The climate crisis resembles a huge planetary lockdown, trapping humanity within an ever-deteriorating environment
‘The shallow layer of earth in which we live … has been transformed into a habitable milieu by the aeons-long labour of evolution.’ Photograph: Jon Helgason/Alamy
Fri 24 Dec 2021 14.00 GMT
There is a moment when a never-ending crisis turns into a way of life. This seems to be the case with the pandemic. If so, it’s wise to explore the permanent condition in which it has left us. One obvious lesson is that societies have to learn once again to live with pathogens, just as they learned to when microbes were first made visible by the discoveries of Louis Pasteur and Robert Koch.
These discoveries were concerned with only one aspect of microbial life. When you also consider the various sciences of the earth system, another aspect of viruses and bacteria comes to the fore. During the long geochemical history of the earth, microbes, together with fungi and plants, have been essential, and are still essential, to the very composition of the environment in which we humans live. The pandemic has shown us that we will never escape the invasive presence of these living beings, entangled as we are with them. They react to our actions; if they mutate, we have to mutate as well.
This is why the many national lockdowns, imposed on citizens to help them survive the virus, are a powerful analogy for the situation in which humanity finds itself detained for good. Lockdown was painful enough, and yet many ways have been found, thanks in part to vaccination, to allow people to resume a semblance of normal life. But there is no possibility of such a resumption if you consider that all living forms are locked down for good inside the limits of the earth. And by “earth” I don’t mean the planet as it can be seen from space, but its very superficial pellicle, the shallow layer of earth in which we live, and which has been transformed into a habitable milieu by the aeons-long labour of evolution.
This thin matrix is what geochemists call the “critical zone”, the only layer of earth where terrestrial life can flourish. It’s in this finite space where everything we care for and everything we have ever encountered exists.There is no way of escaping our earth-bound existence; as young climate activists shout: “There is no planet B.” Here is the connection between the Covid lockdowns we have experienced in the past two years, and the much larger but definitive state of lockdown that we find ourselves in: we are trapped in an environment that we have already altered irreversibly.
If we have been made aware of the agency of viruses in shaping our social relations, we must now reckon with the fact that they will also be moulded for ever by the climate crisis and the quick reactions of ecosystems to our actions. The feeling that we live in a new space appears again at the local as well as the global level. Why would all nations convene in Glasgow to keep global temperature rises below some agreed upon limit, if they did not have the sensation that a huge lid had been put over their territory? When you look up at the blue sky, are you not aware that you are now under some sort of dome inside which you are locked?
Gone is the infinite space; now you are responsible for the safety of this overbearing dome as much as you are for your own health and wealth. It weighs on you, body and soul. To survive under these new conditions we have to undergo a sort of metamorphosis.
This is where politics enters. It is very difficult for most people used to the industrialised way of life, with its dream of infinite space and its insistence on emancipation and relentless growth and development, to suddenly sense that it is instead enveloped, confined, tucked inside a closed space where their concerns have to be shared with new entities: other people of course, but also viruses, soils, coal, oil, water, and, worst of all, this damned, constantly shifting climate.
This disorienting shift is unprecedented, even cosmological, and it is already a source of deep political divisions. Although the sentence “you and I don’t live on the same planet” used to be a joking expression of dissent, it has become true of our present reality. We do live on different planets, with rich people employing private fire fighters and scouting for climate bunkers, while their poorer counterparts are forced to migrate, suffer and die amid the worst consequences of the crisis.
This is why it is important not to misconstrue the political conundrum of our present age. It is of the same magnitude as when, from the 17th century onward, westerners had to shift from the closed cosmos of the past to the infinite space of the modern period. As the cosmos seemed to open, political institutions had to be invented to work through the new and utopian possibilities offered by the Enlightenment. Now, in reverse, the same task falls to present generations: what new political institutions could they invent to cope with people so divided that they belong to different planets?
It would be a mistake to believe that the pandemic is a crisis that will end, instead of the perfect warning for what is coming, what I call the new climatic regime. It appears that all the resources of science, humanities and the arts will have to be mobilised once again to shift attention to our shared terrestrial condition.
Bruno Latour is a philosopher and anthropologist, the author of After Lockdown: A Metamorphosis and the winner of the 2013 Holberg prize
Cold era, lasting from early 15th to mid-19th centuries, triggered by unusually warm conditions
Date: December 15, 2021
Source: University of Massachusetts Amherst
Summary: New research provides a novel answer to one of the persistent questions in historical climatology, environmental history and the earth sciences: what caused the Little Ice Age? The answer, we now know, is a paradox: warming.
New research from the University of Massachusetts Amherst provides a novel answer to one of the persistent questions in historical climatology, environmental history and the earth sciences: what caused the Little Ice Age? The answer, we now know, is a paradox: warming.
The Little Ice Age was one of the coldest periods of the past 10,000 years, a period of cooling that was particularly pronounced in the North Atlantic region. This cold spell, whose precise timeline scholars debate, but which seems to have set in around 600 years ago, was responsible for crop failures, famines and pandemics throughout Europe, resulting in misery and death for millions. To date, the mechanisms that led to this harsh climate state have remained inconclusive. However, a new paper published recently in Science Advances gives an up-to-date picture of the events that brought about the Little Ice Age. Surprisingly, the cooling appears to have been triggered by an unusually warm episode.
