Age of currency disruption is here

With Sinclair Davidson and Jason Potts

It is unusual for the World Economic Forum’s Davos conference, held every year at the end of January, to be genuinely significant. But it seems this one was. Davos 2020 made clear that we are now living through a monetary reform era comparable to the great monetary events of the twentieth century.

The end of the gold standard, the creation of the Bretton Woods system in 1944, and that system’s collapse in the 1970s all brought about massive, structural economic changes. Our new age – the age of digital money competition – is likely to be just as disruptive.

At Davos the World Economic Forum announced a global consortium for the cross-border governance of digital currencies (including the class of cryptocurrencies stabilised against fiat money known as ‘stablecoins’) and a toolkit for the world’s central banks to establish their own digital central bank currencies.

The details of these Davos initiatives are less important than what they symbolise. Central banks have been experimenting with fully digital currencies for at least half a decade, ever since Bitcoin received its first big waves of press. But their experiments are suddenly urgent, for both commercial and geopolitical reasons.

On the one side, the Facebook-led Libra digital currency project offers a vision of corporate-sponsored non-state private money. On the other side, China is fast-tracking the development of a fully digital yuan, with a barely disguised goal to challenge the American dollar’s domination through technological innovation. Both projects create enormous problems for the rest of the world’s central banks – let alone finance regulators and foreign policy strategists.

Libra has been faced with a concerted hostile attack from central banks and regulators – an attack that begun literally the day it was announced in June last year. Many of the Libra consortium have been pressured into withdrawing from the project.

Mastercard, Stripe and Visa withdrew after they received a letter from US Senators in October declaring that if they stayed in Libra they could “expect a high level of scrutiny from regulators not only on Libra-related payment activities, but on all payment activities”. The Bank of France chief declared last week that “Currency cannot be private, money is a public good of sovereignty”, and the French finance minister has warned that Libra is not welcome in Europe.

This mafia-like behaviour from American and European regulators is short-sighted – astonishingly so. Whether Libra ends up being a successful global corporate currency or not, it represents a powerful and competitive counterbalance to the Chinese digital yuan.

Details have been dribbling out about the digital yuan since it was revealed in August last year. Its key feature is that it is fully centralised. The People’s Bank of China will have complete visibility over over financial flows, including the ability to control transactions tied to an individual consumer’s identity. This offers China the digital infrastructure for a type of financial repression that is without historical parallel.

And adoption is basically assured. The Chinese government can coerce financial institutions to adopt the digital yuan, if necessary, and can exploit the remarkably strong hold that digital payments like WeChat Pay and AliPay have on Chinese commerce.

Let us hope there are some serious strategists thinking about what happens if this digital currency becomes part of China’s foreign policy toolkit – what the consequences of yuan-isation will be for those countries torn between the Chinese and American spheres of influence.

This is the context in which the many of the world’s central bankers came to Davos to spruik their own digital currencies. More than 50 central banks surveyed by the Bank of International Settlements are working on some form of digital currency, and half a dozen have moved to the pilot project stage. Our Reserve Bank told a Senate committee in January that it too has been secretly working on an all-digital Australian dollar.

And of course in the background to this monetary competition between the corporate sector and the government sector is the slowly growing adoption of fully decentralised cryptocurrencies – the decade-old technology that first sparked these waves of monetary innovation.

The global monetary system of 2020s will be a regulatory and financial contest between these three forms of all-digital money: central bank digital currencies, corporate digital currencies, and cryptocurrencies. The contest has profound significance for the ability for governments to control capital flows across international borders, for financial privacy, for tax collection, and obviously monetary policy.

China has the authoritarian power to force adoption of its central bank digital currency. Countries like Australia do not. So it is not obvious which form of money will eventually dominate.

National governments have had nearly absolute control over national currencies for at least a hundred years, in some cases much longer.

The end of the Bretton Woods system in the 1970s incited a generation of economic reform, as domestic policymakers discovered that Bretton Woods had been propping up all sorts of regulatory controls, trade barriers and even labour restrictions.

We’re about to discover what centuries of state monopoly over money has propped up.

Automating the big state will need more than computers

Robodebt – the automated Centrelink debt issuance program that was found invalid by a federal court last month – is not just an embarrassment for the government. It is the first truly twenty-first century administrative policy debacle.

Australian governments and regulators increasingly want to automate public administrative processes and regulatory compliance, taking advantage of new generations of technologies like artificial intelligence and blockchain to provide better services and controls with lower bureaucratic costs. There are good reasons for this. But our would-be reformers will need to study how robodebt went wrong if they want to get automation right.

The robodebt program (officially described as a new online compliance intervention system) was established in 2016 to automate the monitoring and enforcement of welfare fraud. Robodebt compared an individual’s historical Centrelink payments with their averaged historical income (according to tax returns held by the Australian Taxation Office). If the Centrelink recipient had earned more money than they were entitled to under Centrelink rules, then the system automatically issued a debt notice.

That was how it was supposed to work. In practice robodebt was poorly designed, sending out notices when no debt actually existed. Around 20 per cent of debts issued were eventually waived or reduced. The fact that those who bore the brunt of these errors had limited financial resources to contest their debts contributed to robodebt’s cruelty. In November, the federal court declared that debts calculated using the income average approach had not been validly made, and the government has now abandoned the approach.

Automation in government has a lot of promise, and a lot of advocates. Urban planners are increasingly using AI to predict and affect transport flows. The Australian Senate is inquiring into the use of technology for regulatory compliance (‘regtech’) particularly in the finance sector. Some regulatory frameworks are so byzantine that regulated firms have to use frontier technologies just to meet bare compliance rules: Australia’s adoption of the Basel II capital accords led to major changes in IT systems. And the open banking standards being developed by CSIRO’s Data61 promise deeper technological integration between private and public sectors.

Regulatory compliance costs can be incredibly high. The Institute of Public Affairs has estimated that red tape costs the economy around 11 per cent of GDP in foregone output. The cost of public administration to the taxpayer is considerably more. Anything that lowers these costs is desirable.

But robodebt shows us how attempts to reduce the cost of administration and regulatory compliance can be harmful when done incompetently. The reason is built into the modern philosophy of government.

