The digital consequences of the pandemic

With Darcy WE Allen, Sinclair Davidson, Aaron M Lane, and Jason Potts. Originally a Medium post.

The global policy response to the COVID-19 pandemic has been extraordinary. We’ve seen a massive increase in government spending and social welfare programs, heavy handed policing, and some less remarked on crisis deregulation.

But the long run effect of the pandemic will be even more substantial. COVID-19 is driving far deeper, and profound, changes in the economy.

Some of these changes we can start to see already, but their full implications are still murky and distant. Nonetheless, as we argue in our book Unfreeze: How to Create a High Growth Economy After the Pandemic, the economy will not simply snap back into place. The post-COVID-19 economy will not look like the pre-COVID-19 economy.

Here we offer seven changes that have big consequences for policymakers, entrepreneurs, and employees.

1 — Digital acceleration

COVID-19 has massively accelerated the adoption of digital technology to facilitate work from home. But also shop from home, school from home, telehealth, and so on.

This digital shift is often remarked on but not well understood. Technology adoption normally follows a particular diffusion trajectory. Digital technologies that have significant scale effects must overcome behavioural and institutional resistance, and they can get stuck at take-off. This means that the productivity benefits from widespread technology adoption, especially infrastructural and production technology, can be very slow to realise.

COVID-19 arrived at a critical time in the history of technology — when a supercluster of digital technologies were forming, poised to disrupt the underlying infrastructure of the economy. This suite of digital platforms and technologies had been developing for the past several decades. But they had run into innovation constraints caused by coordination adoption problems and regulatory barriers.

In March 2020, many of these constraints suddenly vanished. The spread of online education and telemedicine, which had been until then a multi-decade process, occurred in a matter of weeks.

This was a massive, global, multisector, virtually-instantaneous coordinated adoption of digital technology. That’s utterly incredible — and perhaps unique in the history of technology adoption.

A major problem with platform technologies is to drive coordinated adoption. The pandemic did in a few weeks what decades of government effort had failed to do. Long-run that is very good. But short-run it is highly disruptive.

2 — A need for massive entrepreneurial adjustment

In Unfreeze we argue that there is an urgent need for entrepreneurs to adapt to the post-COVID-19 world. Economies are made of connections, information, contracts, webs of value, relationships. When we try to restart the economy, much of this connective tissue will be gone.

The rapid technological acceleration driven by the crisis creates its own unique needs for adaptation. We’re already seeing the formation of new consumer preferences, new types of jobs, new types of business models with new cost and demand structures, new patterns of supply, and new regulatory and legal uncertainties.

But this implies that a significant amount of human capital and physical capital (built for industrial era technologies and business models) has rapidly devalued.

The first priority for entrepreneurs in the post-COVID-19 economy will be understanding how particular markets and jobs and administrative functions have changed. For example, many restaurants have moved to take-away only. Will consumers expect those new services to continue? Much of the white-collar economy has moved to work from home. Will employees demand that continues?

Entrepreneurial skills are essential during periods of rapid change. Entrepreneurship is not something that can be supplied by governments. But it can be inhibited. Policymakers have to make sure they are facilitating — not impeding — entrepreneurial adaptation to the accelerated digital adoption triggered by COVID-19.

3 — Decentralised production and innovation

One consequence of this sudden digital uptake is increased decentralisation. With the rapid adoption of work from home — not just the technologies but the social practices — we’ve seen a shift in the locus of much economic activity from offices into homes.

This shift has several implications. One, it facilitates greater co-production of value. More household resources, including especially local information, are being mixed into production.

Two, this also shifts the sites of innovation, facilitating greater household innovation and user innovation. More innovation occurs in the commons rather than in markets and organisations. This in turn increases the need for trusted decentralised networks and, in turn, increases the demand for and use of distributed innovation technology and institutions.

Three, distributed production will require more distributed dispute resolution mechanisms. Traditional courts have been slow to adapt to the digital environment and parties will be looking to more agile forms of alternative dispute resolution.

Four, because more production and innovation is occurring in households and in the commons, this means that it is harder to measure value creation and improvements in these non-market contexts. The non-market part of the economy will increase in apparent scale. So our industrial era measurements of economic activity (like GDP) will need to catch up with these new digital era realities of value creation.

This new institutional economic order will require a new economics to make sense of these new patterns of consumption and production, and new digital forms of capital and value creation.

4 — Powered-up economic evolution

The pandemic is a selection filter. As the precursor and mechanism of many of these changes, the economic consequence of the economic policy response to the viral pandemic is a powerful evolutionary selection mechanism passing over the global economy and through each sector.