When lead author Francois Lapointe, postdoctoral researcher and lecturer in geosciences at UMass Amherst and Raymond Bradley, distinguished professor in geosciences at UMass Amherst began carefully examining their 3,000-year reconstruction of North Atlantic sea surface temperatures, results of which were published in the Proceedings of the National Academy of Sciences in 2020, they noticed something surprising: a sudden change from very warm conditions in the late 1300s to unprecedented cold conditions in the early 1400s, only 20 years later.
Using many detailed marine records, Lapointe and Bradley discovered that there was an abnormally strong northward transfer of warm water in the late 1300s which peaked around 1380. As a result, the waters south of Greenland and the Nordic Seas became much warmer than usual. “No one has recognized this before,” notes Lapointe.
Normally, there is always a transfer of warm water from the tropics to the Arctic. It’s a well-known process called the Atlantic Meridional Overturning Circulation (AMOC), which is like a planetary conveyor belt. Typically, warm water from the tropics flows north along the coast of Northern Europe, and when it reaches higher latitudes and meets colder Arctic waters, it loses heat and becomes denser, causing the water to sink at the bottom of the ocean. This deep-water formation then flows south along the coast of North America and continues on to circulate around the world.
But in the late 1300s, AMOC strengthened significantly, which meant that far more warm water than usual was moving north, which in turn cause rapid Arctic ice loss. Over the course of a few decades in the late 1300s and 1400s, vast amounts of ice were flushed out into the North Atlantic, which not only cooled the North Atlantic waters, but also diluted their saltiness, ultimately causing AMOC to collapse. It is this collapse that then triggered a substantial cooling.
Fast-forward to our own time: between the 1960s and 1980s, we have also seen a rapid strengthening of AMOC, which has been linked with persistently high pressure in the atmosphere over Greenland. Lapointe and Bradley think the same atmospheric situation occurred just prior to the Little Ice Age — but what could have set off that persistent high-pressure event in the 1380s?
The answer, Lapointe discovered, is to be found in trees. Once the researchers compared their findings to a new record of solar activity revealed by radiocarbon isotopes preserved in tree rings, they discovered that unusually high solar activity was recorded in the late 1300s. Such solar activity tends to lead to high atmospheric pressure over Greenland.
At the same time, fewer volcanic eruptions were happening on earth, which means that there was less ash in the air. A “cleaner” atmosphere meant that the planet was more responsive to changes in solar output. “Hence the effect of high solar activity on the atmospheric circulation in the North-Atlantic was particularly strong,” said Lapointe.
Lapointe and Bradley have been wondering whether such an abrupt cooling event could happen again in our age of global climate change. They note that there is now much less Arctic sea ice due to global warming, so an event like that in the early 1400s, involving sea ice transport, is unlikely. “However, we do have to keep an eye on the build-up of freshwater in the Beaufort Sea (north of Alaska) which has increased by 40% in the past two decades. Its export to the subpolar North Atlantic could have a strong impact on oceanic circulation,” said Lapointe. “Also, persistent periods of high pressure over Greenland in summer have been much more frequent over the past decade and are linked with record-breaking ice melt. Climate models do not capture these events reliably and so we may be underestimating future ice loss from the ice sheet, with more freshwater entering the North Atlantic, potentially leading to a weakening or collapse of the AMOC.” The authors conclude that there is an urgent need to address these uncertainties.
This research was supported by funding from the National Science Foundation.
Francois Lapointe, Raymond S. Bradley. Little Ice Age abruptly triggered by intrusion of Atlantic waters into the Nordic Seas. Science Advances, 2021; 7 (51) DOI: 10.1126/sciadv.abi8230
IS IT NEARLY over? In 2021 people have been yearning for something like stability. Even those who accepted that they would never get their old lives back hoped for a new normal. Yet as 2022 draws near, it is time to face the world’s predictable unpredictability. The pattern for the rest of the 2020s is not the familiar routine of the pre-covid years, but the turmoil and bewilderment of the pandemic era. The new normal is already here.
Remember how the terrorist attacks of September 11th 2001 began to transform air travel in waves. In the years that followed each fresh plot exposed an unforeseen weakness that required a new rule. First came locked cockpit doors, more armed air marshals and bans on sharp objects. Later, suspicion fell on bottles of liquid, shoes and laptops. Flying did not return to normal, nor did it establish a new routine. Instead, everything was permanently up for revision.
The world is similarly unpredictable today and the pandemic is part of the reason. For almost two years people have lived with shifting regimes of mask-wearing, tests, lockdowns, travel bans, vaccination certificates and other paperwork. As outbreaks of new cases and variants ebb and flow, so these regimes can also be expected to come and go. That is the price of living with a disease that has not yet settled into its endemic state.
And covid-19 may not be the only such infection. Although a century elapsed between the ravages of Spanish flu and the coronavirus, the next planet-conquering pathogen could strike much sooner. Germs thrive in an age of global travel and crowded cities. The proximity of people and animals will lead to the incubation of new human diseases. Such zoonoses, which tend to emerge every few years, used to be a minority interest. For the next decade, at least, you can expect each new outbreak to trigger paroxysms of precaution.