Economists distinguish between administrative regimes governed by discretion and those governed by rules. The prototypical example here is monetary policy. Rules-based monetary policies, where central banks are required to meet targets fixed in advance, are less flexible (as the RBA, which has consistently failed to meet its inflation target is keenly aware) but at the same time provide a lot more certainty to the economy. And while discretionary regimes are flexible, they also vest a lot of power in unelected bureaucrats and regulators, which comes at the cost of democratic legitimacy.

Automation in government is possible when we have clear rules that can be automated. If we are going to build administrative and compliance processes into code, we need to be very specific about what those processes actually are. But since the sharp growth of the regulatory state in the 1980s governments have increasingly relied less on rules and more on discretion. ASIC’s shrinks-in-the-boardroom approach to corporate governance is almost a parody of the discretionary style.

The program of automating public administration is therefore a massive task of converting – or at least adapting – decades of built up discretionary systems into rules-based ones. This was where robodebt fell over. Before robodebt, individual human bureaucrats had to manually process welfare compliance, which gave them some discretion to second-guess whether debt notices should be sent. Automating the process removed that discretion.

The move from discretion to rules is, to be clear, a task very much worth doing. Discretionary administration feeds economic uncertainty, and ultimately lowers economic growth. We have a historically unique opportunity to reduce the regulatory burden and reassert democratic control over the non-democratic regulatory empires that have been building up.

Of course, public administration-by-algorithm is only as effective (or fair, or just, or efficient) as those who write the algorithm build it to be. There’s a lot of discussion at the moment in technology circles about AI bias. But biased or counterproductive administrative systems are not a new problem. Even the best-intentioned regulations can be harmful if poorly designed, or if bureaucrats decide to use discretion in their interest rather than the public interest.

Robodebt failed because of an incompetent attempt to change a discretionary system to a rules-based system, which was then compounded by political disregard for the effect of policy on welfare recipients. But robodebt is also a warning for the rest of government. The benefits of technology for public administration won’t be quickly or easily realised.

Because when we talk about public sector automation, we’re not just talking about a technical upgrade. We’re talking about an overhaul of the regulatory state itself.

Christian Porter’s defamation reform would be a catastrophic mistake

With Aaron M Lane

Attorney-General Christian Porter wants social media platforms like Twitter and Facebook to be legally liable for defamatory comments made by their users.

Right now, the common law can distinguish between the legal liability of active publishers of information (like newspapers and broadcasters) and the passive platform operators that allow users to publish information themselves. Courts decide where this distinction is drawn according the unique facts of each case.

But in a speech to the National Press Club on Wednesday, the Attorney-General declared he wants to eliminate the distinction altogether: “Online platforms should be held to essentially the same standards as other publishers.”

The Attorney-General’s proposal is fundamentally confused. Removing the distinction between digital platforms and newspapers would have a devastating effect on both those platforms and our ability to communicate with each other.

The proposal is bad on its merits. But even besides that, the conservative government needs to understand how destructive it would be to the conservative movement online.

Let’s start with the legal principles. It makes sense that newspapers and broadcasters are liable for what they publish. They actively commission and produce the content that appears on their services. They read it, edit it, arrange and curate it. They pay for it. Newspapers and broadcasters have not only an editorial voice, but complete editorial control. Indeed, it is this close supervision of what they publish that gives them strength in the marketplace of ideas.

Social media platforms do nothing of the sort. Not only do they not commission the content that appears on our newsfeeds (let alone read, factcheck, or edit that content), they don’t typically confirm that their users are even real people – not, say, bots or foreign impersonators. They merely provide a platform for us to communicate with each other. Social media has facilitated a massive, global conversation. But it has no editorial voice.

In the United States a parallel debate is going on among Republicans about whether Section 230 of the Communications Decency Act – which explicitly prevents courts from treating ‘interactive computer services’ as publishers or speakers for the purpose of legal liability – should be abolished.

Section 230 has variously been described by scholars and commentators as “the 26 words that created the internet” or the “the internet’s first amendment”. The internet law professor Jeff Kosseff writes that eliminating this provision would “turn the internet into a closed, one-way street”. Attorney-General Porter’s proposal would have the same effect.

If social media platforms have to bear legal responsibility for what their users say, they will assume editorial responsibility for it. That means editing, deleting, and blocking all content that could be even the least bit legally questionable.

Newspapers and broadcasters sometimes take calculated risks with what they print, if they believe that the information they reveal is in the public interest. But why would a technological company – a company that lacks an editorial voice or the journalistic vision – be anything but hypercautious? Why wouldn’t it delete anything and everything with even the slightest risk?

And here is where the practical politics comes in. Even if the Attorney-General’s proposal was a good idea in principle, this policy would be particularly devastating for the conservative movement that supports his government. Indeed, it is hard to imagine a legislative proposal that would more effectively, and immediately, cut down the Australian conservative movement online.

After all, what side of politics benefits most from the political diversity and openness of the modern internet? What side of politics has relied most on the internet’s ability to bypass traditional media gateways? It is difficult to imagine the conservative political surge in recent years without social media – without Facebook, Twitter, YouTube, and all those podcast platforms.

If conservatives are concerned about social media networks “censoring” conservative content on their services now, well, making them liable for everything conservatives say would supercharge that.

And why would this policy stop at defamation laws? Why wouldn’t it also apply to liabilities around, say, Section 18C of the Racial Discrimination Act? Or our sedition laws? We are looking at a future where technology companies in California (companies that many conservatives believe are stacked with culturally left employees) could be required to second-guess how the most left-wing judges in Australia might enforce this country’s draconian anti-speech restrictions.

The Coalition government should also reflect on how some of its most recent legislative programs have backfired on conservatives. The Foreign Influence Transparency Scheme, passed in 2018 in order to tackle Chinese interference in Australian politics, is now being used to target the organiser of the Australian Conservative Political Action Conference, Andrew Cooper, and even Tony Abbott.

The Attorney-General is right that defamation law needs reform. Australia’s defamation framework is heavy-handed and disproportionately favours private reputation over the public need to discuss significant issues. But removing the courts’ ability to determine liability for defamation – and instead deputising the world’s technology companies to enforce what they imagine it could be – would be a catastrophic mistake.

The Crypto-Circular Economy

With Darcy WE Allen and Jason Potts. Originally a Medium post

If we are going to realise the environmental vision of the circular economy, we need to first think of it as an entrepreneurial economy.

