will be a #PunkMoney thanks tweet. The ‘thank you’ note can be created in two ways: by replying to a promise with

@someone thanks #punkmoney

or by creating a new tweet from scratch, for example

@someone thanks for the beer #punkmoney

This new functionality has already been added to the tracker, so this building block is already in place. In the proposal that follows, thanks basically stands for any gesture from X to Y which constitutes an acknowledgement of value created by Y. We can represent this as an edge between two nodes:

X -> Y

The approach will in fact be agnostic to the type of gesture used, as long as it means the same. All my examples will rely on the #PunkMoney thank you gesture as this is the context the currency is being defined for.


A naive approach would be to simply count the number of thanks a person received over a given time period, and represent this as a karma score. The basic problem with this is that it is trivial to game: just tweet someone a lot of thanks to inflate their score.

The solution is to take a perspectival approach. [4] According to this way of looking at things, no user in the network has an intrinsic score or balance which is the same to all other users. Instead, Y’s karma will look different depending on where you stand in relation to Y in the #PunkMoney network.

Let’s assume the following graph of A’s basic network. We arbitrarily normalise A’s karma to 100, representing the total amount of karma which will be shared out to users as A sends thanks to others.

In this thanks graph, we can calculate a perspectival karma score for every user from A‘s point of view, using some simple maths. Since A has sent two thanks, each of them is worth 50% of his starting balance of 100. As a result, A will see B and C‘s karma as 50 respectively (50% of 100.) Since B has thanked D and E, their karma will be equal to the product of the ratios (times 100) down the branch to either user. We also want karma to decay with distance, so that after a certain number of hops through a branch it fades out, rather than continues indefinitely. To achieve this, we can divide the ratio for each hop by its distance from the origin of the calculation, A.

In this case, D’s karma from A’s perspective can be calculated as follows,

KA->D = (1 x KA->B) x (1/2 x KB->D) x 100

= (1 x 50%) x (1/2 x 50%) x 100

= 12.5

E’s karma from A’s perspective:

KA->E = (1 x KA->B) x (1/2 x KB->E)

= (1 x 50%) x (1/2 x 50%) x 100

= 12.5

Finally, F will have a karma score equivalent to:

KA->F = (1 x KA->B) x (1/2 x KB->F)

= (1 x 50%) x (1/2 x 100%) x 100

= 25

The defence against gaming is the subjectivity of a perspectival score. The karma a user has depends on the person who is looking at them, and their relationship to them. If a group of conspirators decided to award each other a lot of karma, they would form a closed loop. No other users would be connected to them, and hence, each conspirator’s karma would appear as zero to the rest of the network.

A different gaming strategy would be to first try and earn some thanks from other users in the network, and then to start artificially inflating the karma supply to some co-conspirators. On closer inspection, though, this is impossible because the supply of karma cannot be inflated: the more thanks a user create, the less karma each one confers. A user who wants to game the system could never give away more karma than they have in fact earned. Another way to put this is that total karma received is always equal or greater than karma awarded [5]:

kin <= kout


At the beginning of the post, I defined one of the principles this currency must adhere to as that of increasing returns. Receiving karma should make it more likely (in a non-trivial sense) that other users will want to provide value to them. Perhaps this value provision will take the form of fulfilling specific requests, or sending them new promises for things they might need.

To achieve this, we need the value of a person’s thanks to be proportional to the amount of karma they have. We’ve established that from A‘s perspective, F is the user with the highest karma score (50.) If our currency is karmic, and deserves to be called karma, it must be the case that when F thanks someone, it’s worth more to their karma score than when D or E (with 25 each) do.

This definition presents some issues. First of all, karma is perspectival, rather than an intrinsic property of a user. So a statement such as “F‘s thanks is worth more than E‘s thanks” needs to be qualified accordingly. There is no objective sense in which F‘s and E‘s thanks are worth anything: it’s only from the point of view of users connected to either F or E that those gestures mean something. However, to make sense of this statement we need a neutral way of comparing the value of F and E‘s thanks. We can do this by assuming a neutral observer O, who is connected to both F and E in the same way.

Let’s add O to the graph in relation to F:

In this graph, the theoretical user O (he doesn’t actually need to exist to make this point) can be connected to both F and E in exactly the same way: via a single thanks from either F and E, to him. That is, from A‘s point of view, the only factor which could create a difference in O‘s karma would be F and E‘s relationship to A, not to O.

Clearly, F‘s thanks to O is worth more to O than E‘s, from the perspective of A. Assuming F thanked OO‘s karma from A‘s perspective is calculated as follows:

KA->O = (1 x KA->C) x (1/2 x KC->F) x (1/3 x KF->O) x 100

= (1 x 50%) x (1/2 x 100%) x (1/3 x 100%) x 100

= 8.25

In comparison, if E thanked O instead, his karma from A‘s perspective would be lower:

KA->O = (1 x KA->B) x (1/2 x KB->E) x (1/3 x KE->O) x 100

= (1 x 50%) x (1/2 x 50%) x (1/3 x 100%) x 100

= 4.12

In other words, from the perspective of a neutral observer, it would be better to receive a thanks from F, in order to win favour with A, than it would E. This is significant because it establishes that this currency is karmic: due to F‘s better position than E, his thank you has more value. It’s more likely that O will want to help F, as a result of his relationship to A, all else being equal. Value flows according to merit.

Weighted thanks

The final constraint we defined for this currency was the ability to express gradients of value. I’d like to be able to send a thanks to person A for putting me up in their home for a night worth a hundred times the thanks I’ll send B for retweeting my blog post. This is also no problem given the definition outlined above.

In practical terms, instead of requiring a #PunkMoney user to send a hundred thank you tweets, we’ll allow them to add a number to the thank you note, for example:

“@someone thanks for putting me up +50 #punkmoney”

Now all we have to do is divide up the user’s karma proportionately. A single thanks will be worth 1/50th of this one. The total value will be equal to 100. Assuming two thanks, where one is worth 1/50th of the other, we simply adjust the ratios accordingly:

KA->C = 50 x KA->B
KA->B + KA->C = 100

50 x KA->B + KA->B = 100

KA->B = 100/51 = 1.96
KA->C = 100 – 1.96 = 98.04

Plugging these weighted ratios into the graph will allow us to take into account that A intended his thanks to B to be worth a great deal more, and to cause a greater impact on his karma score.


This defines the basic approach. As I mentioned before, it’s a bare structure which could probably be significantly improved upon, assuming its logic is sound. I’ve deliberately left out factors like time-decay, how to represent a user’s karma back to them, and the computational cost of calculating karma in a large, densely connected network. I’ll hopefully address those in a second post. In the meantime, I’d be grateful for feedback.

To summarise: the basic idea is to introduce a peer-to-peer accounting mechanism which is debt and commitment-free, but which helps to allocate value in a network efficiently, according to merit. If it worked, it might reasonably replace money in some situations. Karma would not have the full force of a monetary claim: having it only makes it more likely that a value will flow back to a user through incentives, but won’t guarantee it. Still, if it works the implications are good enough for #PunkMoney.


[1] See Splitting the Social Currency Atom for my take on social currencies, and a potential ambiguity in the way the term is used.