This brutal selection mechanism is causing job losses, contract terminations or renegotiations, demand reductions, business closures and bankruptcy, fire sales, credit shrinkage, asset repricing, factor substitution, and other distinct forms of economic destruction that will play out over the coming months and years.

This hard evolutionary selection mechanism is also a filter. It will kill off some things disproportionately and let other things pass through. Most obviously, digitally enabled businesses and sectors will do better, because they are more well-adapted to the new environment. Bigger firms with better capitalisation (or better political connections) will do better, and smaller firms will be selected against.

In labour markets some positions are more vulnerable than others, particularly part-time workers or contractors. While many workers and firms are on temporary support through public sector subsidy of wages or quasi-partial nationalisations, a proportion of those positions or organisations being kept alive will die as soon as support is removed. There are many zombies already.

Similarly, there will be a lot of bad debt on company books (and thereby in banks) that will be realised in market revaluations over coming periods. These collapses will release resources for subsequent entrepreneurial reconstitution and reinvention.

But we should also expect consolidation of existing markets and resources among surviving players. This may actually result in higher growth and profits among large adaptive companies — particularly technology driven companies. So a period of global economic destruction is not inconsistent with a booming share market.

5 — The twilight of conventional macroeconomic policy

At the same time, COVID-19 looks to fundamentally break the standard monetary and fiscal policy levers that have been used to manage business cycles over the twentieth century.

From a public finance perspective, the magnitude of the committed policy actions is already unprecedented. The levels of public debt that are planned in order to deal with this crisis — the policies to subsidise wages, provide rent and income relief, bail out companies, etc in order to avoid market catastrophe — are the largest that has ever been experienced. Moreover, these actions are being taken during a massive collapse in tax receipts. The implications for public finance are catastrophic, with a huge increase in public debt, a vastly worse central bank balance sheet, and looming inflation.

The result is a policy challenge that far exceeds capabilities of traditional monetary and fiscal levers. We will require institutional policy reforms to deal with the crisis. But institutional policy designed to free-up the supply side of the economy, to lower the costs and constraints on businesses, is politically much harder to achieve.

Indeed, the limits of these policy levers reveals the extent to which government administration (e.g. of money, of asset and property registries, of identity, of regulation and governance) is still the foundation of a modern economy. The pandemic has brought into sharp relief the limits and constraints of this centralised public infrastructure and the technocratic foundations of the macroeconomic policy mechanisms built upon them.

The real alternative to conventional policy levers isn’t different policies (like quantitative easing, negative interest rates, or universal basic income) but better institutional technologies. We’ve been looking in the past few years at distributed digital technology (that is, blockchain) that offers a new administrative and governance base layer of the economy (see herehereherehere and here to start).

A digital infrastructure base layer of industry utilities and digital platforms would provide a far more agile foundation for targeted economic policy and entrepreneurial adaptation.

6 — A new global trading order

One of the most powerful institutional forces over the past several centuries, and which has underpinned global economic prosperity in the industrial era, was the development of global trading infrastructure for commodities and capital. It was built around the Westphalian system of nation-state record-keeping and intra-nation state treaty-based institutional governance (i.e. trade zones). But it has come to a virtual halt in the crisis.

In the short and medium term the global trading order will rebuild around a different order, namely provable health identity and data to facilitate the safe movement and interaction of people. Where that can safely happen, so can economic activity. Health zones can become the basis for trade zones. Australia and New Zealand are already talking about a “health bubble”. It would be easy to include other highly successful health economies — Taiwan, Japan, Germany, potentially Hong Kong and Singapore, some Pacific Island nations.

Green zones (or cordon sanitaire) have long been used in pandemics and have once again been proposed as a way to exit lockdown. As the health zone grows, so can the trade zone. Economic zones can then free ride on the decentralised identity and data infrastructure created to build a health zone. The result will be the redrawing of physical and network boundaries, even eliminating artificial economic borders, to create integrated trade zones.

7 — A new political order

The costs of COVID-19 do not fall evenly across the population. The health risks fall heavily on some groups (the elderly and those with co-morbidities), and the costs of economic lockdown fall on different groups and will be felt differently. The differential impact by sector, jobs, education, human capital investments or physical or financial capital write-downs shape how the costs are distributed across society.

The virus imposes huge private costs that will be in part socialised through political bargaining. The outcome of these politically mediated bargains and transfers that will shape politics for years to come.