In PIG 05049 the artist Christien Meindertsma shows how the parts of a slaughtered pig get reused downstream. For instance, gelatine derived from the skin ends up in wine, acids from bone fat end up in paint, and pig hair ends up in fertiliser.

The farmer sells what they can to retailers and sells the rest to other businesses, who then process and resell the what they can’t use to other users and businesses, who then process and resell the other parts … anyway you get it the point.

In a world of perfect information and zero-transaction costs this use and reuse would be trivial. The near infinite uses of pig parts would be immediately apparent to everyone in the economy and every part of the pig would be reallocated efficiently.

But of course we don’t live in a world of perfect information. All these reallocations have to be discovered by entrepreneurs and innovators.

PIG 05049 is a story of how resources move through the economy in surprising ways, as entrepreneurs reduce waste in the pursuit of profit.

But a circular economy makes stronger demands on us. The circular economy aspires not simply to minimise waste, but for goods to be “reused, repaired and recycled” after their first users no longer need them.

The circular economy imagines a world in which material goods are recovered, endlessly, and thus the environmental impact of the materials that we rely on for our prosperity is radically reduced.

It’s a powerful vision. But it is a hard vision to realise because transaction costs are not zero. Obviously, as goods travel through their life cycle they deteriorate. Goods get worn out, they rust, they fall apart.

But just as critical is the fact that information about the goods deteriorates as well. Product manuals get lost. Producers go out of business. Critical parts get separated. What the goods are made from is forgotten.

This information loss is a huge problem for the circular economy — it is very extremely expensive to reuse goods when we have lost information about what they are made of and how they work. This information entropy makes it hard for entrepreneurs and innovators to close the loop.

A circular economy with information entropy
This is what that looks like

In some previous work we’ve described a hypothetical “perfect ledger” where information is infinitely accessible, immediately retrievable, completely immutable, perfectly correspondent to reality, and permanently available. The perfect ledger is a thought experiment. It’s a thought experiment like an economy with perfect information or zero transaction costs that allows us to see how our imperfect world differs from an imaginary ideal.

And in a world of perfect ledgers, the circular economy’s information loop is completely closed. There is no information entropy — we never forget, so we can always reuse.

Blockchain technology of course is not a perfect ledger. But on many of the relevant margins, it offers a drastically improved way of managing information about goods as they travel through their lifecycle.

Information can be stored on a distributed ledger in a way that is resistant not only to later amendment, but that persists when it a good is passed from hand to hand, or travels across a political border, or when it is discontinued and forgotten by its designer, or when its original manufacturer goes out of business.

The information about the goods we have sitting on our desk, scattered around our homes and workplaces, built into our buildings, and powering our vehicles is being unpredictably but relentlessly lost. This is the blockchain opportunity for the circular economy. Blockchains can secure more information, better, more permanently and more accessibly about goods, so that they can be more efficiently reused.

And in conjunction with similar technological developments that reduce search costs — that is, that allow innovators to identify underutilised goods in the economy that could be bought and repurposed — the owners of goods will have increased incentivises to store and protect their property, if only to maximise the sale price.

The circular economy is often thought as a problem for governments to bring about. But if the circular economy is to be realised, we need to rethink the problem of waste and reuse as an environmental problem caused by an information problem.

Technological advances in the way we store and trust information offer a vision of large-scale, yet still bottom-up environmental improvements, where market incentives, price signals and contracting work to close the industrial loop.

Regulate? Innovate!

Suddenly, we live in a world of policy dilemmas around social media, digital platforms, personal data, and digital privacy. Voices on both sides of politics are loudly proclaiming we ought to regulate Facebook and Google. From the left, these calls focus on antitrust and competition law—the big platforms are too large, too dominant in their respective markets, and governments need to step in. From the right, conservatives are angry that social media services are deplatforming some popular voices and call for some sort of neutrality standard to be applied to these new ‘utilities’.

Less politically charged but nonetheless highly salient are the concerns about the collection and use of personal data. If ‘data is the new oil’—a commodity around which the global economy pivots—then Facebook and Google look disturbingly like the OPEC oil production cartel. These firms use that data to train artificial intelligence (AI) and serve advertisements to consumers with unparalleled precision. No more is it the case that 50 per cent of advertising is wasted.

These policy dilemmas have come about because the digital environment has changed, and it has changed sharply. Facebook only opened to the public in 2006 and by 2009 already had 242 million users. In the second half of 2019 it has 2.38 billion users.

Facebook is not just central to our lives—one of the primary ways so many of us communicate with family, friends and distant acquaintances—but central to our politics. The first volume of the Mueller investigation into Russian interference in the 2016 American presidential election focused on the use of sock-puppet social media accounts by malicious Russian sponsors. There’s no reason to believe these efforts influenced the election outcome but it is nonetheless remarkable that, through Facebook, Russian agents were able to fraudulently organise political protests (for both left and right causes)—sometimes with hundreds of attendees—by pretending to be Americans.

There always have been and always will be a debate about tax rates, free trade versus protectionism, monetary policy and banking, Nanny State paternalism, or whether railways should be privatised or nationalised. The arguments have been rehearsed since the 19th century, or even earlier. But we are poorly prepared not just for these topics of digital rights and data surveillance, but for new dimensions on which we might judge our freedoms or economic rights.

Private firms are hoovering up vast quantities of data about us in exchange for providing services. With that data they can, if they like, map our lives—our relationships, activities, preferences—with a degree of exactness and sophistication we, as individuals, may not be able to do ourselves. How should we think about Facebook knowing more about our relationships than we do? Do we need to start regulating the new digital economy?

The surveillance economy

One prominent extended case for greater government control is made by Shoshana Zuboff, in her recent book The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power (PublicAffairs, 2019). For Zuboff, a professor at Harvard Business School, these new digital technologies present a new economic system, surveillance capitalism, that “claims human experience as free raw material for translation into behavioural data”.

Zuboff argues these new firms look a lot like the industrial behemoths of the 19th and 20th century. Google is like General Motors in its heyday, or the robber barons of the Gilded Age. Using Marxist-tinged language, she describes how firms claim the ‘behaviourial surplus’ of this data to feed AI learning and predict our future desires—think Amazon or Netflix recommendation engines.