Covid has also helped bring about today’s unpredictable world indirectly, by accelerating change that was incipient. The pandemic has shown how industries can be suddenly upended by technological shifts. Remote shopping, working from home and the Zoom boom were once the future. In the time of covid they rapidly became as much of a chore as picking up the groceries or the daily commute.
Big technological shifts are nothing new. But instead of taking centuries or decades to spread around the world, as did the printing press and telegraph, new technologies become routine in a matter of years. Just 15 years ago, modern smartphones did not exist. Today more than half of the people on the planet carry one. Any boss who thinks their industry is immune to such wild dynamism is unlikely to last long.
The pandemic may also have ended the era of low global inflation that began in the 1990s and was ingrained by economic weakness after the financial crisis of 2007-09. Having failed to achieve a quick recovery then, governments spent nearly $11trn trying to ensure that the harm caused by the virus was transient.
They broadly succeeded, but fiscal stimulus and bunged-up supply chains have raised global inflation above 5%. The apparent potency of deficit spending will change how recessions are fought. As they raise interest rates to deal with inflation, central banks may find themselves in conflict with indebted governments. Amid a burst of innovation around cryptocoins, central-bank digital currencies and fintech, many outcomes are possible. A return to the comfortable macroeconomic orthodoxies of the 1990s is one of the least likely.
The pandemic has also soured relations between the world’s two great powers. America blames China’s secretive Communist Party for failing to contain the virus that emerged from Wuhan at the end of 2019. Some claim that it came from a Chinese laboratory there—an idea China has allowed to fester through its self-defeating resistance to open investigations. For its part, China, which has recorded fewer than 6,000 deaths, no longer bothers to hide its disdain for America, with its huge death toll. In mid-December this officially passed 800,000 (The Economist estimates the full total to be almost 1m). The contempt China and America feel for each other will heighten tensions over Taiwan, the South China Sea, human rights in Xinjiang and the control of strategic technologies.
In the case of climate change, the pandemic has served as an emblem of interdependence. Despite the best efforts to contain them, virus particles cross frontiers almost as easily as molecules of methane and carbon dioxide. Scientists from around the world showed how vaccines and medicines can save hundreds of millions of lives. However, hesitancy and the failure to share doses frustrated their plans. Likewise, in a world that is grappling with global warming, countries that have everything to gain from working together continually fall short. Even under the most optimistic scenarios, the accumulation of long-lasting greenhouse gases in the atmosphere means that extreme and unprecedented weather of the kind seen during 2021 is here to stay.
The desire to return to a more stable, predictable world may help explain a 1990s revival. You can understand the appeal of going back to a decade in which superpower competition had abruptly ended, liberal democracy was triumphant, suits were oversized, work ended when people left the office, and the internet was not yet disrupting cosy, established industries or stoking the outrage machine that has supplanted public discourse.
Events, dear boy, events
That desire is too nostalgic. It is worth notching up some of the benefits that come with today’s predictable unpredictability. Many people like to work from home. Remote services can be cheaper and more accessible. The rapid dissemination of technology could bring unimagined advances in medicine and the mitigation of global warming.
Even so, beneath it lies the unsettling idea that once a system has crossed some threshold, every nudge tends to shift it further from the old equilibrium. Many of the institutions and attitudes that brought stability in the old world look ill-suited to the new. The pandemic is like a doorway. Once you pass through, there is no going back. ■
This article appeared in the Leaders section of the print edition under the headline “The new normal”
As alarm about climate change and calls for action intensify, solar geoengineering (SG) is seeing increased attention and controversy. Views on whether it should or will ever be used diverge, but the evidentiary basis for these views is thin. On such a high-stakes, knowledge-limited issue, one might expect strong support for research, but even research has met opposition. Opponents’ objections are grounded in valid concerns but impossible to fully address, as they are framed in ways that make rejecting research an axiom, not a conclusion based on evidence.
Supporters of SG research argue that it can inform future decisions and prepare for likely future calls for deployment. A US National Academies of Sciences, Engineering, and Medicine (NASEM) report earlier this year lent thoughtful support to this view. Opponents raise well-known concerns about SG such as its imperfect climate correction, its time-scale mismatch with greenhouse gases (GHGs), and the potential to over-rely on it or use it recklessly or unjustly. They oppose research based on the same concerns, arguing that usage can never be acceptable so research is superfluous; or that sociopolitical lock-in will drive research toward deployment even if unwarranted. Both support and opposition are often implicit, embedded in debates over additional governance of SG research beyond peer review, program management, and regulatory compliance.
At present, potential SG methods and claimed benefits and harms are hypothetical, not demonstrated. The strongest objections to research invoke potential consequences that are indirect, mediated by imprudent or unjust policy decisions. Because the paths from research to these bad outcomes involve political behavior, claims that these “could” happen cannot be fully refuted. Understanding and limiting these risks require the same research and governance-building activities that opponents reject as causing the risks.
To reject an activity based on harms that might follow is to apply extreme precaution. This can be warranted when there is risk of serious, unmitigable harm and the alternative is known to be acceptable. That is not the case here. Rejecting SG research means taking the alternative trajectory of uncertain but potentially severe climate impacts, reduced by whatever emissions cuts, GHG removals, and adaptation are achieved. But these other responses needed to meet prudent climate targets carry their own risks: of falling short and suffering more severe climate change, and of collateral environmental and socioeconomic harms from deployment at the required transformative, even revolutionary, scale.
