Liberal fatalism, COVID 19 and the politics of impossibility

Abstract

How liberal governments manage knowledge, ignorance, prediction and uncertainty has attracted increased attention across the social sciences. In this paper, we analyse the strategy and rhetoric of the UK government during the COVID-19 pandemic, with particular attention to the first half of 2020. We see the initial UK policy response – as well as its later legitimation – as a form of ‘politics of impossibility’, effecting political change through claims of incapacity or impotence. We argue this approach departs from the uses of knowledge and ignorance in both classical liberalism and neoliberalism, and suggests the emergence of a new, hybrid form of governance which can be dubbed liberal fatalism. We discuss the relevance of this new form of governance for political futures of an increasingly volatile world.

Keywords:

• liberal fatalism
• COVID-19
• strategic ignorance
• behavioural science
• UK government
• pandemics

Introduction

There is nothing new in observing how those in positions of power use knowledge for strategic purposes. The problems of ‘unknowing’ and its political potency, however, have only more recently attracted the increased attention of social theorists and philosophers (e.g. McGoey, 2007; Bacevic, 2019; Schwitzgebel, 2012; Smithson, 2008; Sullivan & Tuana, 2007; Tapp, 2000).

As ecological and political crises proliferate, it makes sense to ask whether existing frameworks and concepts can adequately capture the relationship between knowing about and intervening in the world. The coronavirus pandemic offered a fresh lesson in the difficulty of avoiding the dual trap of ‘epochal theorizing’ versus ‘business-as-usual’. Some theorists were quick to label it an unprecedented ‘event’ (Žižek, 2020) or rupture offering the opportunity to rebuild societies along more equal, just and environmentally sustainable lines (Walby, 2021); others saw it as confirming existing theories, like Giorgio Agamben’s (2021) attempt to explain pandemic governance as the operation of sovereign power through the state of exception (see also Prozorov, 2021).

This paper aims to capture what the COVID-19 pandemic can teach us about the modes of governing knowledge and ignorance, while remaining attentive to the ways it both reproduces and departs from existing or preceding forms of political epistemology. Our main contribution is to identify a form of governance emerging from the coronavirus pandemic that we term ‘liberal fatalism’. Whereas classical liberalism involved a ‘taming of chance’ (Hacking, 1990) through ‘turning a qualitative world into information and rendering it amenable to control’ (Rose, 1999, p. 203), and neoliberalism uses the market to distribute the risk of epistemic monopolies (Amadae, 2015; Foucault, 2004), liberal fatalism both embraces and wilfully reproduces the idea of the unknowability and unpredictability of complex systems or events that provides justification for increased state control, but in ways that appear opposed to authoritarianism old and new.

Whereas this shift in governance can be seen across major areas of political governance today, from climate to domestic energy pricing management, to taxation policy, the UK government’s response to the COVID-19 pandemic provides a particularly illuminating case. In this way, the paper contributes to the scholarship on ignorance, knowledge, prediction and political futures, both adding to and departing from earlier work on techniques of governing the essentially uncertain nature of contemporary modernity (e.g. Browne, 2023; Bostrom & Ćirković, 2008; Centeno et al., 2015; Amoore, 2013; Aradau & van Munster, 2011; Zinn, 2008; Hacking, 1990).

Using a critical policy approach (e.g. Stone, 2020; Yanow, 2007), we examine the rise of liberal fatalism through the analysis of the UK government’s approach to managing COVID-19 in the first year of the pandemic, focusing on the period from March 2020 to December 2020, as well as later government investigations of the early response. We build on three corpuses of data: (1) Reports, data and advice presented by the government’s Scientific Advisory Group for Emergencies (SAGE), with particular attention to the timing of non-pharmaceutical interventions (NPIs) and other measures introduced by the UK government; (2) Inter- and post-pandemic government reports assessing the UK response, such as reports from the House of Commons and the House of Lords Joint Committee on the National Security Strategy; and (3) Reports from media and advocacy groups such as the Good Law Project and statements of facts from legal proceedings (e.g. Good Law Project Ltd & ors v Secretary of State, 2021).

We show how the lack of certainty in scientific advice was used to justify the absence of more coherent governmental intervention in the first wave of the pandemic, but it also provided retroactive justification for stricter measures in the second. In this way, the government was able to justify stronger intervention by the supposedly ‘unpredictable’ nature of the virus as well as ‘unknown’ effectiveness of behavioural interventions. Yet, as we demonstrate, both elements were ultimately knowable: the likelihood and nature of the contagion were presented to the government both through the 2017 Risk Register and through different modelling scenarios, and the behaviour of the population was not only predicted but, more importantly, shaped through the framing of ‘knowns’ and ‘unknowns’ in the pandemic.

The paper proceeds as follows. In the first part, drawing on reports and briefings, we analyse the UK government’s response to COVID-19 in the course of 2020. We argue that this period represented a series of ‘critical junctures’ where decisions that set the trajectory of Britain’s response to the pandemic were taken. What others have characterized as a series of ‘blunders’ or accidents can be explained by shifting the angle from questions of knowledge and/or ignorance about the nature of the virus to questions of political epistemology: that is, the kinds of political action enabled by this approach to knowns and unknowns.

