Never have we seen as many white gowns as in the past year: epidemiologists, virologists, infectiologists, doctors and clinicians of all specializations, from resuscitation to pneumonology, springing like mushrooms out of every news broadcast. Thanks to Covid, it seems that scientists have broken into society at large. But is this invasion a transitory phenomenon, or is it destined to become a permanent occupation? Perhaps the time has come to ask ourselves how science has fared in this recent period, and how the relationship between science and society has altered – an ambiguous relationship at best, demonstrated by the resistance which vaccination efforts have met thus far, even among some healthcare professionals.
As the philosopher of science Isabelle Stengers noted in a recent interview, this relationship has lately become suffused with panic. It’s an uncomfortable word to use, for most are reluctant to admit they’re gripped by this feeling. Yet the term is appropriate: ‘confinement should be understood from the standpoint of a panicked reaction. And when we panic we forget many things. We react under the pressure of an emergency, which prevents us from thinking. We have been guided by panic, and it has accentuated all social inequalities and relations of power… Deep down, I think what we saw was indifference towards anything that fell outside the preservation of public order’.
Stengers also observes that, in these conditions, science must be discussed in the plural rather than the singular:
Regarding the sciences, what really hurt me was hearing talk – from doctors, in particular – of ‘science’, and seeing politicians parroting the term (‘we listen to the science’) out of convenience. All of a sudden, in another panicked impulse, they forgot about politics, making way for a ‘science’ which began guiding us. Now, it is always a terrible idea to ask ‘science’ what to do, because that’s not its job. Its role is to try to ask pertinent questions. As soon as we say ‘science’ we forget the pertinence of its questions. It’s as if there were a universal scientific method, capable of responding to everything objectively. It’s also a way of silencing people, as it’s well-known that ordinary people are unable to understand ‘science’. It’s striking to me that the pluralisation of the sciences proceeded through this unifying, singular denomination of ‘science’. This plurality depends precisely on the different objects of each of the sciences, and on the questions they raise, faced with which each science will respond as it sees fit.
When politicians claim they listen to the science, in reality they resort to experts. And there’s nothing further from a scientist than an expert. As a group of researchers wrote for Scienza in rete,
the scientist selects the object of and questions for an investigation; the expert – who enjoys a certain experience of recognised value – is called on to apply knowledge and judgement to a query posed by others. This raises a series of problems: 1) It’s often not possible to trace the answer to a problem back to a single field. The Covid-19 pandemic posed problems at once virological, epidemiological, economic, social: problems of healthcare, relating to public order, and so on; 2) It is necessary for the expert to respond to the issue at hand in a restricted amount of time – or in any case by a certain precise deadline – scarcely compatible with the time needed for research, which, moreover, often ends up raising more questions, calling for a further round of studies; 3) the multidimensionality of problems requires the expert to give an answer that transcends the limits of what they possess any authority to say (given their disciplinary field), setting off political conflicts and controversies which bear only a distant relation to more focused scientific debates.
The advice of scientists (or ‘researchers’, as they are often called) and experts tends to diverge depending on several factors. Among them: the economic, social and political stakes of ‘expert opinion’; the uncertainty of the information on which they base their advice; and the urgency of the political decisions that flow from their intervention. When the stakes are high, facts uncertain, values in dispute and decisions urgent, then we enter into the realm of ‘post-normal science’ (as defined in a seminal article by Silvio Funtowicz and Jerome Ravetz from 1993).
The uncertainty surrounding the basic facts of the pandemic was evident in this list, drawn up by epidemiologists on 25 March 2020, of information that was then unknown to us:
Known unknowns include the real prevalence of the virus in the population; the role of asymptomatic cases in the rapid spread of the virus; the degree to which humans develop immunity; the dominant exposure pathways; the disease’s seasonal behaviour; the time to deliver global availability of an effective vaccine or cure; and the nonlinear response of individuals and collectives to the social distancing interventions in the complex system of communities interconnected across multiple scales, with many tipping points, and hysteresis loops (implying that society may not be able to rebound to the state it was in before the coronavirus interventions took place).
Apart from the vaccine, these ‘unknowns’ remain more or less obscure despite thousands of scientific studies. The result is a profound uncertainty which renders any epidemiological forecast hypothetical and unreliable. Yet to make policy decisions, governments now use mathematical models which produce crisp numbers via a drastic simplification of such ambiguities. (This tension between scientific uncertainty and political decision-making sometimes breaks out into the open: Dr Anthony Fauci, grilled by a Republican Congressman on exactly how many coronavirus deaths could be expected back in March 2020, responded, ‘There is no number-answer to your question!’)
All the ‘unknowns’ cited above depend on data-collection processes which often prove fallible. After a year of Covid, even the simplest figures still elude us, and it’s probable we’ll never pin them down. This is in part due to the inveterate habit of governments to lie to themselves; the more autocratic they are, the more they can cherry-pick the most convenient facts. Studies using various indicators of despotism show a strong inverse correlation between authoritarianism in a given country and its tally of Covid victims. The firmer the regime, the fewer deaths it declares. Last November, the prominent Italian physicist Giorgio Parisi wrote that even in a relatively transparent country like Italy the official rate of transmission (Rt) is untrustworthy. Imagine, then, how trustworthy the political decisions based on it have been.