Suppressing research on SG might reduce risks from its future use, but this is not assured: Rather than preventing use in some future crisis, blocking research might make such use less informed, cruder, and more dangerous. Even if these risks are reduced, this would shift increased risks onto climate change and crash pursuit of other responses. Total climate-related risk may well increase—and be more unjustly distributed, because the largest benefits of SG appear likely to flow to the most vulnerable people and communities.
Yet the concerns that motivate opposition to research are compelling. SG use would be an unprecedented step, affecting climate response, international governance, sustainability, and global justice. Major concerns—about reckless or rivalrous use, or over-reliance weakening emissions cuts—are essential to address, even if they cannot be avoided with certainty. A few directions show promise for doing so. Research should be in public programs, in jurisdictions with cultures of public benefit and research accountability. The NASEM call for a US federal program is sound. Other national programs should be established. Research governance should be somewhat stronger than for less controversial research, including scale limits on field experiments and periodic program reassessments. Exploration of governance needs for larger-scale interventions should begin well before these are considered. Research and governance should seek broad international cooperation—promptly, but not as a precondition to national programs. Broad citizen consultations are needed on overall climate response and the role of SG. These should link to national research and governance programs but not have veto power over specific activities.
Precaution is appropriate, even necessary. But precaution cannot selectively target risks from one climate response while ignoring its linkages to other responses and risks. Suppressing SG research is likely to make the harms and injustices that opponents fear more likely, not less.
In Discriminating Data: Correlation, Neighborhoods, and the New Politics of Recognition, Wendy Hui Kyong Chun explores how technological developments around data are amplifying and automating discrimination and prejudice. Through conceptual innovation and historical details, this book offers engaging and revealing insights into how data exacerbates discrimination in powerful ways, writes David Beer.
Discriminating Data: Correlation, Neighborhoods, and the New Politics of Recognition. Wendy Hui Kyong Chun (mathematical illustrations by Alex Barnett). MIT Press. 2021.
Going back a couple of decades, there was a fair amount of discussion of ‘the digital divide’. Uneven access to networked computers meant that a line was drawn between those who were able to switch-on and those who were not. At the time there was a pressing concern about the disadvantages of a lack of access. With the massive escalation of connectivity since, the notion of a digital divide still has some relevance, but it has become a fairly blunt tool for understanding today’s extensively mediated social constellations. The divides now are not so much a product of access; they are instead a consequence of what happens to the data produced through that access.
With the escalation of data and the establishment of all sorts of analytic and algorithmic processes, the problem of uneven, unjust and harmful treatment is now the focal point for an animated and urgent debate. Wendy Hui Kyong Chun’s vibrant new book Discriminating Data: Correlation, Neighborhoods, and the New Politics of Recognitionmakes a telling intervention. At its centre is the idea that these technological developments around data ‘are amplifying and automating – rather than acknowledging and repairing – the mistakes of a discriminatory past’ (2). Essentially this is the codification and automation of prejudice. Any ideas about the liberating aspects of technology are deflated. Rooted in a longer history of statistics and biometrics, existing ruptures are being torn open by the differential targeting that big data brings.
This is not just about bits of data. Chun suggests that ‘we need […] to understand how machine learning and other algorithms have been embedded with human prejudice and discrimination, not simply at the level of data, but also at the levels of procedure, prediction, and logic’ (16). It is not, then, just about prejudice being in the data itself; it is also how segregation and discrimination are embedded in the way this data is used. Given the scale of these issues, Chun narrows things down further by focusing on four ‘foundational concepts’, with correlation, homophily, authenticity and recognition providing the focal points for interrogating the discriminations of data.
It is the concept of correlation that does much of the gluing work within the study. The centrality of correlation is a subtext in Chun’s own overview of the book, which suggests that ‘Discriminating Data reveals how correlation and eugenic understandings of nature seek to close off the future by operationalizing probabilities; how homophily naturalizes segregation; and how authenticity and recognition foster deviation in order to create agitated clusters of comforting rage’ (27). As well as developing these lines of argument, the use of the concept of correlation also allows Chun to think in deeply historical terms about the trajectory and politics of association and patterning.
For Chun the role of correlation is both complex and performative. It is argued, for instance, that correlations ‘do not simply predict certain actions; they also form them’. This is an established position in the field of critical data studies, with data prescribing and producing the outcomes they are used to anticipate. However, Chun manages to reanimate this position through an exploration of how correlation fits into a wider set of discriminatory data practices. The other performative issue here is the way that people are made-up and grouped through the use of data. Correlations, Chun writes, ‘that lump people into categories based on their being “like” one another amplify the effects of historical inequalities’ (58). Inequalities are reinforced as categories become more obdurate, with data lending them a sense of apparent stability and a veneer of objectivity. Hence the pointed claim that ‘correlation contains within it the seeds of manipulation, segregation and misrepresentation’ (59).