[2] The term asymmetric accounting was coined by Gregory Rader, to describe “systems that record and track the provision of value rather than the volume of money transacted.”

[3] See A Broader Definition of Currency for a discussion on expanding the concept of currency beyond money.

[4] First explored in a A Perspectival Trust Metric for Ripple. Thanks to Jordan Greenhall for pointing me in this direction.

[5] This is similar to the approach taken by PieTrust for resisting “reputation inflation.”

Ripple, Bitcoin and Peer-to-Peer Money

How could Bitcoin and Ripple complement each other? Until 1971, the international monetary system relied on a combination of gold reserves and paper money issued by governments. The paper notes were convertible to gold on request, although the rates of conversion varied, and were sometimes suspended. Until the post-war Bretton Woods accord, this system emerged without central design or protector institutions, and saw the lowest period of inflation in British history between the 18th and 19th centuries, and a signficant growth in international trade.

The relationship between Bitcoin and Ripple might be similar. Bitcoin is a special type of commodity money, like gold. A limited quantity of Bitcoins will ever exist – 21 million, of which 8.1 million have already been mined. Like gold, Bitcoin involves no counter-party risk: owning it doesn’t require the bearer to trust another person. Bitcoin transactions are also irreversible and don’t depend on a centralised authority to authorise or remember them. Once the thing, or bits have changed owner, it’s permanent. Bitcoin went through a large speculative bubble–perhaps inevitably–garnered by hype and media attention. Its critics dismiss it as flawed, yet it is still around and, at the time of writing, a Bitcoin is worth six dollars.

Ripple is a different kind of system: a proposal to create a peer-to-peer credit network, in which anyone can create their own money as IOUs, subject to other people’s willingness to accept them. The creation of new money as IOUs is made possible by people’s willingness to believe that the issuer will accept them back in exchange for goods and services at a later date. Alternatively, Ripple users can pay people who don’t explicitly trust their IOUs, by routing payments through a chain of intermediary users who do. If Alice wants to pay Paul, who doesn’t know her, she can still send him an IOU via John, who is trusted by both of them. This idea forms the basis of what could potentially be a digital, peer-to-peer credit system. Rather than merely providing us with a new way of lending old money to each other without banks, Ripple would allow its users to create their own.

Current challenges

At the moment, Bitcoin is entering its third year. It has received generous media attention, however its main users are mostly hardcore hackers and libertarians. It hasn’t yet caught on to the mainstream, for a number of reasons, including usability, scarcity, legal ambiguity and the lack of goods and services currently on offer for Bitcoin. It is interesting to see that despite this, Bitcoin has not yet collapsed. The network has stayed true.

Ripple has not yet successfully scaled beyond the level it needs to in order to become useful as a means of payment, rather than just an IOU tracking tool for friends. Part of the reason is that is suffers from unusual bootstrapping difficulties: its network only becomes really useful after reaching a certain size and density. Before that point, the network effects are not that strong. You might have a number of friends on a Ripple system, but it’s unlikely they’re the kind of people you need to do business with. Yet in order to get big enough to enable impersonal transactions to happen, lots of people need to join it.

Perhaps Bitcoin and Ripple can help each other, much like paper and gold complemented each other in the gold standard arrangements before they collapsed in 1971. However, this time, the technologies can be fundamentally peer-to-peer. A synthesis of Ripple and Bitcoin would create a sophisticated monetary system fully outside the control of any government or corporation. Such a system could provide a stable source of liquidity to people and businesses around the world, without having to rely on the monetary policy of governments, or lending habits of banks.

How exactly might this work?

Bitcoin as reserve currency

The most obvious starting point is to create a peer-to-peer credit network based on genuinely decentralised technology. Much like Bitcoin, such a network would process and record transactions in a totally peer-to-peer manner, without the need for a central book-keeper. However, in the case of Ripple, individuals would be creating their own money as IOUs, rather than mining it. A decentralised design would mean that each node in the network would know about every node it was connected to through a trust relationship. The software would work as a protocol, like email, rather than as a hosted service.

This proposal already exists as the theoretical latter stage of Ripple’s development. However, it’s possible to imagine something further still. It would be interesting if Ripple’s international unit of account became Bitcoin. Self-issued credit currencies in the Middle Ages were often denominated in gold or silver bullion. Most of the time, notes were redeemed in an equivalent amount of goods or services, as gold and silver were hoarded in temples and monasteries. The metals were used to periodically settle accounts, particularly large ones. The gold standard which followed later allowed international trade to take place thanks to a similar principle: currencies were pegged to a quantity of gold, but were often redeemed in goods and services. Gold only changed hands when deficits needed to be settled between countries. This, in turn, imposed discipline to keep control of their balance of payments, lest they run out of gold.

A similar option might be available to a decentralised Ripple network. Users could hold bitcoins in ‘reserve’ accounts, with the ratio of credit issued to bitcoins held exposed to other users of the network. Such transparency would allow everyone to see how leveraged any given user was. People would accept credit from other members who didn’t necessarily produce anything they wanted, because they would be able to convert credit into Bitcoin on request. Bitcoin would provide a level of security and confidence in the credit system. Such a set up seems to have worked for gold and paper for centuries.

There is nothing wrong with users extending credit in excess of their Bitcoin reserves: credit is denominated in Bitcoin, but redeemable in all kinds of goods and services, as well as Bitcoin, if necessary. What matters is that users have confidence in each other’s credit, whether they intend to redeem it for Bitcoin or not. With the ability to create credit denominated and backed by Bitcoin, users are no longer artificially limited by its supply. Credit can expand and contract according to confidence, but still stay within credible limits.

Transparent reputation

The last ingredient to this hybrid model is a trust metric, which would allow users to share information about their confidence in users with their neighbours. In the informal gift economy, the checks and balances of reputation accounting ensure that free-riders are eventually outed, while people who do their fair share (or more) win trust and respect. Similarly, a good trust metric will make credit-worthy users well regarded, further extending their ability to create money. People who don’t honour their promises should see their trust ratings drop, discouraging others in the network from accepting their credit.

In principle, this is how many trust measurement systems work: on eBay, judgements of individuals about a person’s trustworthiness are aggregated into points. This rating system makes eBay work: it gives people who don’t know each other sufficient reason to engage in time-delayed transactions, where fraud would otherwise be easy to get away with. Reputation currencies create confidence.

However, an eBay-ratings model would almost certainly be gamed in a monetary system (and already is to an extent on eBay). How do you design a trust measurement system that can’t be? It sounds like an unlikely task, but ideas about how it can be achieved exist.

With a Bayesian approach, trust can be measured perspectivally. If Alice trusts Bob, and Bob trusts Jane, Alice is more likely to trust Jane as well, though perhaps not as much. This dynamic is already at work informally in social networks. Jane has no intrinsic trust score floating above her head; rather, different people will trust her to different degrees, depending on their relationship to her. A Ripple trust metric can work in the same way.

