Alcove

Science, culture, complexity

Tag: science communication

  • Notes on covering QM

    1. I learnt last year that quantum systems are essentially linear because the mathematics that physicists have found can describe quantum-mechanical phenomena contain only linear terms. Effects add to each other like 1 + 1 = 2; nothing gets out of control in exponential fashion, at least not usually. I learnt this by mistake in an article published in 1998 when I was trying to learn more about the connection between the Riemann zeta function and ‘quantum chaos’. This is to say that physicists take for granted several concepts – many of which might even be too ‘basic’ for them to have to clarify to a science reporter – that the reporter may only accidentally discover.
    2. “Classical systems are, roughly speaking, defined by well-bounded theories and equations, most of which were invented to describe them. But the description of quantum systems often invokes concepts and mathematical tools that can be found strewn around many other fields of physics.” This impression was unexpectedly disorienting when it first struck. After many years, I realised that the problem lies in my (our?) schooling: I learnt concepts in classical physics in a way that closely tied them to other things I was learning at the same time. Could that be why complicated forms of Euclidean geometry come up at the same time as optics, and vector algebra at the same time as calculus? But it also strikes me that quantum systems lend themselves more readily to be described by more than one theory because of the significant diversity of effects on offer.
    3. The edge of physics is a more wonderful place than the middle because there’s a lot of creativity at work at the edge. This statement is very true for classical physics but vaguely at best for quantum physics. One reason is the diversity of effects: a system that is intractable in statistical mechanics might suddenly offer glimpses of order and predictability when viewed through the lens of quantum field theory. More than a few problems require ‘goat solutions’ – a personal term for an assumption thrown in to make a problem amenable to solving in such a way that the solution doesn’t retain any effects of the assumption (reason for the choice of words here). In some instances, physicists’ assumptions have brought the Iron Man films to mind: the assumptions are in the realm of the fantastic, but are still bound by a discipline that prevents runaway imagination.
    4. Researchers who use the tools of mathematical physics seem to take mathematical notation for granted. Statements of the following form may seem simple but actually pack a lot of information: “Consider a function f(x, y) of the form Σ xip where p is equal to dy/dt in some domain…” (an obviously made up example). I’m all the more spooked when I encounter symbols whose names themselves are beyond me, like ζ or Π, or when the logarithms make an appearance. We need to acknowledge the importance of being habituated to these terms. To a physicist who has spent many years dealing with that operation, a summation might mean a straightforward accumulation of certain effects, but in my mind it always invokes a series of complex sums. I don’t know what else to visualise.
    5. Only a small minority of physicists in India can talk in interesting ways about their work. They use interesting turns of phrase, metaphors borrowed from a book or a play, and sometimes contemplate what their and/or others’ work is telling them about the universe and our place in it. I don’t know why this is rare.

  • Neuromorphic hype

    We all know there’s a difference between operating an Indica Diesel car and a WDP 4 diesel locomotive. The former has two cylinders and the latter 16. But that doesn’t mean the WDP 4 simply has eight times more components as the Indica. This is what comes to my mind when I come across articles that trumpet an achievement without paying any attention to its context.

    In an example from yesterday, IEEE Spectrum published an article with the headline ‘Nanowire Synapses 30,000x Faster Than Nature’s’. An artificial neural network is a network of small data-processing components called neurons. Once the neurons are fed data, they work together to analyse it and solve problems (like spotting the light from one star in a picture of a galaxy). The network also iteratively adjusts the connections between neurons, called synapses, so that the neurons cooperate more efficiently. The architecture and the process broadly mimic the way the human brain works, so they’re also collected under the label ‘neuromorphic computing’.

    Now consider this excerpt:

    “… a new superconducting photonic circuit … mimics the links between brain cells—burning just 0.3 percent of the energy of its human counterparts while operating some 30,000 times as fast. … the synapses are capable of [producing output signals at a rate] exceeding 10 million hertz while consuming roughly 33 attojoules of power per synaptic event (an attojoule is 10-18 of a joule). In contrast, human neurons have a maximum average [output] rate of about 340 hertz and consume roughly 10 femtojoules per synaptic event (a femtojoule is 10-15 of a joule).”