More sinisterly in Zuboff’s telling, these firms are not simply predicting our future preferences, but shaping them too: “It is no longer enough to automate information flows about us; the goal now is to automate us.” Netflix can put its own content at the top of its recommendation algorithm; Pokémon Go players tend to shop at restaurants and stores near the most valuable creatures.

Where many people spent years worrying about government surveillance in the wake of Edward Snowden’s leaks about the National Security Agency, she argues NSA learned these techniques from Google—surveillance capitalism begets surveillance state. At least the NSA is just focused on spying. Silicon Valley wants to manipulate: “Push and pull, suggest, nudge, cajole, shame, seduce,” she writes. “Google wants to be your co-pilot for life itself.”

Harrowing stuff. But these concerns would be more compelling if Zuboff had seriously engaged with the underlying economics of the business models she purports to analyse. Her argument—structured around an unclearly specified model of ‘surveillance assets’, ‘surveillance revenues’, and ‘surveillance capital’—is a modification of the internet-era adage, “If you’re not paying for the product, you are the product”. Many services we use online are free. The platforms use data about our activities on those platforms to make predictions—for example, about goods and services we might like to consume—and sell those predictions to advertisers. As she describes it:

… we are the objects from which raw materials are extracted and expropriated for Google’s prediction factories. Predictions about our behaviour are Google’s products, and they are sold to its actual customers but not to us. We are the means to others’ ends.

 … the essence of the exploitation here is the rendering of our lives as behavioural data for the sake of others’ improved control of us.

This argument misses a crucial step: what is this control? For the most part, the product derived from our data that is sold to other firms is advertising space: banner ads on news websites, ads dropped into social media feeds, ads threaded above our email inboxes. Seeing an advertisement is not the same as being controlled by a company. The history of advertising dates back at least to Ancient Rome. We are well familiar with the experience of companies trying to sell us products. We do not have to buy if we do not like the look of the products displayed on our feeds. It’s a crudely simple point, but if we do not buy, all that money—all that deep-learning technology, all those neural networks, all that ‘surveillance’—has been wasted.

Two sided markets

So how should we think about the economics of the big technology companies? Google and Facebook are platforms; what Nobel-winning economist Jean Tirole described as ‘two-sided’ markets. Until recently the dominant market structure was a single-sided market: think a supermarket. A supermarket has a one-directional value chain, moving goods from producers to consumers. Goods are offered to customers on a take-it-or-leave-it basis. In a two-sided market, customers are on both sides of the market. The service Google and Facebook provide is matching. They want advertisers to build relationships with users and vice-versa. Since the first scholarly work done on two-sided markets, economists have observed platforms that take three or more groups of users and match them together.

Two-sided markets are not new, of course. Newspapers have traditionally done this: match advertisers with readers. Banks match borrowers with lenders. French economics professor Jean Tirole’s first work looked specifically at credit card networks. But two-sided markets dominate the online world, and as the economy becomes more digital they are increasingly important. When we try to define what is unique about the ‘sharing economy’, we’re really just talking about two-sided markets: AirBnB matches holidaymakers with empty homes, Uber matches drivers with riders, AirTasker matches labour with odd jobs. Sometimes single and two-sided markets co-exist: Amazon’s two-sided marketplace sits alongside its more traditional online store.

The economic dynamics of two-sided markets are very different dynamics to what we are used to in the industrial economy. They are strongly characterised by network effects: the more users they have on both sides, the more valuable they are. So firms tend to price access in strange ways. Just as advertisers subsidised the cost of 20th century newspapers, Google and Facebook give us free access not because we are paying in personal data but because they are in the relationship business. Payments go in funny directions on platforms, and the more sides there are the more opaque the business model can seem.

An ironic implication of Zuboff’s arguments is that her neo-Marxian focus implicitly discounts what most analysts identify as the two key issues around these platforms: whether these networks are harmful for privacy and whether they are monopolistic.

First, the monopoly arguments. In Australia the ACCC has been running a digital platforms inquiry whose draft report—released in December 2018—called for using competition law against the large platforms on the basis they have started to monopolise the advertising market. There are many problems with the ACCC’s analysis. For example, it badly mangles its narrative account of how newspaper classifieds migrated online, implying Google and Facebook captured the ‘rivers of gold’. In fact, classified advertising went elsewhere (often to websites owned by the newspapers, such as Domain).

Yet the most critical failure of the ACCC is its bizarrely static perspective of an incredibly dynamic industry. True, platform markets are subject to extreme network effects—the more users, the more valuable—but this does not mean they tend towards sustainable monopolies. Far from it. There are no ‘natural’ limits to platform competition on the internet. There is unlimited space in a digital world. The only significant resource constraint is human attention, and the platform structure gives new entrants a set of strategic tools which can help jump-start competition. Using one side of the market to subsidise another side of the market helps ‘boot-strap’ network effects.

Consumer harm is the standard criteria for whether a firm is unacceptably monopolistic. Usually this means asking whether prices are higher than they would be if the market was more contested. Given the money prices for these services are often zero, that’s hard to sustain. Nobody pays to use Google.com. At first pass the digital platform business seems to have been an extraordinary boost to consumer surplus.

But, again, platform economics can be strange. It is possible we are paying not with money but with personal data, and the role of a competition authority is to protect our privacy as much as our wallet. This is the view of the ACCC (at least in its December 2018 draft report) and has become an article of faith in the ‘hipster antitrust’ movement in the United States that competition regulators need to focus on more than just higher prices.

There is obviously a great deal to privacy concerns. In a recent book, The Classical Liberal Case for Privacy in a World of Surveillance and Technological Change (Palgrave Macmillan, 2018), I argued we currently are in an extended social negotiation about the value of privacy and its protection. But the privacy debate is characterised by a lot of misconceptions and confusions. Privacy policies and disclosures have not always been acceptable. Expectations are changing. Mark Zuckerberg would no longer get away with the reckless anti-privacy statements he made as a CEO when Facebook launched. The question is whether to wait for privacy expectations to shift—supplemented by the common law—or whether governments need to step in with bold new privacy regulation.