In the second part, we analyse the UK government’s approach to knowns and unknowns in the period between March and December 2020, focusing on two aspects. The first is the relationship between scientific evidence and policy interventions. Drawing on critical discourse analysis of the reports published by SAGE, and guidance circulated by international organizations such as the World Health Organization (WHO), we show how the UK government used ‘the science’ to justify or oppose interventions that often had very little to do with scientific knowledge or evidence. Contrary to the approaches that focused on the role of SAGE and, in particular, epidemiological and mathematical modelling in shaping the government’s response, we focus on the government’s use of public opinion research as a way of assessing possible reactions of the public (Bacevic, 2021a, 2020a, 2020b, 2020c). This provided a sufficient ‘knowledge base’, but one that was primarily oriented towards managing the population, rather than the virus.

The other aspects we focus on are ‘failures’ or delays in the development of diagnostic capacity, including Test & Trace or PPE procurement. Drawing on the analysis of the policy process informed by public and media reports, we show how ‘ignorance’ enabled the government to make decisions about public procurement that benefitted the private sector. In the third section, drawing on discussions in political theory of the relationship between liberalism and meliorism (e.g. Shklar, 2020 [1969]; Guilhot, 2022), we describe how liberal fatalism builds on and departs from political epistemologies of, on the one hand, classical liberalism and, on the other, neoliberalism. What it shares with both classical liberalism and neoliberalism is a distaste for visible government intervention. Yet, while classical liberalism derives this distaste from a belief in universal rationality (Zagzebski, 2012) and neoliberalism from recognition of the problem of tacit, unarticulated knowledge (see Davies & McGoey, 2012), liberal fatalism uses ‘unknowns’ as a type of insurance against political liability. Ignorance becomes a post-hoc justification for the absence of intervention. In the concluding part, we discuss what this new phase of liberalism suggests about the changing relationship between knowledge, expertise and politics.

1. Pandemic uncertainty

The novel coronavirus (SARS-CoV-2) was first detected and isolated in December 2019, after people around the seafood market in the Chinese city of Wuhan became critically ill, some dying shortly after being admitted to the hospital. Early observations suggested the virus was highly contagious, spreading easily between humans, even without direct and prolonged exposure. The effects of the virus were equally different from its predecessors: initial studies suggested that the mortality of COVID-19, as the illness was dubbed, would be in the rate of 0.5–2 per cent but that it would be particularly lethal for over-60s, where it could reach 80 per cent. Combined with high transmission rate, it became obvious that this could lead to a serious health crisis on the global level. On 11 March 2020, the WHO declared a global pandemic, following weeks of earlier advice to nations to rapidly increase testing and contact tracing strategies.

Already in the first phase of the pandemic, the UK government’s approach diverged significantly from those of other governments, and, notably, from the approach recommended by the WHO. Then Prime Minister Boris Johnson’s first address to the nation included the infamous line ‘Many of us are going to lose their loved ones before their time’, suggesting that the government had accepted a high casualty rate, especially among the elderly and the already ill. It also included recognition that the pandemic would exceed the capacity of the UK’s National Health Service (NHS). Despite the fact that the Prime Minister’s own Conservative Party had been pushing for the privatization of the NHS for years, this seemed to imply there was no connection between the current government and past political actions that had created the conditions for the impending crisis.

Throughout February 2020, the government appeared relatively unconcerned. At the time when death rates in Italy were soaring, the official public health advice in the United Kingdom focused on the isolation of symptomatic cases (those who have developed fever, cough and difficulty breathing), but only if they had recently travelled from places identified with COVID-19 outbreaks. Boris Johnson first chaired a meeting of the Cabinet Office Briefing Room (COBRA) team in early March of the same year, having skipped five emergency COBRA meetings on the virus over January and February (Calvert et al., 2022).

Once the government had acknowledged the threat of the virus and the likely impact of the pandemic, official rhetoric switched into full ‘combat’ mode. Resources were directed into buttressing NHS’s critical care capacity (which the Prime Minister had a chance to peruse after ending up in an ICU having contracted COVID-19 in April 2020). A national lockdown was introduced, schools, universities and non-essential businesses ordered to close. As the number of cases began to level off in June, the government started slowly scaling down some of the measures, with the emphasis on reopening businesses in July and August. The ‘Eat out to help out’ scheme was specifically designed to incentivize people to eat in restaurants and pubs. Schools and universities were ordered to open in September and October, despite the fact that SAGE had advised the government against face-to-face teaching in universities. Hope, instead, was invested in the development of an efficient ‘track-and-trace’ system, as well as the development of the vaccine, with promising results of trials of the vaccine developed at the University of Oxford.