But the pandemic also shifts some of the anchor points of political economy. The sudden growth of the welfare state, of unemployment insurance and wage-support, of healthcare provision and childcare, even of social housing are unlikely to be easily rolled back. So there will be a higher demand for social welfare safety nets.

But to pay for this, along with the urgent need to address the huge deterioration of public balance sheets, economic policy will need an aggressive pro-market agenda to unleash economic growth. Politically, this is a pivot to the centre with very ‘dry’ economic policy and ‘wet’ social policy — what was called ‘third way’ in the 1990s.

The counterpoint to that centre-pivot is that many of the high-cost political projects of both the right and the left will be abandoned. Reduced economic growth means we can afford fewer of the luxuries of advanced capitalism.

This is a vision of a new kind of social-digital capitalism to be built after the reset — from the government-led physical infrastructure of the industrial era, to a digital era built on private, open and communally developed technology platforms.

Finally

The economic consequences of the COVID-19 pandemic are mostly currently being discussed as a macro policy response to dealing with the economic destruction that the public health strategy necessitates. This is talk of the V-shaped, U-shaped, L-shaped or W-shaped recoveries. In Unfreeze we wrote of the need for a square root shaped recovery — after the reopening, we’ll need a long period of high economic growth to return to the prosperity of 2019.

But here we’ve gone further. COVID-19 is driving structural evolutionary change in the economy. The accelerated adoption of digital economic infrastructure during the crisis will leave a lasting mark on the political and economic system of the future.

Look at our history: protectionism doesn’t work

With Vijay Mohan

We rarely think about supply chains – those immensely complex networks of production and logistics that structure the economy. 

That has changed. Early in the COVID-19 crisis, we learned that Australia imports much of its basic medical equipment like facemasks and other protective gear. As borders were being closed importing this high-demand equipment got suddenly very hard.  

Now there is an unsurprising clamour for the government to take more of an interest in how our supply chains actually work, and to use the traditional tools of protectionism to encourage domestic production of medical equipment and pharmaceuticals.  

Prime Minister Scott Morrison said in April that “we need to look very carefully at our domestic economic sovereignty”. 

But neo-protectionism to secure Australia’s supply chains would be a grave mistake – and it fundamentally gets the supply chain challenge wrong. 

First, the obvious but necessary point. We actually had a protectionist economy for most of the twentieth century. And we didn’t build facemasks. We built cars. We built cars because cars had a certain romance in the twentieth century and Labor and the union movement wanted to lock in prestigious manufacturing jobs for their supporters. 

This has always been one of the central planks of the case against protectionism. The choice of what industries to protect is not made by all-knowing and benevolent leaders, but by self-interested politicians. They get to the top of their profession not because they are skilled production managers or supply chain coordinators, but because they’re great at navigating political factions and going on television. 

Of course, our national leaders will come out of this crisis more focused on the risk of future pandemics, and more motivated to prepare our economy for this now-known risk. But as they say in the military, generals too often prepare for the last war, not the next one. We don’t need an economic system that is prepared for a crisis that looks exactly like COVID-19. We need an economic system that is prepared for an unexpected crisis – which, definitionally, could be anything. 

Indeed, it is the fact that the pandemic was unexpected to most in government that makes the strongest case for free trade. The crisis has caused a lot of market disruption. But global supply chains have adjusted remarkably well to new demands and routed around new constraints. For example, airlines have been doing temporary conversions of passenger planes to cargo planes – particularly important because medical equipment, which in normal times would be leisurely transported by ship, needs to get to new COVID-19 hot spots urgently. 

Protectionism invariably makes the industries it protects brittle and highly politicised, not agile and adaptable to sudden economic shocks. And it is a fantasy to suggest that a small, wealthy, highly-educated nation like Australia could or should ever be self-reliant in the production of all low-value goods that might be needed in unexpected crises. 

There are things the government can do to be prepared for the next crisis. Rather than making essential products, we can buy them and store them. This requires no more foresight than full-blown protectionism and is a lot cheaper. The idea of keeping extensive national stockpiles of equipment for emergencies is uncontroversial. By all accounts, the National Medical Stockpile has been an immensely valuable asset during COVID-19. 

With our RMIT colleague Marta Poblet, we have been looking at the problems consumers had getting reliable information on supply chain security in the first weeks of the crisis.  

Before the pandemic, Australian industry was interested in using new technologies (such as blockchain, 5G communication, and smart devices) to better combat food fraud in export markets or to how to prove to their customers that their products were organic or fair trade certified.  