The experience with privacy regulation so far has not been great. The European Union’s General Data Protection Regulation presents the single most significant attempt to regulate privacy thus far. The GDPR, which became enforceable in 2018, requires explicit and informed consent of data collection and use, informing users about how long their data will be retained, and provides for a “right of erasure” that allows users to require firms to delete any personal data they have collected at any time. The GDPR was written so broadly as to apply to any company that does business with any European citizen, in practice making the GDPR not just a European regulation but a global one.

Early evidence suggests host of consequences unforeseen by the GDPR’s designers. Alex Stapp, at the International Center for Law and Economics, argues GDPR compliance costs have been “astronomical”. Microsoft put as many as 1,600 engineers on GDPR compliance, and Google says they spent “hundreds of years of human time” ensuring they follow the new rules globally. These firms have the resources to do so. One consequence of high compliance costs has been to push out new competitors: small and medium internet companies that cannot dedicate thousands of engineers to regulatory compliance. As Stapp points out, it’s not at all clear this trade-off for privacy protection has been worth it: regulatory requirements for things such as data portability and right of data access have created new avenues for accidental and malicious access to private data.

A peculiarity of the history of early-stage technologies is they tend to trade off privacy against other benefits. Communications over the telegraph were deeply insecure before the widespread use of cryptography; early telephone lines (‘party lines’) allowed neighbours to listen in. Declaring privacy dead in the digital age is not just premature, it is potentially counterproductive. We need sustained innovation and entrepreneurial energy directed at building privacy standards into technologies we now use every day.

The deplatforming question

One final and politically sensitive way these platforms might be exercising power is by using their role as mediators of public debate to favour or disfavour certain political views. This is the fear behind the deplatforming of conservatives on social media, which has seen a number of conservative and hard-right activists and personalities banned from Facebook, Instagram and Twitter. Prominent examples include the conservative conspiracist broadcaster Alex Jones, his co-panellist Paul Joseph Watson, and provocateur Milo Yiannopoulos. Social media services also have been accused of subjecting conservatives to ‘shadow bans’—adjusting their algorithms to hide specific content or users from site-wide searches.

These practices have led many conservative groups who usually oppose increases in regulation to call for government intervention. The Trump administration even launched an online tool in May 2019 for Americans to report if they suspected “political bias” had violated their freedom of speech on social media platforms.

One widely canvassed possibility is for regulators to require social media platforms to be politically neutral. This resembles the long-discredited ‘fairness doctrine’ imposed by American regulators on television and radio broadcasting until the late 1980s. The fairness doctrine prevented the rise of viewpoint-led journalism (such as Fox News) and entrenched left-leaning political views as ‘objective’ journalism. Even if this was not an obvious violation of the speech rights of private organisations, it takes some bizarre thinking to believe government bureaucrats and regulators would prioritise protecting conservatives once given the power to determine what social media networks are allowed to do.

Another proposal is to make the platforms legally liable for content posted by their users. The more the platforms exercise discretion about what is published on their networks, the more they look like they have quasi-editorial control, and courts should treat them as if they do. While this would no doubt lead to a massive surge in litigation against the platforms for content produced by users, how such an approach would protect conservative voices is unclear: fear of litigation would certainly encourage platforms to take a much heavier hand, particularly given the possibilities of litigation outside the United States where hate speech and vilification laws are common.

The genesis of this proposal seems to come from a confusion about the distinction between social media platforms and newspapers. Newspapers solicit and edit their content. Social media platforms do not. Social media platforms come from a particular political and ideological environment—the socially liberal, quasi-libertarian and individualistic worldview of Silicon Valley and the Bay Area—and these technologies now hold the cultural high-ground. The conservative movement has focused on trying to change Washington DC when it should have been just as focused on developing new ways for people to exercise their freedom, as has Silicon Valley.

But regulation cannot be the answer. Regulation would dramatically empower bureaucrats, opening up new avenues for government intervention at the heart of the new economy (any proposed regulation of Facebook’s algorithm, for instance, would lay the foundation for regulating Amazon’s search algorithm, and then any firm that tries to customise and curate their product and service offerings), and threatening, not protecting, freedom of speech. To give government the power to regulate what ought to be published is a threat to all who publish, not to just a few companies in northern California.

Platform to protocol economy

I opened this article with a discussion of how recent a development the platform economy is: a decade old, at best. A host of new technologies and innovations are coming that challenge the platforms’ dominance and might radically change the competitive dynamic of the sector. New social media networks are opening all the time. Many of those who have been deplatformed have migrated to services such as Telegraph or specially designed free speech networks such as Gab. Blockchain technology, for instance, is a platform technology as a decentralised (no single authorities, public or private, can control its use) and open (anyone can join) protocol.

Likewise, intense innovation focusing on decentralised advertising networks threatens Google’s ad sector dominance, and offers advertisers more assurance their digital dollar is used well. Other new technologies focus on regaining control over user privacy. Cutting-edge privacy technologies such as zero-knowledge proofs open massive opportunities for hiding personal information while still participating in economic exchange and social interactions. Blockchain applications are being developed to give users genuine control over data and facilitate the sort of private property rights over information the European Union’s GDPR awkwardly tries (and fails) to create.

The platforms know they face an uncertain and more competitive technological future. That is why Facebook is developing its own cryptocurrency—a pivot into financial services, like Chinese social media WeChat developing WeChat Pay. Google is investing serious resources into blockchain research, despite the technology’s long-run potential to displace its competitive advantages. The internet 10 years on will look very different—not because governments decided to regulate, but because digital entrepreneurs will have kept pushing, bringing us new products and services, revolutionising the global economy.

Facebook’s monetary revolution

With Sinclair Davidson and Jason Potts

With its new digital money, Libra, a Facebook-led global consortium has created the world’s first private international reserve currency.

Announced on Wednesday, this is no small thing. For the first time since the collapse of the Bretton Woods system there is a clear competitor to the US dollar for global dominance in the currency market.

For simplicity’s sake think of Libra as a return to the global gold standard. But rather than governments setting the rules and exchange rates, with gold being the underlying store of value, we’re seeing a private organisation setting the rules and a portfolio of relatively risk-free assets playing the role of gold.

To be clear – Libra is not a cryptocurrency like, say, Bitcoin; but it has many Bitcoin-like characteristics. It is a private money. It is not government money – ultimately fiat is backed only by the taxing powers of the state. Libra will be backed by tangible assets.

