The Long Shadow Of The Future


Steven Weber is a professor at the school of information and the department of political science at the University of California, Berkeley.

Nils Gilman is the deputy editor of Noema Magazine.

We’re living through a real-time natural experiment on a global scale. The differential performance of countries, cities and regions in the face of the COVID-19 pandemic is a live test of the effectiveness, capacity and legitimacy of governments, leaders and social contracts.

The progression of the initial outbreak in different countries followed three main patterns. Countries like Singapore and Taiwan represented Pattern A, where (despite many connections to the original source of the outbreak in China) vigilant government action effectively cut off community transmission, keeping total cases and deaths low. China and South Korea represented Pattern B: an initial uncontrolled outbreak followed by draconian government interventions that succeeded in getting at least the first wave of the outbreak under control.

Pattern C is represented by countries like Italy and Iran, where waiting too long to lock down populations led to a short-term exponential growth of new cases that overwhelmed the healthcare system and resulted in a large number of deaths. In the United States, the lack of effective and universally applied social isolation mechanisms, as well as a fragmented healthcare system and a significant delay in rolling out mass virus testing, led to a replication of Pattern C, at least in densely populated places like New York City and Chicago.

“Regime type isn’t correlated with outcomes.”

Despite the Chinese and Americans blaming each other and crediting their own political system for successful responses, the course of the virus didn’t score easy political points on either side of the new Cold War. Regime type isn’t correlated with outcomes. Authoritarian and democratic countries are included in each of the three patterns of responses: authoritarian China and democratic South Korea had effective responses to a dramatic breakout; authoritarian Singapore and democratic Taiwan both managed to quarantine and contain the virus; authoritarian Iran and democratic Italy both experienced catastrophe.

It’s generally a mistake to make long-term forecasts in the midst of a hurricane, but some outlines of lasting shifts are emerging. First, a government or society’s capacity for technical competence in executing plans matters more than ideology or structure. The most effective arrangements for dealing with the pandemic have been found in countries that combine a participatory public culture of information sharing with operational experts competently executing decisions. Second, hyper-individualist views of privacy and other forms of risk are likely to be submerged as countries move to restrict personal freedoms and use personal data to manage public and aggregated social risks. Third, countries that are able to successfully take a longer view of planning and risk management will be at a significant advantage.

The Case of Taiwan

Arguably, Taiwan has had the single most successful response to the coronavirus pandemic. Closely linked to mainland China, where the virus first appeared in late 2019, it could easily have had a disastrous experience with COVID-19. Hundreds of thousands of Taiwanese work in China, and over a thousand flights go between the island and the mainland each week. Taiwan recorded its first case of coronavirus on Jan. 21 (by coincidence, the same day the U.S. recorded its first case, in Washington) — a 55-year-old woman returning from her job in Wuhan, the epicenter of the outbreak.

Taiwan has a vigorous democratic political culture that places a great premium on popular participation in politics and respect for civil liberties, factors which some have claimed inhibit the effective governmental response to emergency situations like epidemics. According to some scholars, Taiwan’s political system and culture explain its chaotic response to the SARS epidemic of 2003. It’s also worth noting that, in deference to China’s sovereignty claims over Taiwan, the World Health Organization offered the country no assistance against COVID-19 and underutilized the data it provided.

Nevertheless, Taiwan’s response to the novel coronavirus outbreak has been exemplary. First, it rapidly instituted border controls. Immediately after China reported to the WHO on Dec. 31 that it was experiencing a high-fatality novel virus outbreak, Taiwan began inspecting plane passengers coming from Hubei’s capital, Wuhan; two days after its first case was recorded, Taiwan banned all Wuhan residents from entry. Two days after that, it suspended tours to China, and by Feb. 6, it had banned all Chinese visitors.