    The article, however, skips the fact that the researchers operated only four circuit blocks in their experiment – while there are 86 billion neurons on average in the human brain working at the ‘lower’ efficiency. When such a large assemblage functions together, there are emergent problems that aren’t present when a smaller assemblage is at work, like removing heat and clearing cellular waste. (The human brain also contains “85 billion non-neuronal cells”, including the glial cells that support neurons.) The energy efficiency of the neurons must be seen in this context, instead of being directly compared to a bespoke laboratory setup.

    Philip W. Anderson’s ‘more is different’ argument provides a more insightful argument against such reductive thinking. In a 1972 essay, Anderson, a theoretical physicist, wrote:

    “The ability to reduce everything to simple fundamental laws does not imply the ability to start from those laws and reconstruct the universe. In fact, the more the elementary particle physicists tell us about the nature of the fundamental laws the less relevance they seem to have to the very real problems of the rest of science, much less to those of society.”

    He contended that the constructionist hypothesis – that you can start from the first principles and arrive straightforwardly at a cutting-edge discovery in that field – “breaks down” because it can’t explain “the twin difficulties scale and complexity”. That is, things that operate on larger scale and with more individual parts are physically greater than the sum of those parts. (I like to think Anderson’s insight to be the spatial analogue of L.P. Hartley’s time-related statement of the same nature: “The past is a foreign country, they do things differently there.”)

    So let’s not celebrate something because it’s “30,000x faster than” the same thing in nature – as the Spectrum article’s headline goes – but because it represents good innovation in and of itself. Indeed, the researchers who conducted the new study and are quoted in the article don’t make the comparison themselves but focus on the leap forward their innovation portends in the field of neuromorphic computing.

    Faulty comparisons on the other hand could inflate readers’ expectations about what the outcomes of future innovation could be, and when it (almost) inevitably starts to fall behind nature’s achievements, those unmet expectations could seed disillusionment. We’ve already had this happen with quantum computing. Spectrum‘s choice could have been motivated by wanting to pique readers’ interest, which is a fair thing to aspire to, but it remains that the headline employed a clichéd comparison, with nature, instead of expending more effort and framing the idea right.

  • The passive voice is political

    Eric Martinez, Francis Mollica and Edward Gibson of the Massachusetts Institute of Technology and the University of Edinburgh won an Ig Nobel Prize for literature this year for their work on what makes legal documents so hard to read. Ironically, the abstract of their paper, published in July 2022, is also very hard to read, coming in at 165 words in just five sentences:

    Despite their ever-increasing presence in everyday life, contracts remain notoriously inaccessible to laypeople. Why? Here, a corpus analysis (n ≈10 million words) revealed that contracts contain startlingly high proportions of certain difficult-to-process features–including low-frequency jargon, center-embedded clauses (leading to long-distance syntactic dependencies), passive voice structures, and non-standard capitalization–relative to nine other baseline genres of written and spoken English. Two experiments (N=184) further revealed that excerpts containing these features were recalled and comprehended at lower rates than excerpts without these features, even for experienced readers, and that center-embedded clauses inhibited recall more-so than other features. These findings (a) undermine the specialized concepts account of legal theory, according to which law is a system built upon expert knowledge of technical concepts; (b) suggest such processing difficulties result largely from working-memory limitations imposed by long-distance syntactic dependencies (i.e., poor writing) as opposed to a mere lack of specialized legal knowledge; and (c) suggest editing out problematic features of legal texts would be tractable and beneficial for society at-large.

    But nitpicks aside, I hope the award will bring more attention to why writing in the passive voice is problematic.

    1. It makes for duller reading.
    2. It glosses over actors who are performing an action and focuses on those on whom the action is being performed.