Rather than Bitcoin, Libra is more like PayPal, or WeChat Pay, on steroids – a payment gateway and a new money system all rolled into one. This is perhaps a good halfway house to introduce the world to the concept of non-government digital money.

The implications are huge. Facebook has disrupted digital money in a way central banks and the commercial banking system never could. Facebook has brand recognition that even the global banks must envy.

For those consumers who may baulk at using Facebook to transact, other large tech companies cannot be far behind with their own products. So what now?

We predict a large uptake in these digital money products. Largely because consumers tend to emphasise convenience. Libra will very quickly achieve global acceptance among consumers and merchants. If that prediction comes true, many other firms will launch their own competing monetary systems. In short, there is going to be a lot of competition in this space in the very near future.

The short-term consequences include the immediate disruption of the remittance market. Those companies charging exorbitant fees to move money around the world will see their rivers of gold drying up. Debit cards will also quickly become redundant – accelerating the move to phone-based tap and pay systems. The world’s “unbanked” will quickly become “banked”.

There are other immediate practical concerns. Within the next year, both Australian consumers and merchants will be wanting to use Libra. How will this be done? How will it be taxed? Will it be taxed? But any work that has been done so far on these questions has come in the context of Bitcoin and cryptocurrency – an extremely niche market. A general use private money has simply not been on the radar.

Those central banks that tolerate high rates of inflation will see disintermediation. Governments that pursue irresponsible fiscal policies will see even greater capital flight. Ironically the presence of a convenient, sound and private digital money will provide incentives to institutionally challenged governments to lift their game or lose total control over their domestic policy environments.

Every country in the world faces policy challenges from a viable private international reserve currency. Control over the monetary system lies at the heart of the modern economy. A viable alternative to fiat currency, with international mobility, undermines both the conduct of monetary policy and fiscal policy.

No doubt governments and their regulators will be looking very closely at Libra. They may treat it as a threat. But it is an opportunity for a forward-thinking government. It should come as no surprise that Libra is being set up in Switzerland. They have sensible laws relating to financial matters. The question we should be asking is why Australia isn’t being considered as a location for these products?

Australia should consider becoming a currency haven. Not only should a suite of policies be developed that facilitates the use of a private international reserve currency within Australia, a suite of policies that attracts the providers of such currencies to Australia should be considered. The use of Australian markets to purchase the underlying assets should encouraged and especially the inclusion of Australian assets in those portfolios should be encouraged.

With the announcement of Libra, the global monetary system – and arguably the structures of global financial capitalism – changed irreversibly. And just 10 years after the invention of Bitcoin and blockchain technology. The rate of disruptive innovation is only going to accelerate.

How well Australia adapts to this change will be determined over the next six months. Libra is coming in 2020. Regulatory obstruction is simply not an option.

Blockchain and the manufacturing industry

With Darcy Allen and Jason Potts

Bitcoin was invented in 2008 by Satoshi Nakamoto as a censorship-resistant cryptocurrency built for the internet. With regular fiat money centralised bodies such as banks and governments control the records of who owns what. For bitcoin those records are held in a decentralised blockchain. Blockchains are updated and maintained by a decentralised network. To ensure the transactions and records are correct, economic incentives to continually drive the blockchain network towards consensus.

Applications of blockchain extends beyond records of money. We rely on trusted third parties to maintain our registries, enforce our contracts, and maintain our records. Entrepreneurs are now discovering which roles carried out by third parties such as governments and firms will be shifted towards blockchain-based decentralised networks.

Blockchain is now being applied to trace goods along supply chains, to give control of medical records to patients, and to create decentralized identities that help people move across borders.

What does blockchain mean for Australia’s manufacturing industry?

At first glance manufacturers produce physical products and then transport those goods to consumers. More deeply, the manufacturing process is heavily reliant on databases of information in multiple directions along their supply chains. This is especially true for advanced manufacturing. When goods and inputs move, information about them must move too. This includes information about the provenance of sub-components and intermediate parts, information about the integrity of rare products prone to counterfeit, and information about ethical standards in production.

It’s harder to produce this supply chain information than you think. The information must be coordinated between hundreds of parties in the supply chain. Most of those parties don’t know or trust each other. And this information is still often paper-based or siloed within organisational hierarchies. The result is a trail of information about manufactured goods that is prone to error, fraud and loss. And these problems only get worse as supply chains get longer in a globalised world, and manufactured goods become more complex.

Blockchain technology presents a different way to govern supply chain data that centres on the movement of the good itself. Rather than passing pieces of paper between supply chain participants to track goods, information can be recorded in a decentralised blockchain. In practice goods are given a digital representation. Then as the goods move, information about them is timestamped in an immutable blockchain. Importantly this information is stored outside of organisational boundaries, making blockchain an alternative mechanism to solving the age-old problems of provenance and quality. What information is stored in a blockchain could be the historical location of a good, who produced it, how it has been stored, and who has finance on the goods.

Supply chain information extends beyond a single supply chain. To produce a complex product involves first mining raw materials, transforming those into intermediate parts, before manufacturing of the final good. Blockchains are critical here because they can track goods and components across multiple supply chains, giving more visibility and traceability deeper into complex manufactured goods.

Blockchain supply chains will leverage other frontier technologies such as the Internet of Things (IoT). Containers and products will contain sensors to record information such as GPS location and temperature. This information won’t be sent to a centralised party, but recorded cryptographically into a blockchain. This information can help consumers in verifying genuine products, assist producers in creating analytics of consumer demand and ensuring their inputs are legitimate, and governments in ensuring compliance with domestic rules and regulations.

The first and most obvious application of blockchain in supply chains has been in agricultural products such as wine, meat and seafood. The common characteristic of these goods is that they are information-rich. Information about their provenance and stewardship is often hard to verify by observing the final goods, but radically affects the price that consumers will pay.

This means the next wave of applications is likely to be other high-value information-high goods. Goods that are highly-customised, such as 3D printed medical devices, aeroplane parts and pharmaceuticals, are perfectly poised to apply blockchain technology.

Blockchain in advanced manufacturing is more than just tracking goods once they’ve been produced. We can use blockchains to coordinate the highly valuable digital files that sit behind many of these products. How can you ensure that the CAD file being 3D printed was the one originally intended? Similarly, blockchains are being used for intellectual property rights, helping to ensure compliance in an increasingly digital world.