To quell community spread, it then instituted a rigorous program of testing, tracking and isolation of anyone who had been exposed to the infection. It also centralized control over the distribution of personal protective equipment, while rapidly ramping up production. The result is that Taiwan has recorded less than 450 cases and only seven deaths, despite the continued arrival of infected citizens returning home from overseas. Arguably no country has performed better, and this against long odds.

Crucial to Taiwan’s success in the face of the COVID-19 pandemic has been the fact that the most important decisions have been handed to experts. Even before its first case was recorded, the government activated its Central Epidemic Command Center and directed it to integrate resources and coordinate the response across government agencies. Taiwan also has a “meme engineering team” searching for online misinformation or disinformation regarding the coronavirus and trying to offer a clarification to the public within an hour. The vice president is even an epidemiologist.

The Taiwanese government also took a proactive role around the economic and distributional questions related to the epidemic, enforcing rigorous screening at the borders as well as monitoring and controlling the movement of goods. The government made a mantra of the phrase “centralized procurement, centralized distribution and centralized pricing” — while tracking production and inventories to ensure dependable domestic supplies. There was also an activist approach to manage equity and foreign exchange markets and to initiate bailout measures for impacted industries, particularly transportation, tourism and leisure.

While one shouldn’t put too much stock in a single case study, Taiwan exemplifies several long-term patterns in governance that may be strengthened coming out of the COVID-19 pandemic. Specifically, Taiwan’s success in combating COVID-19 resulted from a combination of strong, effective governmental action by a high-capacity state manned by operational experts, a willingness to prioritize collective risk and burden-sharing over hyper-individualism and a commitment to taking a long view of planning for potentially catastrophic risks.

Revaluing Operational Expertise

One of the less-positive effects of digital social media over the last decade has been to contribute to a set of mythologies about the special value of ideas. Ideas are of course powerful and ultimately the source of innovation and social change, but the pandemic is revealing a sharp difference between power and value. In a landscape where there are plenty of ideas — good and bad and mixed in terms of quality, and often hard to distinguish — value tends to migrate toward what is relatively scarce. And what’s been shown to be relatively scarce right now is competent operational expertise.

Put simply, ideas are cheap and easy to create and distribute — never more so than on social media platforms. But really knowing how to get things done effectively requires a set of capabilities that are difficult to create, expensive to maintain and improve, and not something you describe in 280 characters. Pandemics and other mass emergencies and mobilizations like wars demonstrate the difference in sharp relief. The ability to execute becomes visibly more important than the ability to ideate. What’s more, the best ideas are rarely discovered in isolation from practical implementation. Improvement depends on concrete feedback from what happens when ideas are put into practice in the world. What works and what doesn’t reveals itself to operators before (and often more clearly than) it reveals itself to idea generators.

Sally Deng for Noema Magazine

This isn’t a backdoor defense of technocracy or conventional political experts and elites. Rather, the sorts of technical experts we’re talking about are the process technicians who mostly aren’t even considered technocrats. Dwight Eisenhower didn’t see himself as an ideas guy but as a military operator whose practical expertise helped the U.S. win a world war. John F. Kennedy may have had the idea to put an American on the moon, but it was the engineers at NASA, most with military backgrounds, who made themselves heroes through painstakingly detailed technical development, including learning from (sometimes fatal) mistakes.

These kinds of experiences are an important reason why, in the U.S. and many other countries, the military is one of the most highly respected modern institutions. Anyone can be an armchair grand strategist. But moving half a million people and their equipment halfway around the world in order to take on enemies under the most demanding and dangerous conditions requires extraordinary operational expertise. Managing the functioning of an aircraft carrier — essentially a floating city under constant threat of attack — requires extraordinary operational expertise. Building a fully functional hospital in two weeks or suddenly quadrupling the production of ventilators requires not new ideas but operational experience and effectiveness.