Given this use of data to categorise, it is easy to see why Discriminating Data makes a conceptual link between correlation and homophily – with homophily, as Chun puts it, being the ‘principle that similarity breeds connection’ and can therefore lead to swarming and clustering. The acts of grouping within these data structures mean, for Chun, that ‘homophily not only eases conflict; it also naturalizes discrimination’ (103). Using data correlations to group informs a type of homophily that not only misrepresents and segregates; it also makes these divides seem natural and therefore fixed.
Chun anticipates that there may be some remaining remnants of faith in the seeming democratic properties of these platforms, arguing that ‘homophily reveals and creates boundaries within theoretically flat and diffuse social networks; it distinguishes and discriminates between supposedly equal nodes; it is a tool for discovering bias and inequality and for perpetuating them in the name of “comfort,” predictability, and common sense’ (85). As individuals are moved into categories or groups assumed to be like them, based upon the correlations within their data, so discrimination can readily occur. One of the key observations made by Chun is that data homophily can feel comfortable, especially when encased in predictions, yet this can distract from the actual damages of the underpinning discriminations they contain. Instead, these data ‘proxies can serve to buttress – and justify – discrimination’ (121). For Chun there is a ‘proxy politics’ unfolding in which data not only exacerbates but can also be used to lend legitimacy to discriminatory acts.
As with correlation and homophily, Chun, in a particularly novel twist, also explores how authenticity is itself becoming automated within these data structures. In stark terms, it is argued that ‘authenticity has become so central to our times because it has become algorithmic’ (144). Chun is able to show how a wider cultural push towards notions of the authentic, embodied in things like reality TV, becomes a part of data systems. A broader cultural trend is translated into something renderable in data. Chun explains that the ‘term “algorithmic authenticity” reveals the ways in which users are validated and authenticated by network algorithms’ (144). A system of validation occurs in these spaces, where actions and practices are algorithmically judged and authenticated. Algorithmic authenticity ‘trains them to be transparent’ (241). It pushes a form of openness upon us in which an ‘operationalized authenticity’ develops, especially within social media.
This emphasis upon the authentic draws people into certain types of interaction with these systems. It shows, Chun compellingly puts it, ‘how users have become characters in a drama called “big data”’ (145). The notion of a drama is, of course, not to diminish what is happening but to try to get at its vibrant and role-based nature. It also adds a strong sense of how performance plays out in relation to the broader ideas of data judgment that the book is exploring.
These roles are not something that Chun wants us to accept, arguing instead that ‘if we think through our roles as performers and characters in the drama called “big data,” we do not have to accept the current terms of our deployment’ (170). Examining the artifice of the drama is a means of transformation and challenge. Exposing the drama is to expose the roles and scripts that are in place, enabling them to be questioned and possibly undone. This is not fatalistic or absent of agency; rather, Chun’s point is that ‘we are characters, rather than marionettes’ (248).
There are some powerful cross-currents working through the discussions of the book’s four foundational concepts. The suggestion that big data brings a reversal of hegemony is a particularly telling argument. Chun explains that: ‘Power can now operate through reverse hegemony: if hegemony once meant the creation of a majority by various minorities accepting a dominant worldview […], now hegemonic majorities can emerge when angry minorities, clustered around a shared stigma, are strung together through their mutual opposition to so-called mainstream culture’ (34). This line of argument is echoed in similar terms in the book’s conclusion, clarifying further that ‘this is hegemony in reverse: if hegemony once entailed creating a majority by various minorities accepting – and identifying with – a dominant worldview, majorities now emerge by consolidating angry minorities – each attached to a particular stigma – through their opposition to “mainstream” culture’ (243). In this formulation it would seem that big data may not only be disciplinary but may also somehow gain power by upending any semblance of a dominant ideology. Data doesn’t lead to shared ideas but to the splitting of the sharing of ideas into group-based networks. It does seem plausible that the practices of targeting and patterning through data are unlikely to facilitate hegemony. Yet, it is not just that data affords power beyond hegemony but that it actually seeks to reverse it.
The reader may be caught slightly off-guard by this position. Chun generally seems to picture power as emerging and solidifying through a genealogy of the technologies that have formed into contemporary data infrastructures. In this account power seems to be associated with established structures and operates through correlations, calls for authenticity and the means of recognition. These positions on power – with infrastructures on one side and reverse hegemony on the other – are not necessarily incompatible, yet the discussion of reverse hegemony perhaps stands a little outside of that other vision of power. I was left wondering if this reverse hegemony is a consequence of these more processional operations of power or, maybe, it is a kind of facilitator of them.
Chun’s book looks to bring out the deep divisions that data-informed discrimination has already created and will continue to create. The conceptual innovation and the historical details, particularly on statistics and eugenics, lend the book a deep sense of context that feeds into a range of genuinely engaging and revealing insights and ideas. Through its careful examination of the way that data exacerbates discrimination in very powerful ways, this is perhaps the most telling book yet on the topic. The digital divide may no longer be a particularly useful term but, as Chun’s book makes clear, the role data performs in animating discrimination means that the technological facilitation of divisions has never been more pertinent.
Para as instituições científicas, essas práticas e movimentos enquadram-se na categoria das “pseudociências”. Ou seja, doutrinas baseadas em fundamentos que seus adeptos consideram científicas e, a partir daí, criam uma corrente que se afasta do que é normalmente aceito pelo mundo acadêmico.
Mas como distinguir o que é ciência daquilo que se faz passar por ciência?