When people connect on Ripple, they declare a trust relationship which is quantifiable, because it is expressed in terms of credit limits. If Jane trusts Bob with 50 BTC and Adam with 25 BTC, it’s possible to infer that she trusts Bob’s credit twice as much as Adam, and so on. These decision can then be used to weight calculations about who Jane can trust, based on who Bob or Adam trusts. A perspectival trust metric, as I’ve argued in this post, might be the missing ingredient which helps Ripple to scale beyond personal trust relationships, as it needs to.

Could it happen?

Perhaps the way money has worked in the past–as a combination of commodity and promise–is the key to creating a successful monetary system. A Bitcoin-Ripple mash-up would combine the scarcity of Bitcoin with the power of credit creation. All the technology to build such a hybrid model already exists, after all, so it is perhaps only a matter of time until someone creates it.

Related posts


Philip Coggan, Paper Promises (2011), ch.3 “Going for Gold”

Self-Issued Credit in the Middle Ages

In the Middle Ages, Roman bullion money ended up hoarded inside churches and monasteries, leading to a shortage of money in circulation. This led to the creation of new, improvised forms of paper money, issued by the people rather than their rulers. Esoteric types of credit money, such as ‘tea checks, noodle checks, bamboo tallies, wine tallies’ emerged China [1]. In England, money was issued by ‘shopkeepers, tradesmen and even widows who did odd jobs.’ [2] All over the world, money took on unprecedented forms as credit tokens issued by peers in relationships of trust, or ‘self-issued credit.’ In Europe, such forms of money were often denominated in Carolingian money, but did not rely on it as a basis for issuance.

Self-issued credit may have been widespread in the Middle Ages, but the history of money seems to be denominated by bullion. This is partly because objects like paper notes and tally sticks don’t survive as well as coins do, even though they may have been used a lot more at a given time in history. Traditionally, money is conceived of as something created by monarchs, or their central banks, and not by people. However, today we face cash problems which are similar to those at the onset of the Middle Ages in Europe: money is becoming scarce again, as banks are contracting, leaving people who are able and willing to earn a living without the means to pay for it. Perhaps we can learn some lessons from the abundant self-issued credit of the medieval era.

What is self-issued credit?

First of all, what is self-issued credit precisely? It could be defined as a recorded promise to deliver an equivalent amount of goods or services to the bearer of the note. Such a promise would usually come with an expiry date, which limits the issuer liability in case of non-redemption over an extended period. Here’s an example: a “labour note” issued in the 19th Century: [3]

Notes would typically be denominated in a unit of account: in this example, three hours’ labour “in Carpenter’s Work” from Joseph Peters. This particular note is non-transferable, however most notes would be. Usually, the community of people who are willing to trust the issuer to make good on their promise defines the boundaries of circulation. A typical medieval market would involve trading with notes issued by bakers, butchers and farmers. Promises issued from one source could circulate through many pairs of hands before returning to their issuer for redemption, providing a supply of money even for people who didn’t intend to redeem them. As confidence begets confidence, self-issued credit becomes money.

From this description, it’s obvious that money like this is heavily dependent on trust between individuals. The credibility of a given producer literally determines their access to money. This creates a virtuous feedback loop in the system: people who don’t redeem their promises loose credibility, and their money starts to trade at a discount, or not at all, as other people factor in the risk of accepting it. On the other hand, issuers who are honourable benefit from the fact that people who don’t necessarily want to buy their produce will accept their cash, because it is highly trusted. It’s these dynamics which regulate the supply of self-issued credit – the amount of money a person can create depends on people’s faith in their promises, and vice versa. [4]

The advantages

From the above description, self-issued credit might sound like a risky idea. This is true, insofar as relying on promises – even State-backed ones – always involves an element of risk. What is interesting about this particular type of money is that the risks are transparent and distributed: people issue their own money, which they’re responsible for redeeming. The bearer would probably not have legal recourse if something went wrong. In fact, in the medieval Islamic trade routes, disputes over self-issued credit notes could only be referred to voluntary courts mediated by merchant guilds or civic associations. The courts’ ability to impact a merchant’s credibility, and hence their access to credit, was their main source of power. [5]

The greater risk transparency means that there is less moral hazard in the monetary system: people who accept self-issued credit are aware of the risks that they are taking in doing so, and bear the consequences if something goes wrong. In the case of a national money supply, bad debts lead to monetary crises which affect everybody who uses the currency. Similarly, in a mutual credit system, money issued by people who don’t keep their promises creates problems for everybody else using the system, as it exists as a collective liability, rather than a personal one. Self-issued credit systems, by contrast, create resilience through diversity.

Another benefit of accepting greater risk is liquidity. Unlike forms of money which originate from hierarchical institutions like commercial banks, or government mints, self-issued credit is never in short supply relative to need. As long as people are able to produce things, and convince other people to accept their promises to deliver them as payment, money can be created. The ability to produce, and trust within a community, are the determinants of the money supply, rather than the other way around. Douglas Rushkoff recently coined the phrase “radical abundance” to describe this tendency in medieval monetary systems. [6]

As well as risk transparency, and abundant liquidity, we could also add to the list that self-issued credit is not debt-based, like other proposals to replace the financial system are. Specifically, transactions do not necessarily create debts, they create potential liabilities. The difference might appear semantic, but isn’t. Debts are exchanges which aren’t yet brought to completion, and which linger on when not completed. We are naturally averse to going into debt to people we have close relationships to for good reasons: they change the balance of power within relationships, and potentially undermine them. In a centralised financial system, the banks act as mediators between borrowers and lenders, absorbing the bad Karma of debt-ridden relationships. In mutual credit, debt can also be a problem if it is left hanging, without possibility of escape, because nobody wants to buy anything from the debtor.

A self-issued credit note creates a different type of relationship. A note issued is a potential liability, because a promise to deliver something only has to be redeemed if the bearer wants it to be. If they don’t, there is no feeling of an incomplete transaction hanging over the relationship, as there would be in an accounting system. Expiry dates also allow issuers to limit the extent of their exposure, creating a safety against accumulating potential debts. Another significant factor is the narrative associated with self-issued credit. Issuers feel like they are creating a unit of money, rather than accumulating debts. This, in turn, encourages participation among producers.

What is to be done?

Recent research has led me to the conclusion that self-issued credit is a really powerful invention, which seems particularly well suited to a networked era. It’s money that arises from relationships between peers, and which depends on trust, rather than state coercion of fear of destitution. It transcends the corrosive logic of debt, and it also works particularly well for communities. Another appealing aspect is the simplicity of such systems: ancient technologies like paper, seals and ink were sufficient to create credit notes, and should be again today. What has worked well in the past might prove very useful now, particularly with the help of modern technology. [7] Something to explore in more depth in a future post.

Read more:


[1] David Graeber, Debt, p. 270. During the Song Dynasty (960-1279 AD,) in periods of financial collapse, people resorted to ‘tea checks, noodle checks, bamboo tallies, wine tallies, etc.’ Graeber also notes these forms of popular money resembled the ‘token’ money seen in Europe in the Middle Ages.

[2] David Graeber, Note worthy: what is the meaning of money?, Guardian

[3] The example labour note is from Wikedia’s article on barter. Self-issued credit as well as mutual credit can sometimes be referred to as barter, in the sense that the goods promised are being bartered in the future for goods received now. This is also called ‘virtual barter.’