The people who make these semi-miracles happen don’t have conventional elite status in the U.S., but they are the kind of technocrats whose expertise is coming to the fore in this crisis. Operational experts might not develop the conceptual apparatus to elegantly describe a supply chain to a non-expert audience, but they are the ones who know how to operate it and adapt it under stress. Hospitals don’t need theories about healthcare reform right now — they need people who can intubate critical care patients and manage ventilators at scale under extraordinary stress. The ability of Amazon, Safeway and FedEx, among others, to maintain continuity of food supplies and deliver essential products to people’s homes doesn’t depend on big ideas — it depends on operational expertise and people who know how to get things done.

“What’s been shown to be relatively scarce right now is competent operational expertise.”

The venture capital world has known this for a long time. The popular image of venture capital partners as geniuses with incredible foresight who gain advantage by having better ideas than everyone else makes for good storytelling, but it isn’t close to what’s mostly a much grittier reality. Successful venture investors bet on people who have shown they can execute — people who have built businesses, managed teams, brought products to market and overcome everyday practical adversities to navigate the convoluted path to implementation. As Michael Dell observed: “Ideas are a commodity. Execution of them is not.”

At least for a period of time (a decade?), we expect there will be a shift in valence in favor of people who demonstrate the capacity to get stuff done. This could reshuffle the social hierarchy among job categories: Will it be better to be a knowledge worker or a supply-chain specialist? This shift could give rise to greater accountability and a revival of key performance indicators: Quantitative measures of productivity make more sense for operational executors than for idea generators. It could have ripple effects on education systems and curricula: Might advanced vocational training in community colleges become more valuable, and valued, than humanities or even STEM bachelor’s degrees? Compound the effects of a rebalancing like this over a decade, and you have a different status ladder and leadership model for modern societies.

Revaluing Risk: Libertarian Twilight?

The U.S. over the last few decades has seen a coupling of two strands of thought — the individualization of risk and the protection of individual privacy. These have been driven by distinct communities of activists and intellectuals. On one side, some economists and political scientists and their followers argued that only individuals understand their own risk preferences and therefore individuals are better placed to manage them than any institutional actors. 

On another side, privacy activists (sometimes invoking human rights) have sought to protect personal data from the gaze of government actors and, to a lesser extent, from the private sector as well. What both sides shared was a deep-seated suspicion of government and the connected belief that the key to protecting individuals was to limit the capacity of the state. Over the past 50 years, these activists and politicians have led a concerted and partially successful campaign to hobble the state.

The notion of socialized risk was an important foundational element of the post-New Deal U.S. welfare state. But since the 1980s, risk-sharing via government programs has been systematically eroded in the name of avoiding moral hazards, improving efficiency and incentivizing the individual. Individuals have been increasingly saddled — or empowered, depending on your assessment — with managing their own financial, employment, health, retirement and, in some cases, even security risks.

Motivations for this shift began with a fundamental disillusionment with government institutions designed to manage collective risk and the belief that these institutions were inherently inefficient, wasteful and often corrupt. Over time, people began to wonder if risk decisions are some of the most important determinants of individuals’ opportunities to improve their quality of life, then shouldn’t a society that calls itself liberal place those choices in the hands of the person who understands the stakes the best — the individual herself?

The policies these arguments helped to incubate showed positive results in some domains, notably in the digital technology sector. Over time, the ambitions of the risk de-socializers grew. When they encountered resistance, they tended to dismiss objections as naively moralistic or simply uninformed about the inherent inefficiency and corruption of public sector institutions tasked to manage collective risk. Even as we were busy constructing a massively interdependent world of global flows that cut across national political borders, there was also a relentless push to make individuals the sole bearers of the risks generated by that system.

This raised a deeper question: Are there categories and situations where collective risk is unavoidably baked into reality and where trying to disaggregate that risk into individual micro-foundations is impossible? Hyper-individualists tend to presume that the answer to that question is no. When individuals prove themselves manifestly unable to manage their own risks, the proposed fixes focus on nudges to individual risk behaviors without questioning the foundational assumptions of the model.