Yet, as cases started rising again in October and November, SAGE advised the government to introduce a second national lockdown, warning that the second wave could be potentially worse than the first. Despite the experience in springtime, however, the government yet again delayed the lockdown, until the UK’s Chief Scientific Officer, Chris Witty, advised that the effects of further delays were likely to prove disastrous. The second national lockdown was introduced in November 2020, shortly relaxing in December only to be reintroduced with the discovery of the new strain of the coronavirus, the B.1.1.1.7, reputed to be even more contagious. While vaccination programmes begun in January 2021, Britain remained in lockdown without a clear indication of when it would be over.

To date, the population-adjusted death rate from COVID-19 in the United Kingdom has been considerably higher than in nations with lower GDP per capita, including South Korea. While the full impact of the pandemic is still difficult to estimate, the United Kingdom seems to be among the countries that were hit hardest in this phase, second to only Peru and Spain: UK’s GDP per capita in the second quarter of 2020 was 21.7 per cent lower than in the same period in 2019 (Hasell, 2020). The same set of data suggests no ‘trade-off’ in terms of health versus the economy: countries most impacted by the virus simultaneously suffered the worst recession, which challenges the narrative of ‘saving the economy’ as justification for UK’s avoidance of lockdown. A 2021 report from the House of Commons Health and Social Care and Science and Technology Committees found that delays in introducing the first lockdown cost thousands of avoidable deaths, and labelled the early response period one of the UK’s worst ever public health failures in history (Sample & Walker, 2021).

What can explain the extent of the UK government’s (mis)management of COVID-19 in the first year of the pandemic? The report of the Joint Committee on the National Security Strategy attributed government failures to incompetence and short-sightedness (UK HoC & HoL, 2020). But, as sociology of ignorance has taught us, ‘short-sightedness’ can also be a useful political strategy. Our account shows how incompetence is produced through a series of policy decisions that simultaneously allow certain actions and make others not possible.

This, of course, does not mean that the UK government had access to information other governments did not, that it was manufacturing evidence, or deliberately hiding it from the general public, as some conspiracy theories would suggest. A firm, conclusive answer regarding government motivations is impossible: complete disclosure of the subjective states of different actors is not only unlikely to be shared with the public, reporters or social scientists, but also inaccessible to the actors themselves. But, pace Weber, it is also clear that even without access to semi-conscious or subconscious states, plausible narratives of motivations can and should be asserted in order to understand social action.

From this perspective, ignorance appears as not just ‘objective’ or inevitable, but also as communicable and useful (McGoey, 2007, 2012). In contexts of uncertainty, decision-making also involves choosing what kind of knowledge (or its absence) will be used to inform policymaking. In this sense, ‘uncertainty’ is not only a feature of reality (the ‘outside world’), but also a measure of the interaction between human intervention and reality (Hacking, 1990; Cartwright, 2012, 2011). This means that the use of scientific knowledge and evidence turns on political epistemology: not only what is, but what can – and cannot – be done about it.

To begin with, the pandemic was not an ‘unknowable’ or unlikely event. It was a white swan, rather than a black swan – something that was predicted in many public health circles to occur, rather than an unforeseen development. In 2016, the UK civil service ran an emergency preparedness exercise involving a global flu pandemic scenario, codenamed, of all possible things, ‘Operation Cygnus’. The results predicted quite accurately many of the events in 2020, including that the pandemic would exceed NHS capacity.¹ Public health professionals, similarly, have long argued that a pandemic was likely: coronaviruses have been known to ‘jump’ between species, and the highly globalized world of airline travel made it possible for one to spread quickly.

Secondly, the pandemic featured not one but two epistemic objects (Bacevic, 2019): the virus and the population. And while it could be argued that, at the very start of the pandemic, the ‘behaviour’ of the virus was unknown, the behaviour of the population was not. In this sense, understanding the UK government’s approach to the COVID-19 pandemic requires looking not only at how it approached the virus, but also how it approached the other ‘epistemic object’: their own constituents.

2. Decision-making and the productivity of ignorance

The official source of scientific advice for the UK government is SAGE.² SAGE coordinates scientific advice for the Cabinet Office Briefing Room (popularly referred to as COBRA) team meetings, where the government decides how to implement it into policy. During 2020, SAGE was chaired by the Government Chief Scientific Adviser, Sir Patrick Vallance, and co-chaired by Chris Whitty, UK’s Chief Medical Officer and simultaneously Chief Scientific Adviser for the Department of Health and Social Care.

Like many other expert advisory groups, SAGE does not conduct its own research; rather, its role is to provide an authoritative overview of existing knowledge executive bodies can draw on. While the wider membership of the group is not normally disclosed to the public, and minutes of conversations between SAGE and COBRA are confidential, in March 2020 – in response, at least in part, to criticism of its lack of transparency in the media – SAGE published a set of documents detailing scientific evidence for the response to COVID-19.³ These documents provide an insight not only into the knowledge available to the UK government when it came to the pandemic, but also, and more importantly, to the kind of questions they asked.

Government decisions concerning public measures to contain the virus were based on projections provided by SPI-M, SAGE’s subsection that focuses on mathematical modelling of the rate of spread of the virus (R), informed by epidemiological evidence. SPI-M also provided estimates for the outcomes of specific interventions: for instance, the projected drop in cases following bans for indoor gatherings. Yet, when it comes to predicting the effects on the population, the government also took advice from SAGE’s behavioural science subgroup – the Scientific Pandemic Influenza Group on Behaviours (SPI-B).