[4] Paul Grignon’s animated video The Essence of Money: A Medieval Tale gives a good account of the mechanics of self-issued credit in medieval European market fairs.

[5] David Graeber, Debt, p. 276.

[6] This phrase comes from a talk called Radical Abundance given by Douglas Rushkoff in 2009, in which he describes the abundance-based grain-backed currencies of the European Middle Ages.

[7] Mark Frazier has written several interesting proposals for how personal currencies might be implemented using modern technology.

GiftPunk: A Twitter Tool for Giftcasting

Recently I’ve been thinking about communities, and how to build them. Communities are in some sense defined by the flow of gifts, rather than market-based transactions. Perhaps the kinds of behaviour encouraged by the market is one of the reasons communities have been in decline in recent history. As one person put it to me recently, “community building is a truly 21st century problem.”

If gifts define community, it might be because they encourage feelings of generosity and gratitude, and hence bonds of kinship. It may also have something to do with the fact that the informal gift economy presupposes an ongoing relationship. If I give you a sack of potatoes, I have a vested interest in our continued relationship, while I wait for you to reciprocate. According to anthropologist David Graeber, this explains why, historically, many communities deliberately avoid reciprocating with gifts of precisely equal value. [1]

After experimenting with #PunkMoney, a promise currency based on Twitter, I’ve been exploring how Twitter can be adapted and repurposed to do new, unexpected things. Recently the two ideas of community building through gifts, and the simplicity of defining conventions on top of the Twitter API, came together in the shape of GiftPunk – a simple tool for communities to broadcast needs and offers.

How it works

A community sets up a central account, for example @OccupyLondonGifts. The account can be private or public. Whoever follows it has the right to post needs and offers to it, which then appear in the main stream of the account.

For example, if Alice wanted to offer legal advice, she could tweet:

@OccupyLondonGifts I offer an hour of legal advice.

– Alice

GiftPunk can find Alice’s tweet, interpret it and tweet through the community account:

[Offer] @Alice offers one hour of legal advice

– @OccupyLondonGifts

Everyone who follows @OccupyLondonGifts can see Alice’s offer, and take advantage of it if they want to. In the same way, you could tweet your needs. Say Bob needs some help:

@OccupyLondonGifts I need help cleaning the kitchen tent.

– Bob

GiftPunk then finds and re tweets this as:

[Need] @Bob needs help cleaning the kitchen tent.

– @OccupyLondonGifts

You can also easily take down offers and needs from the community stream, by replying to the tweet with “@OccupyLondonGifts close.” Otherwise, they expire on their own within a week.

The nice thing about using Twitter to do this is that it’s very accessible and simple to use. You can use Twitter from a mobile phone. Since it’s easy to add and remove messages, GiftPunk becomes a live stream of your communities needs and offers. This makes it easier to identify where gifts can flow, and to make it happen.

Gratitude currency

The next step for GiftPunk is to add in a gratitude currency, which can be used to help people build a reputation around their capacities. If you are a good legal counsellor, or a good baker, it would be useful if others could record their gratitude to you for those things in a way which helped you to build lasting social capital within and beyond the community.

Twitter makes doing this very easy. Like many other Twitter based gratitude currencies [2], we can easily define a ‘thanks’ syntax, like this:

@OccupyLondonGifts thanks @Harry for the marmalade

– @Sally

GiftPunk will find and record the thank you messages, and the action they relate to if one is given. This data can be aggregated, so I can see how many times different members have been thanked, by whom and for what. It would be useful for all members of the community, as well as the people it describes. If I want to find someone who is good at legal counselling, it will tell me that Alice is probably a safer bet than Harry, even though he makes good marmalade.

The data collected in this way could in turn be displayed on a web page for the community to see, or be made available through an API so that other services can use it. Alternatively, I’ve been pondering how it might be possible to automatically spawn Twitter lists with different ranks, and move users through them as they accumulate gratitude, subject to some kind of time decay.

Try it out

I’ve set up a version of GiftPunk under the Twitter name @GiftPunk. It uses all the conventions described in this post. There have already been a few offers (programming lessons, beta testing and guitar lessons.) To try it out first follow the account and then tweet. It takes on average 30 seconds for your tweet to be found and processed.

If you’re curious, the code is also on GitHub, here.

[1] “The Myth of Barter” in Debt: The First 5000 Years by David Graeber

[2] See Twollars as an example of a Twitter-based gratitude currency

Read more

#PunkMoney: How to Print Money on Twitter

NB: For a more up to date post on #PunkMoney, go here.

In the Middle Ages, producers created their own money as a promise to deliver goods and services in the future, and spent it with people who trusted them. The promisee, who became the bearer of a new credit note, could transfer it to a third party as payment, by signing it on the back. If a note ever came back to the issuer, it would be redeemed for whatever it was a promise for. Personal currencies were effective forms of trust-based local money when bullion was in short supply.

Today, as we face another shortage of sovereign money, why not revive the old practice with new technology? Credit money can be created by anyone with something to produce, and some trust that they can deliver it. Twitter is in fact an ideal platform for this: it offers a public record, its format is brief, it is a social network, and it has some handy syntax to do everything we need.

So here’s a proposal on how to literally print money with Twitter, called #PunkMoney. You can be the Ben Bernank, and Wall Street can be punked – it’s easy…

To make #PunkMoney work best, I’ve put together a set of minimal rules for money issuance, transfer and redemption. They are just conventions, but offer consistency which can help to create trust. You can create #PunkMoney for an hour of French tuition, a cup of coffee, a banquet of Pizza, ten ounces of gold… whatever you want. You can send it all over the world at no cost, too.

My suggestion is to make promises you feel you can actually keep, as this makes it all much more fun for everyone else. Every time someone has a good experience with #PunkMoney, it builds trust in the meme and helps it grow. Consider it a collaborative experiment in open money.

Print money

To create new money, just tweet it into existence as a promise to somebody. I suggest the following phrasing:

@someone I promise to pay you, on demand, [Insert whatever you promise here]

@someone is the person you’re issuing this credit note to, and who will become the bearer. They will have the right to transfer or redeem the note, but more on that in a minute.

You might want to add some details, like an expiry date

Expires in X days/months/years

By convention, we’ll assume #PunkMoney is transferable. If you don’t want this to be the case, add

Non-Transferable, or NT

If you’d like your credit note to be transferable subject to your approval, use


This is especially handy if the promise is for something more personal, like a meal or a night on your couch.

Finally, hashtag your tweet with #PunkMoney. That shows you’re following #PunkMoney rules. Here’s some I printed earlier:

@someone I promise to pay you, on demand, one cold pint of beer. Expires in 60 days. TSA #PunkMoney

Transfer money

Let’s say you’ve received some PunkMoney from someone. What can you do with it? You might want to spend it as money yourself, by transferring it to a third person as payment, or a gift. If that’s the case, reply to the original message with

@issuer Please transfer this to @someoneelse

Since the replies are shown alongside the original tweet, you’ve publicly signed the credit note over to the new person. The new bearer now has the right to transfer or redeem…

Redeem money

If you want to cash in the promise someone has made you, rather than continue to hold it or transfer it, you can reply to the original tweet with

@issuer Please redeem

You might then want to follow up by DM to arrange the details. When you’re satisfied the issuer has made good on the note, you can close the note off with

@issuer Thanks for the [value delivered]

Record your trust

If you had a good experience, you can make a public gesture to record your trust in the issuer. Simply create your own list called PunkMoney-trusted and add them to it. That way other people can see who you trust, as well as who trusts anyone else. It creates some social currency for them, and is also nice way of saying thanks.