In the physical manufacturing process itself blockchain can be used to record information about the lifecycle of manufacturing equipment. We can now have more cost-efficient and credible auditable ledgers that extend beyond organisational hierarchies.

What we have proposed here is a general movement away from intermediaries being trusted to maintain information about goods and their production, towards information governance through decentralised blockchain platforms. To be sure, many of these applications are in the trial and experimental phase. But they represent an early fundamental shift in how we organise information across the entire manufacturing supply chain.

Why Blockchain Technology Could Be the Key to Solving the Developing World’s Biggest Problems

With Darcy Allen

The core of the free market explanation for global poverty is simple and compelling: much of the world’s poor are poor because of institutional failure.

The court systems that service the bottom billion are unreliable or hard to access. The governments impose extractive taxation. The bureaucracies are corrupt.

And some institutions are simply missing in the developing world. A lack of reliable identity services makes it hard to access financial markets. A lack of property titles, as Hernando de Soto famously wrote, makes it hard to use the capital embodied in homes.

Corruption and Monopolies

These explanations are all true. But the free market response to global poverty is insipid to the point of uselessness. Faced with evidence that institutions in developing countries are corrupt, classical liberals respond: well, don’t be so corrupt.

There are other responses, of course. We sometimes adopt the Washington Consensus approach—use the levers of political globalization to force reform on unwilling populations. Or maybe we just hope for a revolution that might turn out liberal. Neither alternatives have good track records.

The problem here is that institutions tend to be monopolies. One country has one court system, one bureaucracy in charge of property titles, one authority giving out birth certificates. To get better institutions, we have to replace the corrupt old ones, and that’s hard to do, especially given the intransigence of rent-seekers who benefit from them.

Institution Innovation

What the developing world needs is a technology of institutions—a way not to replace institutions but to create more of them, experimentally and entrepreneurially.

This is what we see in the blockchain. Blockchain technology is an institutional technology that allows multiple institutions to operate in one place. It is perfectly suited to hostile institutional environments.

There’s been a lot of work, unsurprisingly, on individual blockchain applications that might be helpful for the world’s poor: supply chains, democratic governance, and identity management for example. With these applications, blockchain might allow poor countries to leapfrog some of the stages of development—a poor country might skip the creation of the centralized institutions characteristic of the rich world and instead adopt immediately decentralized ones.

These applications don’t need to replace their competitors, and they are virtually impossible for the beneficiaries of the old order to prevent.

But we think blockchain technology offers something more fundamental than these specific applications.

It offers the possibility of creating new institutions—new algorithmic legal systems, contract dispute resolutions systems, identity technologies, mutual welfare and insurance, and public goods provision—in competition with the existing set of institutions.

For instance, the invention of a smart contracting platform could compete with existing court systems, helping to overcome the problems of hold-up or counterparty risks. The contracting parties to decide which institutional structure they wish to use—the terrestrial one or a near-infinite number of new digital alternatives.

These applications do not need to replace their competitors to function. And they are virtually impossible for the beneficiaries of the old order to prevent.

Institutional Layering

We call this process institutional layering. Blockchain institutions co-exist with existing institutions, effectively layering on top.

Blockchain entrepreneurs in developing economies don’t require international aid agencies or development experts to define economic problems and try to solve them. Rather, they apply their entrepreneurial judgment and skills to define institutional problems and use blockchains to design and test new institutional solutions.

William Easterly famously outlined the distinction between “planners” and “searchers” in economic development. Development economics has been plagued by planners implementing top-down institutions that don’t match local conditions and have a raft of unintended consequences.

Instead of working within the existing institutions, entrepreneurs can use blockchain to operate more effectively.

The capacity of entrepreneurs to search, however, is constrained by the transaction costs they face and the technologies they have available. Rather than propelling institutional change through centralized planners (whether it be through conquest or special economic zones), blockchain enables a new decentralized process of search.

Rather than forming businesses within the existing institutions, entrepreneurs can use the blockchain to more effectively operate on the level of the institutions themselves. Blockchain enables institutional entrepreneurs to search by operating on the governance or “protective-tier” level of entrepreneurship.

Now entrepreneurs can search, discover, and deploy new governance mechanisms. They can attract users by better economizing on transaction costs than alternatives.

Polycentric Institutions

The process of institutional layering will also be more polycentric. Rather than having centralized institutions attempting to fit over broad groups of people within a geographical nation-state, entrepreneurs will, over time, discover the necessary levels of institutional rules within regions and across borders.

Another ongoing problem of institutional change in the developing world is aligning formal institutions with the underlying informal norms. Blockchain-based institutional layering—using governance approaches developed by local entrepreneurs—might better match the underlying norms, or what James C. Scott describes as metis.

New, digital, uncensorable, trustful institutional technologies open up enormous opportunities for decentralized economic development.

Because blockchain institutions are built from the bottom-up and draw on local entrepreneurial knowledge, we might see greater levels of institutional stickiness, where formal blockchain institutions better match underlying norms and therefore are embedded and longer-lasting.

Our argument risks techno-utopianism. We are confident that blockchain—or successor distributed ledger technologies not yet invented—might solve several institutional problems within the developing world. It will not, of course, solve all of them.

Nevertheless, the invention of a class of new, digital, uncensorable, trustful institutional technologies opens up enormous opportunities for decentralized economic development.

And it allows the same entrepreneurial creativity that has driven prosperity in the rich world to be turned to the causes of poverty in the developing world.

The use of knowledge in computers: introducing nanoeconomics

With Sinclair Davidson, Jason Potts and Bill Tulloh. Originally a Medium post.

In his 1945 essay “The Use of Knowledge in Society”, Friedrich Hayek first drew attention the knowledge problem. Information is distributed throughout an economy. No central planner can effectively bring it together.

Hayek, obviously, was talking about a human economy, where people exchange with people. But machines suffer from knowledge problems too. This is the domain of nanoeconomics — which we suggest is the study and evaluation of the economics of machine systems.

Hayek in the machine

Nanoeconomics is about human-machine exchange, and machine-machine exchange. It is the economics of distributed ledgers and artificial intelligence, of object-capability programming and cybersecurity, of ‘central planning’ in the machine, and of ‘markets’ in the machine.