First convened as the Scientific Pandemic Influenza Group on Behaviours and Communications (SPI-B&C) during the H1N1 (‘swine flu’) outbreak in 2009/2010, SPI-B was reconvened in February 2020. This attracted some attention, in part because behavioural science was associated with the Behavioural Insights Team, the infamous ‘Nudge’ Unit. First convened by Blair, and later the Cameron administration, the ‘Nudge Unit’ was tasked with providing a response to what was seen as a growing public health crisis in the United Kingdom. The group drew on behavioural economics – popularized in Richard Thaler and Cass Sunstein’s book Nudge (2008) – to design public interventions that would ‘nudge’ people to make healthier choices when it came to, for example, food shopping or organ donation (see also Thaler & Sunstein, 2003).

The use of behavioural science in public interventions has been chiefly criticized on two grounds. One concerns the lack of transparency: people subjected to behavioural interventions are not supposed to know how they work, or the kind of response they are meant to induce. The other pertains to the justification for the use of this kind of intervention, which aims to decrease spending on public health and other services. The fact that behavioural interventions attempt to promote ‘good’ behaviour by affecting individual choices, rather than through public intervention – for instance, lowering taxes on fruit and vegetables, or funding the NHS – made behavioural science one of the key assets in the toolbox of neoliberal governance (e.g. Leggett, 2014; Gane, 2021).

At first, however, the UK government’s approach to managing the pandemic seemed to sharply diverge from neoliberal orthodoxy. Money was invested in the NHS’s critical care capacity, with ‘Nightingale’ hospitals developing overnight in London and Birmingham. Rishi Sunak, at the time the Chancellor of the Exchequer, introduced a package of measures to aid those worst hit by the pandemic. Leaving the ICU in April, the Prime Minister Boris Johnson stated, ‘There is such a thing as society’, inverting the famous dictum of one of his predecessors, Margaret Thatcher (Thatcher’s ‘There is no such thing as society … There are individual men and women, and there are families’, was often considered paradigmatic for neoliberal political ideology). While this may have suggested a new, explicitly interventionist and protectionist phase in politics, a closer analysis of the relationship between scientific advice and public policy at the time offers a more mixed view.

Initially, SPI-B was asked to provide advice in three domains: the risk of public disorder; the use of behavioural and social interventions; and how to give guidance to people who are asked to self-isolate (SPI-B-07, 4 March 2020). Secondly, the group was asked to comment on public attitudes and support and likely adherence to the interventions, as well as barriers, facilitators or communication issues. SPI-B considered a range of interventions, including stopping large events (‘mass gatherings’), school closures, isolation of people with symptoms, isolation of people with symptoms and also their households, general social distancing and lengthy social distancing for people in at-risk groups (SPI-M-O-06, 16 March 2020). While the group affirmed wider public support for stopping mass gatherings, it had a negative view of school closures and general social distancing – precisely the measures whose absence in the United Kingdom attracted wide-spread criticism:

The closure of schools, the loss of usual outlets for social interactions, and the absence of grandparents and entire families as a result of isolation might lead to unexpected displacement of activity. (…) Applying multiple policies concurrently will also increase the chances that there will be areas or groups who are visibly not complying, or not seeming to comply. It also increases the severity of the inequality of the measures. This will be in terms of financial and social impact but also of the perceived likelihood of contagion if some measures seem impossible to adhere to. (SPI-B-04, 4 March 2020)

Rather than focusing on the effects of different kind of measures on the transmission of the virus, the government, at this stage, focused on the effects of different kinds of measures on adherence to and support for government interventions. This nuance is easy to miss, as there is an obvious link between adherence to measures and their effectiveness. For instance, one of the explanations for not applying a stricter lockdown in the first stage of the pandemic was that people in liberal democracies, such as the United Kingdom, would not tolerate the level of restrictions people in authoritarian regimes, such as China, were supposedly accustomed to (SPI-B-04, 4 March 2020). Yet, this blanket cultural explanation not only obscures important socio-economic and demographic differences within individual countries, but also – conveniently – skirts over the fact that many equally liberal democracies adopted early on packages of measures (such as border closures or mandatory and enforced 14-day quarantine for new arrivals) that the United Kingdom adopted late or never.

The relevance of public knowledge (or ignorance) about the range of interventions applied in countries other than the United Kingdom was highlighted early on by SPI-B:

Expectations of how the Government will react will be set by media reports of public health strategies in other countries. This increases the risk of public concern if interventions that are perceived to be effective are not applied. A clear explanation as to why expected interventions are not being implemented may be necessary (…). One view is that explaining that members of the community are building some immunity will make this acceptable. Another view is that recommending isolation to only one section of society risks causing discontent. (SPI-B-04, 4 March 2020)

This can perhaps explain the brief appearance of ‘herd immunity’ as justification for the absence of stricter lockdown measures in official press briefings.⁴ Unsurprisingly, ‘herd immunity’ did not prove a particularly popular explanation. It prompted accusations of ‘eugenics’ and social engineering, but also public criticism from the medical community who not only pointed out it diverged from WHO guidelines, but also argued that ‘herd immunity’ had no scientific legitimacy or moral defensibility (Horton, 2020, p. 935). The government subsequently denied it had been part of the official strategy.