That’s all

PunkMoney is an experiment in popular money printing. It may seem crude – but that’s because there isn’t really much to a monetary system in the first place. Money is created and accepted as payment through trust. Technologies as simple as paper and pencil have been enough to create it in the past, so why not Twitter?

Now, if you enjoyed this post, punk some money my way.

What should Peer-to-Peer Money be?

Thinking about debt outside the twin intellectual straitjackets of state and market opens up exciting possibilities. For instance, we can ask: in a society in which that foundation of violence had finally been yanked away, what exactly would free men and women owe each other? What sort of promises and commitments should they make to each other?
This post is more about principles than detail; though I intend to follow up with more information about Pebble, a project I am collaborating on to create money around trust, soon. The idea is to use this post to define what I think is the most pressing question in the future of money debate: how to create genuine, decentralised and abundance-based peer-to-peer money. If that sounds like a mouthful, bear with me, as I try to try to convince you that it’s the shape of things to come…
Money matters
First of all, a detour. Why this discussion about money? There is a great deal of interesting thinking going on about the nature of money itself, and how that might be changing. Money, some believe, is not value-neutral but makes us think about the world through the lens of scarcity and materialism. There is also the debate surrounding social currencies, which attempt to measure and represent previously invisible forms of value, such as trust and reputation. These currencies have proven instrumental in creating trust between strangers, lubricating online collaborations, and allowing peer-to-peer “collaborative consumption” to take off. No doubt there will be much more to say about these fascinating inventions still.
However, I want to look at a different question, which I think is fundamental to the future of money. While I’m sure that the role of money is changing as new types of currency, forms of exchange, and a different values emerge, I still believe that money is, in principle, here to stay. By money I mean the thing we use to store savings, measure the value of scarce goods, and transact with. As a technology money is as old as the hills. It was never invented at a precise moment in time, and unlike Economics text books would have us believe, is probably as old as numbers, writing, cooking and clothing. It answers a fundamental need in human life which I do not think is about to go away.
Given this, I can return to peer-to-peer money. What is it, and why is it so important? Without going into the details of specific proposals to create it, I want have a go at defining the criteria according to which any such project should be judged. Consider this an attempt to set the groundwork for discussions to come…
1. Decentralised
Peer-to-peer money should be radically decentralised. By this I mean that nobody should have full control over how it is created, by who, and for what purposes. Any serious peer-to-peer money proposal should show how these tasks are delegated to the nodes of a network. The banking system, as should be obvious, is not such a network: the task of creating money as debt is performed by banks, who do so according to their own commercial interests, with some influence from central banks. Clearly this is undemocratic: the amount of money which gets created, and the projects and people who are deemed “creditworthy,” are controlled by de facto central planners, who have their own interest to look after. What’s more, these decision makers have very inadequate information for the task they have undertaken – a classic Hayekian argument against centralised allocation of resources.
It follows that, in an ideal scenario for peer-to-peer money, such decisions should be pushed out to the edges, to take advantage of local intelligence. The amount of money that gets created should be based on decisions undertaken by people, using their shared knowledge and mutual trust as a basic principle. If this is the political meaning of “decentralisation,” there is a further technological one to make. The kind of software which should underpin genuinely peer-to-peer money should itself be peer-to-peer. Any monetary system which depends on a central coordinator to take care of verifying payments and keeping records of transactions has a single point of failure. It will be vulnerable to rogue administrators, cyber attacks, and will create administrative overhead. In a digital, networked environment, serious peer-to-peer money should become a protocol, like email or HTTP, which can be used as a matter of convention. It should be part of the backbone of the internet, controlled by nobody and existing by free consensus.
You may be thinking that what I’ve described already exists, in the form of Bitcoin. Bitcoin is indeed a fascinating project for anyone interested in the future of money. It is decentralised, and delegates the tasks of running the currency to its network, without any central control. To date, it has never been successfully attacked or disrupted – an amazing achievement which its critics often overlook. However, Bitcoin is not what I have in mind when I think of genuinely peer-to-peer money. The reason why brings me to my next point.
2. Abundant
One of the main complaints a peer-to-peer advocate could wage against the banking system is the fact that it creates money according to the imperatives of a narrow elite, and forces everyone else to use its own IOUs rather than their own. Part of the complaint, as we have seen, is political – about who controls the money supply. The other side of it, from my point of view, is about artificial scarcity and abundance.
On this point, I’m in agreement with monetary theorists who recognise that the fundamental nature of money is social, not physical. While physical things have acted as money, they aren’t it by themselves. Even gold, when it has been considered money by governments, gains part of its value because of a political arrangement, not because of its inherent metallic qualities. Coins and notes, most obviously, circulate at much higher than face value. The reason is: money is a social phenomenon. It’s the collective agreement of a group of people to accept a certain symbol as a promise for value which gives it its power.
Once we can understand this, it’s ours to create and change as we see fit. Since its basis is in belief and confidence, its supply does not need to be artificially constrained by the availability of a physical medium. The amount of gold in the ground or processing power in a Bitcoin miner shouldn’t determine the quantity of money available. The basis for money issuance should be our mutual trust and confidence, and not the availability of physical objects, or artificially scarce electronic symbols. Michael Linton, the inventor of the LETS scheme, summarised this well when he spoke of the absurdity of not being able to build a house for want of inches. People connected by a chain of trust shouldn’t be prevented from transacting for lack of symbols with which to encode and formalise their trust. So, the reason Bitcoin fails the peer-to-peer test, in my view, is its flawed conception of what money is. This is not to say that it isn’t a great technological project; just that it doesn’t fulfil the potential of peer-to-peer money.
3. Community-oriented
The third criteria by which a peer-to-peer money project should be assessed is its conception of community. A community of individuals is more than the some of its parts. Community money, created as credit, is a promise which is backed by a group of individuals who accept it as payment. This makes it more valuable: since more people can accept it as payment, it can travel further, making it more useful as money. So, while a peer-to-peer credit network should allow for the creation of money by individual nodes, it should also allow for emergent, community phenomena. The credit of communities should be maintained by their constituent nodes, who internally rearrange their obligations to one another based on their acceptance of it as payment for value to outsiders. In this way, groups of people who regularly trade with each other can create extra credit, and use it to interact with other communities. There is no reason why there should only be first-order communities as well. Peer-to-peer money can exhibit fractal patterns of communities of communities, and so on, each creating a higher-order of credit sustained by their members. This feature of a peer-to-peer money supply will encourage a balance of local and global economic activity, rather than the radical centralisation our present monetary system encourages.
4. Debt-transcendent
This point is a little tricker, however, I think it’s also a crucial dimension of a peer-to-peer money proposal. In David Graeber’s terms, the practice of debt has historically been bounded by institutions which limited its corrosive consequences on social fabric. In ancient Sumer, the birthplace of credit money and lending at interest, debtors were protected by regular debt jubilees. In the next stage of credit money, the Middle Ages, lending was controlled by the religious institutions which regulated commercial activity. It was impossible to be made a slave because of one’s debts in the literal sense. Further, lending at interest was tightly controlled. It is one of the characteristics of the modern financial system that institutions which existed to protect debtors have been eroded, in favour of the interests of lenders. The rolling back of usury restrictions is one example.
However, historically the understanding that debt is socially dangerous, and to be controlled, is important. If money is just a promise, we need to have collective agreements preventing money creation from getting out of control. This is perhaps the biggest challenge for peer-to-peer money: to create credit money which transcends or limits the logic of debt. Since in software terms, agreements about the structure of the banking system will be a matter of which software gets used, the principles which limit the effects of debt will need to be coded in. How exactly this is fulfilled I will leave open for the time being.
Why build it?
Having outlined the general principles peer-to-peer money should fulfil, it’s worth returning to the original question. Why is it a desirable project, at this stage? One reason is simply that it should be done because it can be: the technology and know-how exist. All that remains are the design ideas, and the willingness to implement them, in search of a solution. With the available technology, it can only be a good idea to experiment and try to realise the ambition of genuinely peer-to-peer, democratic money.
However, the other reason I think this is the most pressing area in the future of money conversation is the current state of the world’s financial system. In this post I’ve argued that the banking system creates money in an inefficient way, at an angle to economic and democratic needs. One thing which should also be obvious, in light of the ongoing financial crisis, is that it is hugely unstable. According to some theories of banking and credit, the design of the banking system itself is inherently geared towards infinite growth, and endless expansion of debt. In a world of finite resources, and finite appetite for debt, the game of credit creation at interest cannot continue. Logically, we should expect the banking system to shake itself to pieces as it confronts its own inherent, paradoxical design. Politicians’ attempts to patch it up, rather than reconsider its basis, appear to me misguided and ignorant of opportunities to create something better.
The banking system is premised on two twin assumptions. If money is just a promise, then the existence of a centralised banking system presumes that individuals acting as peers cannot trust each other enough to make their own. It must also assume that individuals lack the technological means to create the necessary payment infrastructure to keep track of their mutual obligations. The project of peer-to-peer money should presume the exact opposite: that we cannot trust the banks to do this job for us. Given the technological means at our disposal, and equipped with an understanding that money is just a social agreement, we should be able to find a way to do it ourselves.