Essa tarefa é muito mais complicada do que parece, segundo Michael Gordin, professor da Universidade Princeton, nos Estados Unidos, e especialista em história da ciência. Gordin é autor do livro On the Fringe: Where Science Meets Pseudoscience (“Na Fronteira: Onde a Ciência Encontra a Pseudociência”, em tradução livre).
Seu livro detalha como operam as pseudociências e como, do seu ponto de vista, são uma consequência inevitável do progresso científico.
Em entrevista à BBC News Mundo (o serviço em espanhol da BBC), Gordin detalha a complexa relação entre o que se considera ciência verdadeira e o que ele chama de doutrinas marginais.
BBC News Mundo – O senhor afirma que não existe uma linha definida separando a ciência da pseudociência, mas a ciência tem um método claro e comprovável. Esta não seria uma diferença clara com relação à pseudociência?
Michael Gordin – Acredita-se normalmente que a ciência tem um único método, mas isso não é verdade. A ciência tem muitos métodos. Os geólogos fazem seu trabalho de forma muito diferente dos físicos teóricos, e os biólogos moleculares, dos neurocientistas. Alguns cientistas trabalham no campo, observando o que acontece. Outros trabalham em laboratório, sob condições controladas. Outros fazem simulações. Ou seja, a ciência tem muitos métodos, que são heterogêneos. A ciência é dinâmica, e esse dinamismo dificulta a definição dessa linha. Podemos tomar um exemplo concreto e dizer que se trata de ciência ou de pseudociência. É fácil com um exemplo concreto.
O problema é que essa linha não é consistente e, quando você observa uma maior quantidade de casos, haverá coisas que antes eram consideradas ciência e agora são consideradas pseudociências, como a astrologia. Existem temas como a deriva dos continentes, que inicialmente era considerada uma teoria marginal e agora é uma teoria básica da geofísica.
Quase tudo o que hoje se considera pseudociência já foi ciência no passado, que foi refutada com o passar do tempo e os que continuam a apoiá-la são considerados lunáticos ou charlatães. Ou seja, a definição do que é ciência ou pseudociência é dinâmica ao longo do tempo. Esta é uma das razões da dificuldade desse julgamento.
BBC News Mundo – Mas existem coisas que não se alteram ao longo do tempo. Por exemplo, 2+2 sempre foi igual a 4. Isso quer dizer que a ciência trabalha com base em princípios que não permitem interpretações…
Gordin – Bem, isso não é necessariamente certo. Dois óvnis mais dois óvnis são quatro óvnis.
É interessante que você tenha escolhido a matemática que, de fato, não é uma ciência empírica, pois ela não se refere ao mundo exterior. É uma série de regras que usamos para determinar certas coisas.
Uma das razões pelas quais é muito complicado fazer a distinção é o fato de que as doutrinas marginais observam o que é considerado ciência estabelecida e adaptam a elas seus argumentos e suas técnicas.
Um exemplo é o “criacionismo científico”, que defende que o mundo foi criado em sete dias, 6.000 anos atrás. Existem publicações de criacionismo científico que incluem gráficos matemáticos sobre as razões de decomposição de vários isótopos, para tentar comprovar que a Terra tem apenas 6.000 anos.
Seria genial afirmar que usar a matemática e apresentar gráficos é ciência, mas a realidade é que quase todas as doutrinas marginais usam a matemática de alguma forma.
Os cientistas discordam sobre o tipo de matemática utilizada, mas existem, por exemplo, pessoas que defendem que a matemática avançada utilizada na teoria das cordas já não é científica, porque perdeu a verificação empírica. Trata-se de matemática de alto nível, feita por doutores das melhores universidades, mas existe um debate interno na ciência, entre os físicos, que discutem se ela deve ou não ser considerada ciência.
Não estou dizendo que todos devem ser criacionistas, mas, quando a mecânica quântica foi proposta pela primeira vez, algumas pessoas diziam: “isso parece muito estranho”, “ela não se atém às medições da forma em que acreditamos que funcionem” ou “isso realmente é ciência?”
BBC News Mundo – Então o sr. afirma que as pseudociências ou doutrinas marginais têm algum valor?
Gordin – A questão é que muitas coisas que consideramos inovadoras provêm dos limites do conhecimento ortodoxo.
O que quero dizer são basicamente três pontos: primeiro, que não existe uma linha divisória clara; segundo, que compreender o que fica de cada lado da linha exige a compreensão do contexto; e, terceiro, que o processo normal da ciência produz doutrinas marginais.
Não podemos descartar essas doutrinas, pois elas são inevitáveis. Elas são um produto derivado da forma como as ciências funcionam.
BBC News Mundo – Isso significa que deveríamos ser mais tolerantes com as pseudociências?
Gordin – Os cientistas, como qualquer outra pessoa, têm tempo e energia limitados e não podem pesquisar tudo.
Por isso, qualquer tempo que for dedicado a refutar ou negar a legitimidade de uma doutrina marginal é tempo que deixa de ser usado para fazer ciência — e talvez nem surta resultados.