Do you remember when, in 1986, Chernobyl’s radioactive cloud ground to a halt at the Rhine and dared not cross the Franco-German border (at least according to French health statistics at the time)? As the rest of Europe monitored the levels of radioactivity in their food, the French joyfully consumed vegetables which the douanes had cleansed of any radiation by pure administrative fiat. Well, a similar phenomenon occurred with Covid-19 at the frontiers that separate Europe and Asia. It’s mysterious how advanced healthcare systems could record such high mortality rates: hundreds of times higher than in states with fewer resources. While social (and state) control in China and other Asian countries has played a part, it’s difficult to imagine that deep in rural Laos restrictions can be so thorough as to prevent contagion completely. In other cases – in Russia, for instance – the numbers are totally fictitious; they have displayed an unnatural regularity, day after day, for almost a year now. Elsewhere, in the Amazon rainforest or the High Nile, the task of collecting data would require superhuman abilities.
Thus, in recent times, numbers have come to serve a purely rhetorical function, appearing to confer certainty on the uncertain. The claim that ‘thousands of people have died’ leaves some room for debate, whereas the statement ‘there have been 12,327 victims’ sounds indisputable. The ‘number-answer’ is vital to establish trust – justified or not – in the opinion of the expert. But the means by which we arrive at these numbers are not always interrogated.
Here, Stengers’s distinction between singular and plural ‘science’ becomes decisive. On the one hand, there are sciences that rely entirely on data collected by central governments and public health agencies. Epidemiologists are at the mercy of statistics. To give just one example: after a year of Covid, we still don’t know the proper measurement of social distancing. A metre, one and a half, two, three? It varies, according to ‘expert opinion’. On the other hand the hard sciences, based on laboratory experiments, are often shielded from the game of experts. In the lab, the expert and the scientist are allies, for the demands of the outside world accord with the aims of the latter: discovering how to produce the vaccine, for instance. It’s not a coincidence that the most successful sciences are those which generate the most profit: in them, the tension between exogenous pressures and endogenous logic is less pronounced.
Yet when we enter into the ‘post-normal’ domain, the sciences lend themselves more readily to manipulation. Researchers that produce vaccines respond to socially pertinent questions, but those tasked with establishing the safety of the vaccine become ‘experts’, and are drawn into the realm of conflicting interests, as we saw with the flurry of judgements surrounding the AstraZeneca jab. Put bluntly, in post-normal conditions (Chernobyl, Covid-19, global warming), the sciences begin to practice politics.
In one of the best articles written on the subject, ‘New Pathogen, Old Politics’, Alex De Waal recounts the history of the cholera outbreak in Hamburg in 1892; an instructive episode, for viruses and their transmission rates may differ, but they always seem to trigger similar social responses. Today, we’ve forgotten that the first immunity passports were established by Italian cities in the Late Middle Ages to facilitate the free circulation of diplomats and merchants. We also forget that local elites, wherever they might be, have always opposed quarantines and confinement measures imposed by central authorities, fearful of potential damage to their economic interests. As De Waal reminds us, it was in the 19th century, with the advent of colonialism, that the allusion to warfare became widespread, with the development of an ‘anti-infection arsenal in the service of expanding the writ of the colonial state’. In France,
the government portrayed the disease as an ‘invasion’ from the Levant and India, which justified martial medical measures and the establishment of the outer ramparts of Europe’s sanitary frontier in the Middle East. The metaphor of ‘fighting’ a disease, apt for the body’s immune response to a pathogen, is incongruous for the social response to an epidemic. Nonetheless, the language of warfare has become so familiar today that it is adopted unreflectingly – a mark of true hegemony. The traffic in metaphors runs both ways. When mobilizing for war or authoritarian measures, political leaders inveigh against ‘infestation’ by invaders or infiltrators that are akin to pathogens. In times of health crisis, they like to ‘declare war’ on a microbial ‘invisible enemy’.
The metaphor of war recalls the ‘state of exception’ – a return to the ‘state of siege’ of past epochs – which this year’s curfews evoke only vaguely, contrary to what The Economist has called the ‘coronopticon’, evoking Bentham’s infamous gaol.
Gauging the relationship between science and society in light of Covid-19 is therefore a complex matter. Health policies are hurling us into a new political order, a new configuration of power, yet we remain largely unable to see the direction in which we are headed. Of course, the parade of new variants gives us a terrifying glimpse of confinement without end, for as soon as society is relaxed and ready to stretch its legs, the shadow of an invincible mutation (Brazilian, British) rears its head. One can only hope that we emerge from both the state of panic identified by Stengers and the constant fear of new viruses, aped by governments to infantilize and surveil their citizens.
Best to conclude with De Waal’s wise words:
The motives for – and consequences of – public health measures have always gone far beyond controlling disease. Political interest trumps science – or, to be more precise, political interest legitimizes some scientific readings and not others. Pandemics are the occasion for political contests, and history suggests that facts and logic are tools for combat, not arbiters of the outcome. While public health officials urge the public to suspend normal activities to flatten the curve of viral transmission, political leaders also urge us to suspend our critique so that they can be one step ahead of the outcry when it comes. Rarely in recent history has the bureaucratic, obedience-inducing mode of governance of the ‘deep state’ become so widely esteemed across the political spectrum. It is precisely at such a moment, when scientific rationality is honored, that we need to be most astutely aware of the political uses to which such expertise is put.
Translated by Francesco Anselmetti.
Read on: Susan Watkins, ‘Politics and Pandemics’, NLR 125.