A Perspectival Trust Metric for Ripple

This is my second post on defining a trust metric for Ripple, or in fact any peer-to-peer credit network which relies solely on trust. In my last post, I looked at a simple approach based on measuring the average ratio of credits and debts for a user. While this wasn’t a bad start to thinking about the problem of trust in general, it suffered from being too simple (I’ll explain why.) In this post, I want to explore a new approach suggested in a comment by Jordan Greenhall, based on measuring trust as a perspectival, probabilistic calculation rather than an inherent property of a node.

First, let’s revisit the reasons why a trust metric is so critical for any peer-based credit network like Ripple to scale.


Ripple is a system to create money out of credit relationships between peers, rather than between individuals and banking institutions, or the state. It uses a principle of mutual credit, allowing users to “create money” as IOUs within the context of a relationship of trust. Since IOUs can be used to cancel debts out over time, Ripple can be described as a way of keeping money as a unit of account, while dispensing with the complicated, undemocratic ways in which money supplies are created in modern economies.

The critical difference between Ripple and more traditional types of mutual credit circles is the reliance on pairwise relationships between nodes, rather than relationships between nodes and a centralised book-keeper. One of the chief difficulties with a LETS approach to mutual credit is getting debtors to pay down their negative balances, as well as preventing stagnation due to hoarding by creditors. This usually takes some administrative overhead. In Ripple’s case, we are leaving the job of settling balances to peers to sort out for themselves, rather than taking a top-down administrative approach. (For an overview of Ripple and its many advantages, see Is Ripple The Future of Money?)

There is however a tension within Ripple which needs to be resolved for it to scale and achieve its potential as a substitute for money. The more I think about Ripple, the more this basic problem looms: friendship is the predominant context for relationships with high degrees of trust. People tend to expect their “strong ties” not to wrong them by ignoring debts, for example. It’s always riskier to lend money to someone you don’t know, even with some legal recourse if things do go wrong. However, the problem this creates is that the use of money in general, which Ripple seeks to create, is typical of “weak tie” relationships. The vast majority of monetary expenditure, for the average person, is with people they don’t know or trust.

The basic tension is this: the people who a person typically trusts with money are not the kinds of people we need to use money with much. A Ripple network which tries to scale and become useful for impersonal transactions won’t work if the nodes in people’s immediate networks are predominantly friends and family. This would actually require friends to get used to having debts with each other quite a bit more than they already do, and would probably create some discomfort.

This sets the context for why Ripple needs a trust metric. As discussed in a previous posts on social currency, such metrics try to quantify and represent a person’s social capital. In Ripple-language, social capital is really credit-worthiness, or the extent to which you are “deserving of credit.” The effects of quantifying and making trust visible are not to be underestimated. A good trust metric reinforces positive behaviour, punished bad behaviour, and gives strangers an excuse to trust each other in ways they otherwise wouldn’t.

This sounds like the kind of tool which could help Ripple resolve the tension between strong ties and the ability to scale. With a trust metric, we have a way of quantifying and representing creditworthiness to people who don’t know each other, and therefore creating a basis for trust. A trust metric could oil the wheels of a more impersonal, highly scalable Ripple network, with far more extensive payment routing capacity. With that, let’s move on to discussing why the approach in my last post won’t cut it.

Trust as Credit Ratio

In Defining a Trust Metric for Ripple, I suggested that creditworthiness could be boiled down to the weighted average credit ratio for each of a user’s pairwise credit relationships. In simpler language, this is just a ratio which expresses how in debt or credit a user is overall, weighted against the volume of credit capacity in each relationship (i.e. giving 10 times more weight to a 50%-used credit allowance of a thousand pounds, to the same of a hundred pounds.) We can summarise this in a simple formula:

A’s overall credit ratio = A’s total credit capacity / A’s total credit limit

What comes out of this is a number which expresses the overall credit ratio. Someone with 1 has perfectly balanced accounts. This gives a snapshot of the overall credit balance at a given point, but we have to go further. What we’re really concerned with is how this ratio pans out over time, so we might take a six-monthly average ratio. This approach isn’t a bad start – it does make sense to look at credit ratio over time as evidence of whether someone is balancing their accounts (and is therefore creditworthy.)

However, there are some serious limitations. For one, we can’t distinguish between two people who have vastly different credit allowances and network size, but the same overall ratio. We could add the average amount of credit a user has to the metric, like so:

0.8 | £3,000

However, there’s another problem (which I think is the knock down argument for this approach in general.) We still can’t distinguish between someone who has a friend who says they will loan them a million pounds (but isn’t being serious), and someone with thousands of node relationships who will lend him a more modest but real number. This is where I’ll leave this approach (in the graveyard of ideas, somewhere.)