Throughout this period, the UK government was following and commissioning public opinion research into public awareness, risk perception and approval for different kinds of interventions. SPI-B evidence base lists 16 polls, conducted between February and March 2020, including surveys commissioned by the Cabinet Office from YouGov, as well as one commissioned by the Department of Health and Social Care from BMG Research (SPI-B-09). While not all of these surveys are publicly available, the timing of specific measures suggests they followed public approval, rather than new epidemiological evidence.

For instance, the introduction of the first national lockdown in April 2020 was justified by citing ‘new scientific evidence’ in the study produced by Neil Ferguson and colleagues at Imperial College in late March of the same year. However, Ferguson and his team had presented this model to a COBRA meeting already in late January.⁵ Similarly, studies suggesting asymptomatic transmission appeared in February. In this sense, the ‘evidence’ – to the degree to which any knowledge about an emerging disease can be considered reliable – was already there: it took a strategic change of course for it to be publicly announced as the reason for the introduction of specific measures. Similarly, when the government decided to lift the lockdown in June 2020, Ferguson – who opposed the lifting – had his reputation tarnished after the media ‘revealed’ he had broken lockdown to see his (married) lover. This made his opinion seem less valid, despite the absence of a logical link between the credibility of models and the moral ‘scorecard’ of the modeller (Bacevic, 2021a). This would suggest that, rather than being ‘guided by the science’, the UK government was actively involved in shaping public perceptions of ‘the science’.

Of course, shaping public perceptions is not the unique prerogative of the UK government. Political actors and political parties regularly canvas public opinion and probe the public’s support for different kinds of interventions. While the UK’s New Labour was one of the parties to pioneer ‘governing by messaging’ – that is, the use of public information, including in the media, to shape public behaviour (e.g. Finlayson, 2003; Crawshaw, 2013; Haydock, 2014) – strategic framing (or ‘spinning’) of information is hardly a novel tool of governance (e.g. Dunlop, 2016; McCombs et al., 2014; Benford & Snow, 2000). What is specific about the UK approach to the COVID-19 pandemic is the degree to which the government chose to capitalize on the absence of certain knowledge about specific issues in the public, in order to justify not acting (Bacevic, 2021c).

In the case of the COVID-19 pandemic, many of the factors – including the rate at which the virus mutates, main transmission pathways and likely consequences for people with specific conditions – were unknown at the beginning of the pandemic. Yet, while some governments chose to treat ‘unknowns’ as a reason for precaution – for instance, mandating the use of masks, banning indoor gatherings and so on – the UK government used them in order to justify not taking many of these measures. Had the UK government been simply reluctant to intervene, this, in and of itself, could be attributed to the fear of adverse public reactions – for instance, riots or refusal to comply, which was the first question the COBRA team posed to SPI-B. However, this choice not to know enabled framing later interventions as inevitable, or driven by the changing nature of the virus, rather than as in part, at least, created through previous government (in)action. In the next section, therefore, we turn to ignorance as justification (McGoey, 2012; Will, 2019): what this approach to ‘unknowns’ enabled the government to do.

3. From ignorance to incompetence

A notable element of the UK government’s pandemic response in 2020 was the failure to build capacity that could have enabled the three-pronged ‘test, trace and isolate’ approach, adopted by mid-January in nations such as South Korea and Germany. By April, it was clear that earlier delays had left the United Kingdom unprepared to roll out testing on a mass scale because of a shortage of tests and lab facilities to process results (Mueller, 2020; McKee, 2020).

In an interview to the BBC in mid-April 2020, Health Minister at the time, Matt Hancock, insisted that the main impediment to mass testing was the problem of scale: ‘We have the best scientific labs in the world, but we did not have the scale. My German counterpart for instance could call upon 100 testing labs ready and waiting when the crisis struck’.⁶ However, German scientists developed COVID-19 test kits based on earlier coronaviruses and reported the sequence to the WHO, who published it in January; the United Kingdom, however, chose to pass on using this testing sequence (Beaumont, 2020). Passing on the WHO protocol allowed new developers to emerge, by early March, some of the versions of this test were circulating for hundreds of pounds (Neate, 2020).

Comparison between the UK and German diagnostic preparedness was also at the centre of the UK’s public inquiry launched in June 2023. Public hearings provide a useful empirical resource for analysing rationales for past decisions. In June 2023, the former UK chief scientific advisor Patrick Vallance pointed to the lack of manufacturing capacity in comparison to Germany as a reason for inability to mass produce diagnostic tests as quickly as needed: ‘By 2020 UK vaccine manufacturing had almost gone … while we didn’t have a diagnostics industry on any scale, which made it very hard to scale up testing’ (quoted in Neville & Cookson, 2023; see also Kirchhelle, 2022, for a history of German-UK laboratory capacity).