What the COVID-19 pandemic is revealing in stark terms is the limits of the individualist model of risk allocation. The lack of universal health insurance and a shared minimum standard of care in the U.S. may or may not be a reasonable way to spur medical innovation and ensure adequate consumer choice, but it is unquestionably making it harder to manage the coronavirus pandemic. Likewise, the lack of a well-cushioned unemployment scheme may or may not be a good way to keep people focused on getting and keeping their jobs, but when tens of millions of people are suddenly thrown out of work because of social distancing regulations, the limits of minimizing collective risk-sharing become glaringly obvious.

The other side of the individualist agenda concerns ongoing debates about privacy in the digital era. Privacy advocates tend to focus intensively on the risk that data flows, breaches and misuse pose to individuals. Privacy advocates tend to recount lurid fantasies of the worst possible slippery-slope outcomes, often to the exclusion of any kind of social risk-benefit calculation. George Orwell’s Big Brother and Cold War memories of the Stasi cast a long shadow over these discussions.

“The COVID-19 pandemic is revealing in stark terms the limits of the individualist model of risk allocation.”

The same imbalance has shaped the debate over healthcare data. It’s almost too easy to construct nightmare scenarios about the range of risks that individuals could face if their sensitive personal healthcare data were used without restrictions, to discriminate against them and reduce the cost burden on insurance. But what about the social risk-benefit calculations that aggregated health-relevant data permit? The future of evidence-based medicine rests on the ability to aggregate and employ that data at scale. Anonymization and other forms of protecting personal data notwithstanding, the debate has generally been much louder about the potential negative risks of data misuse for individuals than it has been about the risk-benefit ratio for the population at large.

This is where the COVID-19 pandemic has begun and will continue to change the discourse. Where you have been and who you have been close to over the past two weeks is a dataset that most privacy advocates shudder to imagine making available to governments. (Of course, that data is already available to private-sector players like mobile network operators, device manufacturers, service providers and others.) But government use of centralized data has been key to enabling places like South Korea, Singapore and Taiwan to outperform on coronavirus infection control. That data represents a public health treasure trove that has massive potential benefits for managing collective risk.

Despite its democratic credentials and open political culture, Taiwan unflinchingly curtailed privacy and individual liberty in the service of protecting public health during the COVID-19 epidemic. Individuals under isolation or quarantine orders — either because they returned from abroad or because they had contact with an infected person — had their cell phones tracked and were immediately accosted by police if they left their homes or turned off their phones. People breaking quarantine rules face heavy fines. Universal, centralized healthcare records enabled the government to ensure that everyone complied with the rule that they purchase no more than three facemasks a week per adult. The government also threatened to prosecute purveyors of disinformation and fake news concerning the pandemic.

The transparency of the Taiwanese government’s decision-making about why it instituted these measures, as well as its willingness to countenance debates over them, also helped to reassure its citizens that these personal liberty-inhibiting measures will be relaxed once the crisis passes. The operational competence of the Taiwanese government earned it the performance legitimacy that inclines the population to give the government the benefit of the doubt about the necessity of such measures.

As the differential responses to coronavirus come to demonstrate the effectiveness of centralized national health record systems and even “under-the-skin surveillance” (as historian Yuval Harari put it) for stemming the flow of the pandemic, citizens are likely to accept or even demand the pooling of health information to deal with other health risks, from oncology to sexually transmitted diseases. A rebalancing of the tradeoff between individual and collective risk, again compounded over a decade, would make for a trajectory in areas like public health, finance and beyond that might make 2030 look as different from 2020 as 2020 looks from 1980.

Lengthening The Shadow Of The Future

In 2004, the U.S. National Intelligence Council’s quadrennial global trends report warned that “some experts believe it is only a matter of time before a new pandemic appears, such as the 1918-1919 influenza virus that killed an estimated 20 million worldwide.” This, the report continued, could “put a halt to global travel and trade during an extended period, prompting governments to expend enormous resources on overwhelmed health sectors.”