It’s time to move on to Jordan’s proposed approach. I think this has the beginnings of a real solution.

Perspectival Trust

I’ve always defaulted to a sort of Bayesian “perspectival” model where you can’t really give a global universal score for anyone, but you can give *my* perspective on them. You look at the credit I’ve issued to people in the network, the credit they’ve issued to people in the network (etc.) and use this network-cascade to derive the credit score “my network” gives to any given individual. So if I don’t know you but many of my friends do, then your credit score for me is (my credit to friend n * their credit to you) summed over N.

Jordan Greenhall, Blog Comment, Aug 17th

The perspectival approach to measuring trust doesn’t treat trust as an inherent property of a node. Instead, it tries to make a logical, probabilistic calculation about how much you can trust someone, based on how this individual is connected to you in the trust graph. If you have no common connections with a user, there is no credit rating, but that’s not such a bad thing, as I’ll explain.

What’s elegant about this as a general approach is that it takes the act of extending someone a credit limit as a vote of trust. This is intuitive, since by extending credit you are explicitly trusting someone, to that degree. It’s also parsimonious, since it gives us a basis for deriving a trust metric without the hassle of additional social gestures like reviews, or ratings.

The information about trust is encoded in credit graph itself: all we need is a way of extracting it and working with it. Based on this information about trust in first-degree connections, we can make inferences about degrees in second, third and fourth (etc) connections. In other words, we can try to estimate how much a user should trust someone unknown to them, based on how much they trust people who (directly or indirectly) already trust him.

An outline

Here’s my attempt to turn Jordan’s suggestion into a formal approach which could be implemented. I don’t yet know if this is the best way, however I’m partly sharing this in order to get more feedback, and help improve it. First of all, let’s make a basic assumption:

Proportionality Principle: In a credit network, a user trusts someone in proportion to the amount of credit they give them.

This principle allows us to draw conclusions about degrees of trust within a user’s primary network. If trust is proportional to credit awarded, this becomes relatively easy. John trust Sarah with £100, but trusts Jane with £1,000 – he therefore trusts Sarah 10 times more than Jane. In reality, degrees of trust are not likely to be as precise or as directly proportional to credit allowance, as there are other factors which determine how much credit we extend to people. However, the assumption is generally true enough.

The second assumption is about how trust decays:

Trust Decay Principle: Trust from one node to another decays as a function of the distance between them, as measured by number of hops.

This reflects real life: we trust our friends more than our friends’ friends, but we trust the latter more than total strangers, and so on. In credit networks, there is a similar logic: if you are willing to extend credit to John, you must have some degree of confidence in who John extends credit to, as this has bearing on his ability to keep his promises to you.

The rate at which trust decays is something difficult to put a precise number on. It is probably going to be a subjective exercise in working out what feels right. However, since many laws in nature are power laws, and I find a linear relationship to overscore trust, we’ll go with this for now:

Trust coefficient c = 1 / Number of hops, squared

Finally, there is one more assumption we need to make. This one might be more controversial than others, but I think we gain some significant flexibility as a result:

Normalisation Principle: The trust score of the individual with the highest amount of credit in a user’s network is 1, (and every other trust score is therefore a proportion of 1.)

Here, we’ll assume that a score of 1 is the maximum anyone can have in a user’s primary network, as a matter of convention. Everyone else’s score can be worked out as a proportion of 1. This has the consequence that giving someone a million pounds of credit doesn’t allocate them proportionally more power in accumulating trust for their own network (which would be easier to game.) All it means is that, by implication, the user who extends credit has a very high threshold of trust for said user, which affects how the metric will diminish the significance of much lower levels of trust in her primary network.

Putting it to Work

With our basic assumptions in place, it’s time to try out the mechanics of the approach. Here is a credit network graph, showing a small cluster of users around A.

The numbers represent an amount of credit awarded between the two nodes, in the direction of the arrows. (A gives C 50 credit, etc.) As you can see, there are some first, second and third degree connections, as well as an ambiguous 3rd/4th degree connection, between A and H. We can now work out everyone’s trust score in this graph, from the perspective of A.

A:B (1)

A extends the biggest credit line to B, so A‘s trust for B is simply 1.

A:C (50%)

C has half as much credit as B. A‘s trust for C is 0.5. In other words, A trusts C 50% as much as B, who is the baseline user.

A:D (80%)

C has 80% as much credit as B. A‘s trust for D is 0.8.

Moving on to the second row, we need to use our decay coefficient. Here’s how it can be done:

A:H (20%)

Starting with the simplest, A‘s trust for H is expressed as

A:H = A:D * c * (D:H)

c is our trust coefficient, not the speed of light. In this case, we’re at two hopes, so

c = 1 / 2^2

c = 0.25

D:H is simply 1, since D has given H the most credit. Plugging the values in, we have…

A:H = 0.8 * 0.25 * 1

A:H = 0.2

A:E (25%)

This one is also straightforward, like A:H…

A:E = 1 * c * B:E

A:E = 0.25 * 1

A:E = 0.25

A:F (29%)

Moving on to more complex examples, let’s take F, who has has multiple connections to A, via C and B. In this case, I suggest we just take the sum of the trust accumulated from both connections. (Rounded to the second decimal.)

A:F = (A:C * c * C:F) + (A:B * c * B:F)

A:F = (0.5 * 0.25 * 1) + (1 * 0.25 * 0.67)

A:F = 0.12 + 0.1675

A:F = 0.29

A:G (0)

G is an orphan node, with no friends. He’s not connected to A, so from A‘s point of view, he has no trust score. If A decided to trust G with credit, he would have to rely on other information than his network’s opinion of G, because it doesn’t have one. This isn’t a bad consequence, since it’s true to life.

A:I (21%)

Finally, the most complex relationship, A:I. We need to find the sum of trust incurred through both paths, using different coefficients. However, we can make life simple. Since we already know A:F, we can use that for one of the branches, and a coefficient for just one additional hop. The other branch, via D, is straightforward enough. (Final value rounded to the second decimal, again.)

A:I = (A:F * c * F:I) + (A:D * c * D:I)

A:I = (0.29 * 0.25 * 1) + (0.8 * 0.25 * 0.7)

A:I = 0.0725 + 0.14

A:I = 0.21

Final thoughts

No doubt, there will be more nuances to work out before this model can work well. One of them might be capping trust to 1, so no user’s trust can exceed the baseline user’s. There are also questions about how to communicate the meaning of the metric to users in an intuitive way, and calibrating the decay coefficient correctly. We also have to consider the problem of how to present a user’s trust degree back to them. I’ll leave these questions to future posts and comments.

Hopefully, this describes the beginning of an approach which can actually work. As a result, we might have a metric which works the same magic on Ripple as reputation points do on eBay. Imagine how limiting eBay would be if you had no metric serving as a basis for trust between strangers – it wouldn’t work. This is how important I think a trust metric is for Ripple to be able to scale properly in the real, impersonal world of money and credit.