As pessoas vêm refutando o criacionismo científico há décadas. Elas trataram de desmascarar a telepatia por ainda mais tempo e ela segue rondando à nossa volta. Existem diversos tipos de ideias marginais. Algumas são muito politizadas e chegam a ser nocivas para a saúde pública ou o meio ambiente. É a estas, a meu ver, que precisamos dedicar atenção e recursos para sua eliminação ou pelo menos explicar por que elas estão erradas.
Mas não acho que outras ideias, como acreditar em óvnis, sejam especificamente perigosas. Acredito que nem mesmo o criacionismo seja tão perigoso como ser antivacinas, ou acreditar que as mudanças climáticas são uma farsa.
Devemos observar as pseudociências como algo inevitável e abordá-las de forma pragmática. Temos uma quantidade de recursos limitada e precisamos escolher quais doutrinas podem causar danos e como enfrentá-las.
Devemos simplesmente tratar de reduzir os danos que elas podem causar? Esse é o caso da vacinação obrigatória, cujo objetivo é evitar os danos, mas sem necessariamente convencer os opositores que eles estão equivocados. Devemos persuadi-los de que estão equivocados? Isso precisa ser examinado caso a caso.
BBC News Mundo – Como então devemos lidar com as pseudociências?
Gordin – Uma possibilidade é reconhecer que são pessoas interessadas na ciência.
Um terraplanista, por exemplo, é uma pessoa interessada na configuração da Terra. Significa que é alguém que teve interesse em pesquisar a natureza e, por alguma razão, seguiu a direção incorreta.
Pode-se então perguntar por que isso aconteceu. Pode-se abordar a pessoa, dizendo: “se você não acredita nesta evidência, em qual tipo de evidência você acreditaria?” ou “mostre-me suas evidências e vamos conversar”.
É algo que poderíamos fazer, mas vale a pena fazê-lo? É uma doutrina que não considero perigosa. Seria um problema se todos os governos do mundo pensassem que a Terra é plana, mas não vejo esse risco.
A versão contemporânea do terraplanismo surgiu há cerca de 15 anos. Acredito que os acadêmicos ainda não compreendem muito bem como aconteceu, nem por que aconteceu tão rápido.
Outra coisa que podemos fazer é não necessariamente persuadi-los de que estão equivocados, porque talvez eles não aceitem, mas tentar entender como esse movimento surgiu e se expandiu. Isso pode nos orientar sobre como enfrentar ameaças mais sérias.
BBC News Mundo – Ameaças mais sérias como os antivacinas…
Gordin – As vacinas foram inventadas no século 18, sempre houve pessoas que se opusessem a elas, em parte porque todas as vacinas apresentam risco, embora seja muito baixo.
Ao longo do tempo, a forma como se lidou com a questão foi a instituição de um sistema de seguro que basicamente diz o seguinte: você precisa receber a vacina, mas se você receber e tiver maus resultados, nós compensaremos você por esses danos.
Tenho certeza de que isso ocorrerá com a vacina contra a covid, mas ainda não conhecemos todo o espectro, nem a seriedade dos danos que ela poderá causar. Mas os danos e a probabilidade de sua ocorrência parecem ser muito baixos.
Com relação aos antivacinas que acreditam, por exemplo, que a vacina contra a covid contém um chip, a única ação que pode ser tomada para o bem da saúde pública é torná-la obrigatória. Foi dessa forma que se conseguiu erradicar a pólio na maior parte do mundo, mesmo com a existência dos opositores à vacina.
BBC News Mundo – Mas torná-la obrigatória pode fazer com que alguém diga que a ciência está sendo usada com propósitos políticos ou ideológicos…
Gordin – Tenho certeza de que, se o Estado impuser uma vacina obrigatória, alguém dirá isso. Mas não se trata de ideologia. O Estado já obriga tantas coisas e já existem vacinas que são obrigatórias.
E o Estado faz todo tipo de afirmações científicas. Não é permitido o ensino do criacionismo nas escolas, por exemplo, nem a pesquisa de clonagem de seres humanos. Ou seja, o Estado já interveio muitas vezes em disputas científicas e procura fazer isso segundo o consenso científico.
BBC News Mundo – As pessoas que adotam as pseudociências o fazem com base no ceticismo, que é exatamente um dos valores fundamentais da ciência. É um paradoxo, não?
Gordin – Este é um dos motivos por que acredito que não haja uma linha divisória clara entre a ciência e a pseudociência. O ceticismo é uma ferramenta que todos nós utilizamos. A questão é sobre qual tipo de assuntos você é cético e o que pode convencê-lo de um fato específico.
No século 19, havia um grande debate se os átomos realmente existiam ou não. Hoje, praticamente nenhum cientista duvida da sua existência. É assim que a ciência funciona. O foco do ceticismo se move de um lado para outro com o passar do tempo. Quando esse ceticismo se dirige a assuntos que já foram aceitos, às vezes ocorrem problemas, mas há ocasiões em que isso é necessário.
A essência da teoria da relatividade de Einstein é que o éter — a substância através da qual as ondas de luz supostamente viajavam — não existe. Para isso, Einstein concentrou seu ceticismo em um postulado fundamental, mas o fez dizendo que poderiam ser preservados muitos outros conhecimentos que já eram considerados estabelecidos.
Portanto, o ceticismo deve ter um propósito. Se você for cético pelo simples fato de sê-lo, este é um processo que não produz avanços.