Poor policy reactions to the COVID-19 pandemic aren’t the result of a failure of imagination; the pandemic was not a black swan event, and it was not unpredictable. It was entirely foreseeable — and foreseen — by a wide variety of government, business, medical and other foresight professionals. For years, the World Economic Forum hosted pandemic preparedness planning events. Even if we didn’t know when and precisely how, we knew something like COVID-19 was coming.

The real challenge is not foresight itself but how to turn foresight into action — specifically, into operational readiness supported by competent operators. The inability to contain the COVID-19 outbreak signals a failure to take seriously the outputs of our own foresight models by acting to create contingency arrangements, manage risks and secure back-up plans in advance, in a sustained manner and without a precise target date or endpoint. 

This failure has taken place in Italy, Iran, Spain, England, Sweden, the U.S. and elsewhere; authoritarian, conservative and social democratic governments alike have been overwhelmed. And because we live in a time of rapid and intensive global flows of people and products, multiple national failures compound inexorably into a global failure. In the words of President Eisenhower: “Plans are worthless, but planning is everything.”

A small number of countries, like Taiwan, have been able to manage the negative externalities better than others through a distinctive mix of governance attributes — at once vigorously participatory, highly trustworthy, competent and with careful plans. In 2004, the year after the SARS epidemic, which was widely seen to have been mishandled, the Taiwanese government established the National Health Command Center as “a disaster management center that focuses on large-outbreak response and acts as the operational command point for direct communications among central, regional and local authorities.” Five years later, Taiwanese health officials staged simulated drills as a capability exercise. Simulations revealed the tensions and miscommunications between different levels of government and agencies during a crisis, allowing officials to develop heuristics for overcoming such problems in advance.

Lessons from that process in turn helped to inform the planning that has gone into the current response: how quickly to react to an outbreak; the centralization of production, procurement and distribution of critical medical equipment; the conversion of hospitals from patient-centric to community-centric healthcare. While practice may not make perfect, it certainly beats not practicing.

But these attributes only pay off for pandemic risk if they can be “stretched” onto a long shadow of the future. Pandemics are an iconic example of risks with a particularly challenging temporal profile — an event that is logically possible and foreseeable, that has massive negative externalities but no definable time horizon of probabilities. It will happen at some point in time, but that time could be tomorrow, it could be in 10 years or it could be in 100 years, far beyond the lifespan of any decision-maker alive today.

Other risks like artificial generalized intelligence or rapid discontinuous climate change have a similar temporal profile. This kind of time horizon is particularly challenging because normally the cost-benefit models that guide most public policies don’t apply. We’d make very different investments if we knew that a pandemic was more than 50% likely in any given year than if we knew the probability was 1% annually for the next 50 years. But we actually don’t know which of those worlds we’re living in.

How do societies and governments extend the shadow of the future so that we will invest in the (sometimes spare) operational capacity that can make it possible to respond effectively to extraordinary crises? Even as the pressures of efficiency and cost-reduction argue for taking every last bit of excess capacity and redundancy out of the system, those investments must be kept in place over time, waiting for trigger signs that a problem is imminent. Because once the early warning indicators are blinking red — or even yellow — it will be too late to assemble the necessary capacity. In this sense, as Taiwan shows, achieving and maintaining operational competence, particularly in the face of problems of collective risk, is inseparable from the commitment to long-term planning.

Americans often decry the fact that the Chinese are playing a “long game” (in foreign policy, for example), but the U.S. has shown the ability to do that as well, most effectively in the immediate post-World War II period. That is what a long shadow of the future entails. It’s neither a democratic nor an authoritarian advantage. It’s not a small-state against large-state advantage. It’s not even necessarily an advantage of capitalism.

What will matter going forward, as ever, is the capacity of political leadership to frame a long-term narrative and stick to it over time. Institutions and incentives can be bent to that narrative. So, of course, can the decision-making psychology of citizens. Shifting how we think about social risk and about the importance of operational competence, and maintaining those new syntheses for a long time, should be the project of this generation.