While differences in manufacturing capacity were certainly a factor, what this account omits is the role of strategic decisions that compounded this delay. In the critical first months of 2020, Public Health England was relying on only its own eight labs to process COVID-19 tests. The government finally directed 40 other NHS labs to process tests: a total of 48 labs by mid-April – still well below the level of Germany. The government also missed at least three chances to make bulk purchases of protective equipment (PPE) through the EU scheme (Boffey & Booth, 2020). This contributed to the (widely reported) shortage of PPE, including for frontline health workers, at the start of the pandemic. Media investigations later revealed that companies subsequently awarded public contracts for the production of PPE as well as ‘test and trace’ had little to no prior experience in similar tasks, but many had figures in the government and/or the Conservative Party among their management or shareholders (Geoghan, 2020). The decision to establish a VIP ‘fast lane’ for preferred suppliers was later declared unlawful (Woodcock 2022).

Why did the United Kingdom delay improving diagnostic capacity? One possible explanation concerns the previous pandemic, the H1N1 virus or ‘swine flu’. WHO’s early declaration of a pandemic in 2009/2010 received criticism from the international health community, not least because countries rushed to purchase medical supplies that would later turn out unnecessary (Lakoff, 2015). While the independent inquiry found that the WHO has been justified in raising the threat level on H1N1, acting on the principle of caution rather than certainty (Kelly et al., 2020), individual countries were still unhappy about spending on a pandemic ‘that never came’. Thus, one of the reasons why the United Kingdom chose early on not to scale up its testing and diagnostic capacity, extend its PPE stock or boost the production of ventilators, could have been the reluctance to ‘overspend’. Yet, while it can offer partial explanation for initial delays, this narrative alone is hardly sufficient to account for the decisions that followed.

Another explanation involves the exit from the European Union (‘Brexit’). Completing the legal elements of this process was the personal commitment of Boris Johnson and the platform on which the Conservative Party won the 2019 election. From this perspective, the refusal to join other EU countries’ orders for PPE equipment and ventilators could be interpreted as a lack of desire to cooperate with EU institutions or abide by its procurement procedures, in order to be seen as successfully ‘delivering’ Brexit (see also Fitzgerald, 2023). Yet the justification for this similarly revolved around post-hoc ignorance. The government simply did not ‘know’/receive the information about the EU procurement scheme (Boffey & Booth, 2020), just like it did not ‘know’ numbers of infected people due to the shortage of testing and processing equipment.

Political actors can choose to play up or downplay ignorance in order to direct attention to specific elements of the problem. Sometimes, this is aided by the structure and timing of the problem itself: at the very start of the pandemic, epidemiological evidence about the COVID-19 virus was only beginning to emerge; in some cases, it was inconclusive. While the Joint Biosecurity Committee report recognized that ‘the novel features of Covid would have caused difficulties for any government’, it also expressed doubt that ‘the nature of the disease fully explain[ed] the difficulties the Government faced’ (UK HoC & HoL, 2020, p. 3). The report notes that the ‘Government appears to have doubted that a novel disease could circulate so widely’. However, the UK’s 2017 Risk Register deemed it likely that an emerging infectious disease would affect the country in the next five years. This led the Joint Committee to conclude that ‘despite the 2018 Biological Security Strategy’s emphasis on “Detection”, the government failed seriously to consider how it might scale up testing, isolation and contact-tracing capabilities during a serious disease outbreak’ (UK HoC & HoL, 2020, p. 3).

On the other hand, knowledge about public reactions was accessible and relatively reliable. As the analysis of polls included in SPI-B data shows, the questions the COBRA team asked had to do with public perceptions concerning approval for certain kinds of measures. In this sense, the government prioritized surveying public reactions to and knowledge about the virus, retroactively adjusting policy interventions to suit public approval. This is not to suggest, of course, that the UK government had a clear plan, or that it was deliberately pursuing the strategy of sacrificing its own population. Rather, emphasizing ignorance or uncertainty about elements of the response – the effectiveness of mask-wearing, the role of ventilation – made later decisions, such as the rapid awarding of contracts to private providers with no or little prior experience or the late introduction of travel restrictions, appear necessary or inevitable. This provided retroactive justification for UK government’s actions, while, at the same time, avoiding responsibility for inaction on other fronts.

This temporal ‘pincer movement’ is a key political feature of liberal fatalism. Ignorance is used to delay decisions or intervention, omitting to acknowledge that this delay itself narrows down the range of possibilities open to political actors. The UK government’s choice to focus on unknowns in order to justify not acting allowed it to construct the impression that policy interventions were driven by ‘external’ necessity, such as the growing rate of infections, rather than by the government’s own policies – from incentivizing eating out to amplifying ambiguity about transmission routes. In this, the UK government pursued an epistemological strategy to ensure continued political legitimacy and maintain the networks of economic and political patronage in the context of a public health and economic crisis.