Thanks to Jordan Greenhall for suggesting a perspectival approach. As usual, I would be grateful for any comments or suggestions from anyone which can help push this forward.

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Thoughts on Social Currency, pt. II

How do social currencies differ from money as a measure of value?

As well as working as a kind of social means of exchange, social currency is also a tool for measuring value. In that respect, it resembles money’s traditional function as a “unit of account.” Although money can be used to store and exchange value, it can also be used in a purely abstract sense, as a unit of measure, like an inch or a kilogram. The proliferation of social currencies online points to a similar possibility: that of measuring the various types of social value we come to rely on in interacting, and transacting, with one another.

However, as discussed in a previous post, the analogy between money and social currency is not to be taken too literally. There are some significant differences between money and social currency. I’ve already looked at those in relation to social currency as a means of exchange: it turns out that we create and provide social currency likes jokes and stories as abundance-based gifts which circulate in social networks, earning social capital for their originators and transmitters along the way. In this post, I want to look at how social currency as “unit of account” differs from money.

What social currencies measure

The first major difference between social currencies, online or offline, and money as a unit of account is what is being measured. Money measures the value of goods and services which are inherently scarce and can be exchanged. One legitimate criticism of the monetary system is that it is blind to other types of value, which have equal significance in the way economies function.

Social value, or “social capital,” is the value created and sustained through our relations in social networks. While it’s tautological that the rich have lots of money compared to everyone else, it’s less recognised that they are also usually socially wealthy as well. They enjoy connections to other rich and powerful people, which help them get into private schools, high paying jobs and access to other social and economic opportunities.

Money as it is defined today encourages us to see the world in financial terms, and to ignore the myriad other forms of wealth which contribute to wellbeing. One of the functions of social currencies, which makes them compelling to anyone interested in transcending the limitations of an economy viewed solely through money, is that they make visible otherwise intangible forms of social capital, like trust and reputation, for the world to see. This brings us to the second feature of social currencies.

Recorded trust

While social capital is a very useful type of asset, it has some limitations which don’t tend to affect the type of value measured by money. One of these is that, historically, social capital has mainly existed in people’s minds, rather than on paper.

In medieval times, the majority of economic life took place in the context of social networks of trusted participants. There was an honour code, for example, in the medieval Islamic merchant trade networks. According to David Graeber, transactions in goods and services between merchants were secured “with a handshake and a glance at heaven”:

If there were problems, they were referred to sharia courts with no power to have miscreants arrested or imprisoned, but with the power to destroy a merchant’s reputation, and therefore, credit-worthiness, if he were to refuse to abide by their rulings.

David Graeber, How Debt Has Defined Human History

In other words, deals were highly dependent on trust. Honour therefore had a very tangible economic importance: without it, a person couldn’t secure access to credit, and would find themselves excluded from vital trade networks.

Social networks record trust of their participants an informal, implicit ways which don’t scale easily. What’s more, when someone behaves in the wrong way, the information doesn’t spread so quickly through word of mouth. Trust-worthy people who are not known to people they wish to deal with, or who do not have trusted friends to vouch for them, will find it hard to secure trust.

The first social currencies as units of account were attempts to solve this problem, by creating a symbolic representation of trust, or social capital generally, which others could rely upon in deciding whether to trust the bearer. This happened long before the internet: it’s important to realise that social currencies online are just an extension and refinement of an age-old idea. In their older forms, there are all sorts of symbols which stand in for trust, attempting to solve the scaling problems associated with social assets. The commercial trade example is just one of many: medical degrees, Nobel Prizes, club memberships, gold stars in classrooms, getting “made” in the Mafia are all forms of social currency. They record social capital in a way which is commonly accepted within a network, and so encode trust and make it visible for others to see.

It is this function of “making visible” social capital which sets social currencies apart from money. While money measures value, it isn’t primarily used in order to display wealth to others. People do show off wealth to each other, but primarily through things which they own and flout (so called “Veblen goods.”) Social currencies, on the other hand, exist not just to measure social wealth, but also to display it to others. That’s the point: by making recorded trust visible, they enable new trust-based interactions with other people outside of their networks. They enable social capital to scale.

Quantitative and qualitative

Money measures scarce value in a quantitative manner. Social currencies don’t always. As I’ve mentioned before, many types of symbols operate as social currency without being the kinds of things which count anything: Nobel Prizes, for instance, or a review of a hotel. These types of symbols are more qualitative: they represent something without trying to quantity it too precisely. Perhaps this is because such forms of value can’t be too easily quantified: they try to record intangible types of value, which can’t be bought, sold, or measured in any straightforward way.

Perhaps one of the major opportunities the internet brings is the ability to create quantitative social currencies. eBay reputation points are an excellent example: each successful transaction on eBay increases your reputation score by a point, and conversely. By measuring qualitative judgments about individual interactions, eBay is able to summarise a person’s degree of trustworthiness in their community with a number. The proliferation of platforms for collaborative consumption is making quantitative social currencies ever more common. Wherever trust is required to enter into transactions, these symbols help to bridge the gap.

At the basis of a quantitative social currency is the ability to measure gestures, directly or indirectly, from participants, which can be taken as indicators of trust. The ability to aggregate numbers of gestures into an overall metric creates an abstract measure of social value within a network. Sometimes, the recorded gesture is an explicit vote of confidence, in the case of eBay transactions. Other times, the gesture is a byproduct of another, related action, such as following someone on Twitter. In some cases, the record of trust is quite abstract: consider the cumulative consequences of linking to a web site, and the effect on its position in search results.

Abundance-based, but not fungible

Finally, there are two more characteristics of social currencies which are different from money in important ways. One is their abundance-based nature.

Money can be more or less scarce, depending on the type of monetary system in use. Credit-based money can be created abundantly, but is often subject to the lending practices of banks. Since those interested tend to diverge from the needs of the economy in general, we can speak of a de facto scarcity in the money supply. The availability of money is dependent on factors which don’t bear much relation to people’s actual needs. Under commodity money systems, the problem is worse, since there money literally consists in a ‘thing’ which needs to exist prior to the transaction, in order for it to take place.

Social currencies don’t suffer from the same type of scarcity. It costs nothing to create a digital symbol, like a reputation point, or a club membership. These types of tokens of value can be created abundantly: the only thing which needs to govern their creation is a system of rules which guarantees the perception that they mean something. The scarcity of Nobel Prizes is not to do with a lack of paper, but rather in the need to preserve the (perhaps misplaced) perception that Nobel Prizes are valuable social symbols. The scarcity of eBay reputation points is not to do with physical or digital limitations of the availability of numbers. They are limited to one per transaction in order to ensure their long-term meaning and value.

For very similar reasons, it seems that social currencies, unlike money, are inalienable from the people who originally earn them. You can’t buy things with your eBay reputation points, or legitimately transfer them to anyone. The reason is the value of social currencies lies in their ability to represent a social consensus about reputation. Reputation is inseparable from identity, and identity is never going to be legitimately transferable. While there are many reasons to try to earn social currencies, the ability to spend them is not one of them.

This concludes a recent series of posts on social currency. I hope you found them useful.

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