But the pandemic revealed a more basic problem with about supply chain information. Consumers were not worried about quality or fraud. They were worried there were not enough goods available to meet demand at all – hence the panic buying of toilet paper, hand sanitizer, and dried pasta.  

This panic buying looked a lot like the sort of panic withdrawals you see in a bank run. If depositors aren’t convinced their bank is solvent, they rush to be the first to get their money out. And as we saw, Scott Morrison was no better able to convince shoppers that there were adequate domestic supplies of toilet paper in March 2020 than South Australian premier Don Dunstan was able to convince the customers of the Hindmarsh Building Society that there were adequate funds to cover deposits October 1974 — despite standing in the street outside its headquarters with a megaphone.  

In moments of high-stress consumers just don’t trust the political assurances they are given. Do we really blame them? 

Ultimately within a few weeks supply chains adjusted. Coles and Woolworths lifted their toilet paper sale limits. 

But the toilet paper panic symbolises the choice we now face when it comes to supply chain resilience. To go protectionist would be to trust our supply chains to the same political class that we simultaneously accuse of being underprepared for COVID-19. Or we could lean into free trade and open markets. We should encourage entrepreneurs to adapt rapidly to new circumstances, to experiment with new technology, and let them figure out how to operate in a disrupted global economy. 

Australia has a long history of protectionism. Let’s try to remember what we learned. 

The COVIDSafe app was just one contact tracing option. These alternatives guarantee more privacy

With Kelsie Nabben

Since its release on Sunday, experts and members of the public alike have raised privacy concerns with the federal government’s COVIDSafe mobile app.

The contact tracing app aims to stop COVID-19’s spread by “tracing” interactions between users via Bluetooth, and alerting those who may have been in proximity with a confirmed case.

According to a recent poll commissioned by The Guardian, 57% of respondents said they were “concerned about the security of personal information collected” through COVIDSafe.

In its coronavirus rewhy sponse, the government has a golden opportunity to build public trust. There are other ways to build a digital contact tracing system, some of which would arguably raise fewer doubts about data security than the app.

All eyes on encryption

Incorporating advanced cryptography into COVIDSafe could have given Australian citizens a mathematical guarantee of their privacy, rather than a legal one.

A team at Canada’s McGill University is working on a solution that uses “mix networks” to send cryptographically “hashed” contact tracing location data through multiple, decentralised servers. This process hides the location and time stamps of users, sharing only necessary data.

This would let the government alert those who have been near a diagnosed person, without revealing other identifiers that could be used to trace back to them.

It’s currently unclear what encryption standards COVIDSafe is using, as the app’s source code has not been publicly released, and the government has been widely criticised for this. Once the code is available, researchers will be able to review and assess how safe users’ data is.

COVIDSafe is based on Singapore’s TraceTogether mobile app. Cybersecurity experts Chris Culnane, Eleanor McMurtry, Robert Merkel and Vanessa Teague have raised concerns over the app’s encryption standards.

If COVIDSafe has similar encryption standards – which we can’t know without the source code – it would be wrong to say the app’s data are encrypted. According to the experts, COVIDSafe shares a phone’s exact model number in plaintext with other users, whose phones store this detail alongside the original user’s corresponding unique ID.

Tough tech techniques for privacy

US-based advocacy group The Open Technology Institute has argued in favour of a “differential privacy” method for encrypting contact tracing data. This involves injecting statistical “noise” into datasets, giving individuals plausible deniability if their data are leaked for purposes other than contact tracing.

Zero-knowledge proof is another option. In this computation technique, one party (the prover) proves to another party (the verifier) they know the value of a specific piece of information, without conveying any other information. Thus, it would “prove” necessary information such as who a user has been in proximity with, without revealing details such as their name, phone number, postcode, age, or other apps running on their phone.

Not on the cloud, but still an effective device

Some approaches to contact tracing involve specialised hardware. Simmel is a wearable pen-like contact tracing device. It’s being designed by a Singapore-based team, supported by the European Commission’s Next Generation Internet program. All data are stored in the device itself, so the user has full control of their trace history until they share it.

This provides citizens a tracing beacon they can give to health officials if diagnosed, but is otherwise not linked to them through phone data or personal identifiers.

Missed opportunity

The response to COVIDSafe has been varied. While the number of downloads has been promising since its release, iPhone users have faced a range of functionality issues. Federal police are also investigating a series of text message scams allegedly aiming to dupe users.

The federal government has not chosen a decentralised, open-source, privacy-first approach. A better response to contact tracing would have been to establish clearer user information requirements and interoperability specifications (standards allowing different technologies and data to interact).