In the next section, we turn to the political epistemology underpinning this approach, and how it differs from the epistemologies of both classical liberalism and neoliberalism.

4. Global catastrophes and the rise of liberal fatalism

Global catastrophic events such as pandemics or climate change pose new challenges to how political actors engage with questions of knowledge/ignorance, un/certainty and, importantly, their distribution. Systematic production of knowledge about their own (and, often, other) populations has been a defining element in the toolboxes of both classical and neoliberal governance (Foucault, 2004; Rose, 1999; Amadae, 2015). However, the approach that we have identified in the UK government’s handling of the coronavirus pandemic departs from both of these modes.

Early liberals saw ignorance as an ‘open’ epistemic problem, one that different liberal ideals and norms, including public education, freedom of speech and transparent quantification of risks, could help ‘tame’ (Hacking, 1990). Classical liberalism, in this sense, sought to reduce ignorance by providing members of a society with access to knowledge as a route to rational decisions. Later neoliberals also saw human ignorance as an intrinsic problem for decision-making, and they too stressed the meliorative ability to overcome inevitable human ignorance, but through a different conduit, namely through the market. Friedrich Hayek, famously, championed the epistemological benefits of a decentralized market system in meeting human needs more efficiently than any central government planner (Davies & McGoey, 2012; Foucault, 2004).

Hayek’s recognition of the limits of human knowledge was not a new insight; he was indebted to classical political economists such as Adam Smith. In The wealth of nations, Smith argued that people’s socio-economic status inevitably affects their ability to reason impartially or objectively – and thus rationally. He suggested that people who owned land and lived off rents tended to be made mentally lazy by the wealth. In his words, they were ‘not only ignorant, but incapable of that application of mind which is necessary in order to foresee and understand the consequences of any publick regulation’ (Smith, 1997 [1776], p. 155; see also McGoey, 2019). Smith also wrote extensively about the merchant class. He insisted that merchants tended to know a great deal about their own business, but less about matters of public welfare outside their remit. This led, he argued, for them to press legislators to implement pro-merchant policies that harmed the public good: ‘The interests of the dealers, however, in any particular branch of trade and manufactures, is always in some respects different from, and even opposite to, that of the publick’ (1997[1776], p. 156). In light of this threat to the public, Smith called for state intervention to curb the rent-seeking of the merchant class (McGoey, 2019). What really distinguishes both classical liberalism and neoliberalism from what we are calling liberal fatalism, thus, is not the degree of state intervention (state support for industry was consistent over the eighteenth century onwards (see Stahl, 2019)), nor the recognition of the inevitability of human ‘ignorance’. Rather, it is a paradigmatic shift in perceptions of which institutions and people in society are best placed to moderate knowledge and ignorance.

Classical liberals were firm believers in checks and balances on all forms of absolute privilege, including the privileges of commercial merchants and other market actors. Later liberals shifted away from this emphasis. Neoliberalism afforded excessive epistemic privilege to the market. Rather than an ‘open-choice’ framework that seeks to enlarge the power and knowledge of different actors, as in the case of classical liberalism, or to enlarge the price-establishing capacity of market actors, in the case of neoliberalism, liberal fatalism emphasizes epistemological choicelessness: people respond most effectively to incentives the less they consciously know about the rationale for them. What is side-lined, both rhetorically and practically, is the meliorist emphasis within earlier liberal paradigms, replaced by a new harnessing of performative powerlessness.

Within political theory, there has been some attention to gradual loss of meliorism as a political and policy goal, notably in the work of Judith Shklar (1969 [2002]), who explored how the deployment of scientific reason for mass destruction in World War II helped to shake early Enlightenment faith in science as an inevitable good. As Nicolas Guilhot (2022) puts it, building on Skhlar, ‘liberalism had not only forsaken its earlier claims to progress, but now looked with diffidence, if not hostility, to any perfectionist strivings’ settling instead on ‘damage control’ in lieu of grand schemes for societal betterment (see also Ashenden & Hess, 2016, Bacevic, 2021a, McGoey, 2019).

The UK government’s COVID response illustrates and deepens the implications of this ebbing of liberal faith in meliorist progress. Unlike authoritarian regimes, where state control is emphasized as a corrective to the problems of inevitable unknowability of the future (Herzog & Geroulanos, 2021), the UK government’s pandemic response coupled the state’s lack of capacity to manage, predict and intervene with an insistence on individual responsibility when it came to socializing, mask-wearing and other interactions. In authoritarian regimes, the state’s capacity to protect is expanded while at the same time the capacity for individual decision-making is depreciated, thus legitimating an erosion of individual rights in practice: there is explicit emphasis on ‘individual rights as secondary to the goals of the nation’ (Rydgren, 2007, p. 242; see also Arendt, 2009). In lieu of the depreciation of individual reason, liberal fatalism retains an emphasis on the unpredictability of the future while rooting ultimate responsibility for poor decisions with the individual – a strategy that can be attractive to a wide range of constituents across the political spectrum (e.g. low-income, minority voters who have legitimate reasons to be deeply suspicious of state power and overreach in times of medical crisis, such as the Tuskegee experiments (Jones, 1992)). Liberal fatalism can thus appear as a welcome retracting of state overreach, even if it paradoxically leaves some vulnerable groups more exposed to corporate and state harm.