BBC News Mundo – É possível que, no futuro, o que hoje consideramos ciência seja descartado como pseudociência?
Gordin – No futuro, haverá muitas doutrinas que serão consideradas pseudociências, simplesmente porque existem muitas coisas que ainda não entendemos.
Existem muitas coisas que não entendemos sobre o cérebro ou o meio ambiente. No futuro, as pessoas olharão para muitas teorias e dirão que estão erradas.
Não é suficiente que uma teoria seja incorreta para que seja considerada pseudociência. É necessário que existam pessoas que acreditem que ela é correta, mesmo que o consenso afirme que se trata de um equívoco e que as instituições científicas considerem que, por alguma razão, ela é perigosa.
The decision to appoint a board of advisors is welcome — and urgent, given the twin challenges of COVID and climate change.
EDITORIAL – 08 December 2021
Scientists helped to create the United Nations system. Today, people look to UN agencies — such as the UN Environment Programme or the World Health Organization — for reliable data and evidence on, say, climate change or the pandemic. And yet, shockingly, the UN leader’s office has not had a department for science advice for most of its 76-year history. That is about to change.
UN secretary-general António Guterres is planning to appoint a board of scientific advisers, reporting to his office. The decision was announced in September in Our Common Agenda (see go.nature.com/3y1g3hp), which lays out the organization’s vision for the next 25 years, but few other details have been released.
Representatives of the scientific community are excited about the potential for science to have a position at the centre of the UN, but are rightly anxious for rapid action, given the twin challenges of COVID-19 and climate change, which should be urgent priorities for the board. The International Science Council (ISC), the Paris-based non-governmental body representing many of the world’s scientists, recommended such a board in its own report on science and the intergovernmental system, published last week (see go.nature.com/3rjdjos). Council president Peter Gluckman, former chief science adviser to New Zealand’s prime minister, has written to Guterres to say the ISC is ready to help.
But it’s been more than two months since the announcement, and the UN has not yet revealed the names of the board members. Nature spoke to a number of serving and former UN science advisers who said they know little about the UN chief’s plans. So far, there are no terms of reference and there is no timeline.
Nature understands that the idea is still being developed, and that Guterres is leaning towards creating a board that would draw on UN agencies’ existing science networks. Guterres is also aware of the need to take into account that both the UN and the world have changed since the last such board was put in place. All the same, the UN chief needs to end the suspense and set out his plans. Time is of the essence.
Guterres’s predecessor, Ban Ki-moon, had a science advisory board between 2014 and 2016. Its members were tasked with providing advice to the secretary-general on science, technology and innovation for sustainable development. But COVID-19 and climate change have pushed science much higher up the international agenda. Moreover, global challenges are worsening — the pandemic has put back progress towards the UN’s flagship Sustainable Development Goals (SDGs), a plan to end poverty and achieve sustainability by 2030. There is now widespread recognition that science has an important part to play in addressing these and other challenges.
Research underpins almost everything we know about the nature of the virus SARS-CoV-2 and the disease it causes. All countries have access to similar sets of findings, but many are coming to different decisions on how to act on those data — for example, when to mandate mask-wearing or introduce travel restrictions. The UN’s central office needs advice that takes this socio-cultural-political dimension of science into account. It needs advice from experts who study how science is applied and perceived by different constituencies and in different regions.
Science advice from the heart of the UN system could also help with another problem highlighted by the pandemic — how to reinvigorate the idea that it is essential for countries to cooperate on solving global problems.
Climate change is one example. Advice given by the Intergovernmental Panel on Climate Change (IPCC) is being read and applied in most countries, albeit to varying degrees. But climate is also an area in which states are at odds. Despite Guterres’s calls for solidarity, there were times during last month’s climate conference in Glasgow when the atmosphere was combative. Science advisers could help the secretary-general’s office to find innovative ways to encourage cooperation between countries in efforts to meet the targets of the 2015 Paris climate agreement.
The SDGs are also, to some extent, impeded by competition within the UN system. To tackle climate change, manage land and forests, and protect biodiversity, researchers and policymakers need to work collegially. But the UN’s scientific bodies, such as the IPCC, are set up along disciplinary lines with their own objectives, work programmes and rules, all guided by their own institutional histories. The IPCC and the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), for example, have only begun to collaborate in the past few years .
Independence will be key for an advisory role to be credible. Guterres needs to consider an organizational architecture through which UN agencies are represented, and funding could come from outside the UN. But all of those involved would have to accept that their contributions were for common goals — not to promote their own organization’s interests.
Leadership matters, as do communication and support. Guterres should ensure that his scientific advisers are chosen carefully to represent individuals from diverse disciplines and across career stages, and to ensure good representation from low-income countries. The board needs to be well staffed and have a direct line to his office. And it will need a decent budget. Guterres should quickly publish the terms of reference so that the research community has time to provide input and critique.
At its most ambitious, a scientific advisory board to the secretary-general could help to break the culture of individualism that beleaguers efforts to reach collective, global goals, and bring some coherence to the current marketplace of disciplines, ideas and outcomes. This will be a monumental task, requiring significant resources and the will to change. But if the advisers succeed, there will also be valuable lessons for the practice of science, which, as we know all too well, still largely rewards individual effort.