Also, inviting the private sector to help develop solutions (backed by peer review) could have encouraged innovation and provided economic opportunities.

How do we define privacy?

Personal information collected via COVIDSafe is governed under the Privacy Act 1988 and the Biosecurity Determination 2020.

These legal regimes reveal a gap between the public’s and the government’s conceptions of “privacy”.

You may think privacy means the government won’t share your private information. But judging by its general approach, the government thinks privacy means it will only share your information if it has authorised itself to do so.

Fundamentally, once you’ve told the government something, it has broad latitude to share that information using legislative exemptions and permissions built up over decades. This is why, when it comes to data security, mathematical guarantees trump legal “guarantees”.

For example, data collected by COVIDSafe may be accessible to various government departments through the recent anti-encryption legislation, the Assistance and Access Act. And you could be prosecuted for not properly self-isolating, based on your COVIDSafe data.

A right to feel secure

Moving forward, we may see more iterations of contact tracing technology in Australia and around the world.

The World Health Organisation is advocating for interoperability between contact tracing apps as part of the global virus response. And reports from Apple and Google indicate contact tracing will soon be built into your phone’s operating system.

As our government considers what to do next, it must balance privacy considerations with public health. We shouldn’t be forced to choose one over another.

This silent deregulation must become a pillar of recovery

The COVID-19 pandemic has seen a massive expansion of the power of the state – heavy-handed police action and huge increases in government spending are just the most obvious.

But at the same time, the crisis has also seen a major retreat of state power in other areas – a wave of deregulation across the economy that has almost no historical parallel. And these regulatory reforms offer us a path back to prosperity.

The most obvious regulatory reductions have been on the medical frontline. Some controls over the production and use of medical face masks, ventilators, virus testing and pathology have been relaxed. Supervision requirements have been reduced for nurses re-entering the workforce. Regulations have been eased to allow distilleries to produce alcohol-based hand sanitiser.

But the most consequential deregulations have been intended to keep the economy afloat. Night-time curfews on delivery trucks have been lifted to ensure supermarkets can be more easily restocked, and trading and operating hours restrictions for essential retail have been eliminated. Liquor licensing has been relaxed to allow restaurants and bars to do home-delivered alcohol. Construction work can now be done on weekends and public holidays to make up for productivity losses that might come from trying to build while social distancing.

Other reforms have involved the government relaxing its most burdensome regulations. The Australian Prudential Regulatory Authority has eased capital requirements on banks. The Australian Competition and Consumer Commission is reducing its enforcement and surveillance program, announcing that it would now “carefully consider the impact on businesses already under pressure” (this is great, but at the same time reveals a lot about their attitude before the pandemic).

The Australian Securities and Investment Commission has even put a hold on the program that embeds bureaucrats in private companies. This is the program introduced after the financial services royal commission that has government-appointed psychologists observing the ethical standards of senior management. It was widely derided as “shrinks in the boardroom” – and it is no longer active because of COVID-19.

The rules we didn’t need

Even more astonishingly, the communications regulator has suspended Australian content requirements on commercial television and pay TV. It would be hard to nominate a more heavily defended and politically sensitive bunch of regulations. And they have now been shelved with almost no comment.

For the past two decades Australian governments have repeatedly announced red tape reduction programs. Regulatory reform has been a major plank of the Coalition government’s agenda. It was a major plank of the Labor government before it. But none of those heavily promoted programs have had as much scope and scale as the COVID-19 deregulations.

Those earlier red tape reduction programs focused on the sorts of regulations that nobody was interested in defending. They tended to eliminate lots of minor rules rather than significant ones. The guiding principle has been quantity not quality. Ultimately they were less major economic reform and more tidying up the statute books.

But this time is different. The regulations that have been suspended are precisely those that are most burdensome. They are the rules that are most costly to comply with but also least essential to support a functioning economy.

In other words, they are the rules that governments worried about the effect of over-regulation on productivity and economic growth should be very reluctant to reinstate.

This is the conversation to have now. The pandemic is moving from urgent crisis stage to risk-management stage. The Reserve Bank governor warns that we are looking at the greatest hit to the economy since the Great Depression. We need to start thinking about what policy settings will be able to revive the relative prosperity we enjoyed at the end of 2019 – and pay for all the spending that the government has committed to.