Rather than designing institutions to correct for differences in knowledge between groups of actors (as in the liberal commitment to universal education) or allowing the ‘invisible hand of the market’ to adjust it (as in the neoliberal belief in marketized education), liberal fatalism allows political actors to use gaps, uncertainties and inconsistencies in knowledge to justify particular kinds of political (in)action. Unlike authoritarian regimes, this does not mean they necessarily restrict public access to knowledge or to information. They can tolerate and perhaps even actively foster different ‘alternative’ and even explicitly denialist epistemologies, from ‘Covid-truthers’ to ‘climate skeptics’, as long as these do not interfere in the capacity of political elites to retain sufficient control over, for example, public procurement schemes (Fonseca et al., 2021; McGoey, 2022; Ortega & Orsini, 2020).

Liberal fatalism thus supersedes the supposed dichotomy between trust in science, on the one hand, and ‘crisis of expertise’ or ‘post-truth’ on the other (Bacevic, 2021a, 2021b). What the epistemological strategy obscures is precisely the role of political elites in shaping ‘knowns’ and ‘unknowns’. This type of performative fatalism is liberal, in that it ‘asks’ for consent from civil society rather than compelling it. It appears to avoid, as far as possible, constraining choice from the top down. People must be free to choose, but their range of options is limited. Instead of a politics of possibility (Amoore, 2013), liberal fatalism thus engenders a politics of impossibility: it effectively closes the scope of action available to most members of the public, while simultaneously furnishing an ‘ignorance alibi’ (McGoey, 2019) for political elites.

Conclusions

In this paper, we have argued that a key element of the UK government’s response to COVID-19 was the managing of different ‘knowns’ and ‘unknowns’, especially at the start of the pandemic. We show how the timing of measures aimed at the virus, while ostensibly directed by ‘the science’, was in fact developed in response to two overarching goals: maintaining political legitimacy and enabling the sustained flow of capital into specific sectors (such as private firms tasked with the procurement of PPE or COVID-19 testing). In this uncertain time, lack of (certain) knowledge about specific features of the virus of effectiveness of particular measures was used as a justification for not acting, until it appeared that certain decisions became inevitable. The combination of ignorance and incompetence, thus, provided an ‘ignorance alibi’ to ensure continued (even if challenged) political legitimacy.

This temporal pincer movement is likely to become increasingly prominent as the world’s governments face challenges to the political order generated by global events such as pandemics or climate change. This approach to managing ‘unknowns’ has particular appeal for liberal-democratic governments with relatively advanced knowledge production systems and a relatively high capacity to intervene. In the context of high predictive capacity, the problem of foresight is at the same time a challenge to political legitimacy: if you could see ‘it’ coming, why did you not do something about it?

In contradistinction to early liberal regimes that tried to govern through reducing uncertainty, as well as neoliberal regimes that aim to exploit uncertainty for both economic and political gain, liberal fatalism constructs uncertainty as inevitable – ‘many of us are going to lose our loved ones before their time’ – while ensuring political actors will not be held accountable for the decisions that aggravated it. This embrace of epistemological fatalism, in turn, foments insurance against liability by insisting on the impossibility of acting differently. When everyone’s shared ignorance is equally to blame, no-one is to blame.

Acknowledgements

Thank you to Su-ming Khoo who first suggested the formulation ‘liberal fatalism’ (we had earlier decided on ‘fatalistic liberalism’). We are grateful to the anonymous reviewers of Economy and Society for constructive feedback on this paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Jana Bacevic

Jana Bacevic is an Assistant Professor at Durham University, Department of Sociology. Her work is in social theory, politics of knowledge, philosophy of science and the political economy of knowledge production. She has published extensively on the uses of scientific knowledge and evidence, the construction of epistemic authority and the intersection between moral, political and epistemological elements in knowledge production.

Linsey McGoey

Linsey McGoey is a Professor of Sociology at the University of Essex, with expertise in social and political theory, and the epistemology of ignorance. She is the author of No such thing as a free gift: The Gates Foundation and the price of philanthropy (Verso) and The unknowers: How strategic ignorance rules the world (Bloomsbury).

Notes

1 https://www.thetimes.co.uk/article/nhs-fails-to-cope-with-bodies-in-flu-pandemic-test-8pnmdpdfx

2 https://www.gov.uk/government/groups/scientific-advisory-group-for-emergencies-sage

3 https://www.gov.uk/government/news/coronavirus-covid-19-scientific-evidence-supporting-the-uk-government-response

4 https://www.theguardian.com/world/2020/mar/13/coronavirus-science-chief-defends-uk-measures-criticism-herd-immunity

5 https://www.thetimes.co.uk/edition/news/coronavirus-38-days-when-britain-sleepwalked-into-disaster-hq3b9tlgh

6 https://www.bbc.co.uk/news/health-52234061