As we’ve come to understand blockchains and other distributed ledger technologies as an institutional technology, we’ve also learned that not only can blockchains coordinate and govern decentralised human economies (as governments, firms and markets do) but they can coordinate and govern decentralised machine economies (or human-machine economies).

This extends what Hayek called catallaxy — the spontaneous order of the market — from the market coordination of human action to the coordination of human-to-machine and machine-to-machine economies.

Nanoeconomics is not a new idea. In their Agoric papers published in 1988, Mark Miller and K. Eric Drexler developed the idea of a computational system as a space for economic exchange. The development of object-oriented programming has created software agents, which vie for scarce resources in the machine. But right now, these agents are governed through planning, not markets. Miller and Drexler suggested an alternative: a market-based computation system. In this system:

machine resources — storage space, processor time, and so forth — have owners, and the owners charge other objects for use of these resources. Objects, in turn, pass these costs on to the objects they serve, or to an object representing the external user; they may add royalty charges, and thus earn a profit.

With global computers like the smart-contract platform Ethereum we now have the bones of such a market-based computational architecture.

Nor is the idea of an analytical layer below microeconomics a new idea. Kenneth Arrow used the word nanoeconomics for the study of single buying and selling decisions. But that line of research has been subsumed into behavioural and now neuroeconomics. Alternatively it is used to describe the economics of nanotechnology.

But in an age where we deploy digital, quasi-autonomous agents to act on our behalf, and where the traditional economic problems of opportunism, asset specificity and bounded rationality are intimately tied into cybersecurity and digital services, we have to drive our economic analysis — and our institutional choices — into the machine.

Nanoeconomics is the study of an economy of software agents, using market institutions and property rights to order computation and bid for computational resources. It is the study of choices and market exchange that occur between computational objects in object-oriented software architectures, and which are economically coordinated through blockchain infrastructure.

As Miller and his colleagues have pointed out, a key problem with ‘centrally-planned’ computation are the implications for computer security. A decentralised software economy would instead seek to operationalise tradable property rights for access to objects through the principle of least authority.

Contract theory, not choice theory

Nanoeconomics is not simply a new field of economics — it is a significant extension. Where the choice-theoretic branch of economics has managed to drive its analysis down into the brain, the contract-theoretic branch has stopped at the level of human-to-human exchange.

What do we mean by choice-theoretic and contract-theoretic? Choice theory studies why people make the choices they do. This branch has traditionally been split into macroeconomics (the study of the aggregate economy) and microeconomics (the study of individual market choices).

In recent decades many economists have sought to drive their analysis deeper into the brain. Why do they have different preferences? Behavioural economics applies psychology to economics, and even more recently neuroeconomics applies biology. The choice-theoretic branch of economics goes: macro, micro, behavioural, neuro.

The contract-theoretic branch is the economics of Ronald Coase, James Buchanan, Oliver Williamson, Friedrich Hayek, and Elinor Ostrom. This branch looks at exchanges (that is, contracts) and the human institutions we have devised to constrain or facilitate those exchanges. Firms, markets, governments, clubs and commons (and now blockchains) are institutional environments to make exchanges, sign contracts, and otherwise pursue economic goals.

Contract-theoretic economics starts with constitutional economics — the macro level structuring of political and economic choices. It applies a transaction cost approach to microeconomic analysis. And with nanoeconomics we can start look at machine agents as economic actors, making exchanges — and acting opportunistically.

As more and more of the economy becomes machine-mediated, we need to worry about the security and efficiency implications of centrally-planned machine economies. But the underlying knowledge problems are general.

We’ve previously argued that blockchains are constitutional protocols for catallactic ordering. Nanoeconomics is about how they can not only facilitate improved decentralised economic coordination for humans, but also for machines.

Should I use a blockchain?

With Sinclair Davidson and Jason Potts. Originally a Medium post.

Blockchain as a business model can be imagined in one of two ways. It can be thought of as being a new general purpose technology. This category of technologies includes electricity, transistors, computers, the internet, mobile phones, and so on. To this way of thinking a blockchain can be represented as the next generation of the internet.

But if this is how people come to think of a blockchain we believe that many are going to be disappointed. Here the blockchain would be — what economists call — a factor augmenting technology. This is the standard economic story about how technology drives economic growth. People adopt a new technology because it reduces the productions costs associated with producing a given output. Technology ‘economises’ on scarce resources. We do more with less. This is the better-stronger-faster-cheaper model that we have come to associate with new technology.

But there is a problem with this approach to blockchains.

It is not immediately obvious that a blockchain is better-stronger-faster-cheaper for many general purpose uses. If managers are looking for improvements to their back room operations they will likely be underwhelmed by what a blockchain has to offer. There are many existing database software solutions that will very likely outperform a blockchain.

Another way to think about blockchains is as an institutional technology. As The Economist magazine insightfully suggested some years ago the blockchain is a trust machine. We have argued that blockchains industrialise trust. This is where the gains to using blockchain technology originate — not that it economises on production costs, but that it economises on transactions costs — especially trust.

When Satoshi Nakamoto solved the Byzantine general’s problem he also provided a solution to what economists call the coordination problem. Historically economists have recommended the price system, bureaucracy and managerial hierarchy as solutions to coordination problems. Now we also have the blockchain.

That blockchains are fundamentally an institutional rather than a technological innovation is not mere semantics. This distinction matters because it focuses attention on what is actually driving the creative-destruction this innovation generates.

What has changed is the technology of economic coordination and governance.

In the real world there is a trade-off between the price system and bureaucracy and hierarchy. The price system provides clear incentives — prices and profits determine what should be produced, how it should be produced, and who will produce it. In bureaucracy and hierarchy, however, those high-powered incentives are missing. But large scale economic activity generates large transaction costs and a lack of trust means that prices and profits can’t weave their magic.

This is where blockchains have a competitive advantage — the decentralised ledger technology provides a platform for coordination where transactions costs are dramatically reduced and trust industrialised. In an environment of complex economic activity that previously relied on bureaucracy and management we can now have prices and profits doing their magic.

Those adopters who think blockchain is just another backroom business tool are missing the main game. The blockchain is going to be your business model.