Deregulations must stay

Making these temporary deregulations permanent should be one of the pillars of recovery. We cannot assume that the economy will happily bounce back once social distancing controls are lifted. The damage inflicted by the shutdown on business models and supply chains has made this naïve hope impossible. The economy needs to adapt to the post-pandemic world – quickly. Regulations that prevent this rapid adaptation or prevent firms from establishing new sustainable business models need to be culled.

In a 2016 paper published in the European Journal of Political Economy, the economist Christian Bjørnskov looked at how economic freedom (that is, low taxes and minimal regulation) affected how different countries performed during an economic crisis. He found that how heavily a country was regulated predicted how quickly it recovered from crisis – the less regulation, the quicker the recovery.

A lot of the growth in government is likely to survive after the COVID-19 pandemic. It will be politically hard to abolish free childcare or to return Newstart payments to where they were. But we’re going to need a much more productive and prosperous economy to pay for it all. So the deregulations done during the crisis should be locked in too. And the principles that have been established during this crisis – that many politically popular regulations make it hard for businesses to adapt to unexpected circumstances and keep people employed – will be needed to guide our policymakers when they return.

As Scott Morrison has said, all workers are essential. But not all regulations are.

Cryoeconomics: how to unfreeze the economy

With Darcy Allen, Sinclair Davidson, Aaron Lane and Jason Potts. Originally a Medium post.

The Australian government, like many governments around the world, wants to freeze the economy while it tackles the coronavirus pandemic. This is what the Commonwealth’s JobKeeper payments and bailout packages are supposed to do: hold workers in place and keep employment relationships together until mandatory social distancing ends.

Easier said than done. We are in completely uncharted territory. We’ve never tried to freeze an economy before, let alone tried to thaw it out a few weeks or months later. That’s why our new project, cryoeconomics, looks at the economics of unfreezing an economy.

To understand why this will be so hard, think of an economy as a remarkably complex pattern of relationships. Those relationships are not only between employees and employers, but also between borrowers and lenders, between shareholders and companies, between landlords and tenants, between producers tied together on supply chains, and between brands and tastemakers and their fans.

The patterns that make up our economy weren’t designed from above. They evolved from the distributed decisions of consumers and producers, and are shaped by the complex interaction between the supply of goods and services and their demand.

The problem is that the patterns the government plans to freeze are not the patterns we will need when they finally let us thaw.

When the government decides to pull the economy out of hibernation, the world will look very different. As a simple example, it’s quite possible that many Australians, forced to stay home rather than eat out, discover they love to cook. This will influence the demand for restaurants at the end of the crisis. On the other hand, our pent-up desire for active social lives might get us out into the hospitality sector with some enthusiasm. There will be drastic changes because of global supply chain disruptions and government policies. These changes will be exacerbated by the fact that not all countries will be unfrozen at the same time.

The upshot is that the economy which the government is trying to hibernate is an economy designed for the needs and preferences of a society that has not suffered through a destructive pandemic.

Unfreezing the economy is going to be extremely disruptive. New patterns will have to be discovered. As soon as the JobKeeper payments end, many of the jobs that they have frozen in place will disappear. And despite the government’s efforts, many economic relationships will have been destroyed.

Yet there will also be new economic opportunities — new demands from consumers, and new expectations. Digital services and home delivery will no doubt be more popular than they were before.

These disruptions will be unpredictable — particularly if, as we expect, the return to work is gradual and staggered (perhaps according to health and age considerations or access to testing).

As we unfreeze, the problem facing the economy won’t primarily be how to stimulate an amorphous ‘demand’ (as many economists argue government should respond to a normal economic recession) but how to rapidly discover new economic patterns.

It is here that over-regulation is a major problem. So much of the laws and regulations imposed by the government assume the existence of particular economic patterns — particular ways of doing things. Those regulations can inhibit our ability to adjust to new circumstances.

In the global response to the crisis there has already been a lot of covert deregulations. The most obvious are around medical devices and testing. A number of regulatory agencies have stood down some rules temporarily to allow companies to respond to the crisis more flexibly. The Australian Prudential Regulatory Authority is now willing to let banks hold less capital. The Australian Securities and Investment Commission has dropped some of its most intrusive corporate surveillance programs.

The deregulatory responses we’ve seen so far relate to how we can freeze the economy. A flexible regulatory environment is even more critical as we unfreeze. Anything that prevents businesses from adapting and rehiring staff according to the needs of the new economic pattern will keep us poorer, longer.

Today the government is focused on fighting the public health crisis. But having now turned a health crisis into an economic crisis, it must quickly put in place an adaptive regulatory environment to enable people and businesses to discover what a post-freeze economy looks like.

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.