    The first problem is not an opinion: readers like to be able to visualise what they’re reading. It makes reading a more interesting and immersive experience. This is why “show, don’t tell” is always good advice. But when the writer leaves out the performers of an action – everything from day-dreaming to a heist – a part of the picture disappears. The second problem is obviously dangerous but it can also impart the narrative with political overtones that the writer might like to do without. For example, writing “B was hit” instead of writing “A hit B” keeps the focus on the nature of the violence and recipient. A, the perpetrator, stays out of the picture, out of the narrative and out of readers’ conception of what really happened. If a writer intends to keep the focus on B as a way to humanise them, it doesn’t have to come at the cost of forgetting A. The way to construct the identities of A and B is with narrative – and not with grammatical techniques like the passive voice. If all the sentences in a given piece are in the passive voice, it will still be possible to build a narrative that is fair to B and suitably consternated towards A. The inverse is also true: you can write a piece using the active voice in all sentences and still build up to a narrative that’s unfair to B. The passive voice may not compromise your ability to faithfully describe reality but it will get in the way of what the reader takes away. Reading is a psychological experience and every little adjustment matters to whether your attempt to persuade succeeds.

    Unfortunately, many science writers in India – especially those who have trained as scientists – employ the passive voice in a way that reveals the clear influence of scientific writing on their brand of English. In scientific writing – i.e. the labour that produces the text in research papers – both narrative and grammatical technique converge on the desirability of removing the scientist, as the performer of an experiment, from the picture. I dislike this sort of writing because a) it’s founded on the premise that the scientist’s identity or choices don’t matter to the experiment’s outcomes, whereas there are several examples in history of researchers’ identities influencing the questions they choose to ask, and answer, and b) as the Ig Nobel Prize has acknowledged, it makes for needlessly difficult reading. And not just me: even scientists have spoken up about how they’re having a harder time making sense of scientific papers. I’ve written before as to why science communication is not an add-on to science itself but a separate enterprise animated by its own skills and goals. Switching from the narrative-grammatical coincidence associated with ‘good science’ to the narrative-grammatical separation is one of the dividing lines. When scientists don’t make this switch, they’re at risk of participating in a communication exercise that’s liable to overlook the relationships between scientists’ identities and their ideas.

    Note that, in India, a non-trivial number of people come into sophisticated forms of English use by engaging with the scientific enterprise. When The Wire Science first published its ‘submission guidelines’, some readers told us that our decision to enforce them was unfair because different people write in different ways. I agreed – but didn’t edit them because something someone told me at ACJ still rings true: before you attempt poetry, you must understand grammar so you know how exactly to break it.

    Being introduced to English in the walled garden of science habituates people to using English in a certain way – a way that they consider to be good and effective but which is so only in the limited context of scientific work. It fails significantly and repeatedly when writers use it to engage with non-experts from the problems I noted above. It also doesn’t help that the bulk of scientists conducting research in India at the moment are (cis)male and Brahmin, thus not likely to perceive discrimination along these axes, and thus not likely to perceive the need to acknowledge it in the way they use their language. If you had “writing about particle physics” in mind and have been using it to contextualise my arguments, you may not have much luck; instead, I suggest considering “agriculture”, “psychology”, “biomedicine”, “pedagogy” or “astronomy”. (It’s not a coincidence that India’s lower-tech scientific enterprises have been more assailed by such discrepancies.) Irrespective of whether it is good/bad English, the passive voice doesn’t make for good communication. It may not, and never, affect readers’ ability to understand what you alone are communicating, but ditching it for the active voice could a) engender a habit among readers to expect it, and b) encourage other writers to adopt it when they’re writing on topics where the difference is crucial.

  • On anticipation and the history of science

    In mid-2012, shortly after physicists working with the Large Hadron Collider (LHC) in Europe had announced the discovery of a particle that looked a lot like the Higgs boson, there was some clamour in India over news reports not paying enough attention or homage to the work of Satyendra Nath Bose. Bose and Albert Einstein together developed Bose-Einstein statistics, a framework of rules and principles that describe how fundamental particles called bosons behave. (Paul A.M. Dirac named these particles in Bose’s honour.) The director-general of CERN, the institute that hosts the LHC, had visited India shortly after the announcement and said in a speech in Kolkata that in honour of Bose, he and other physicists had decided to capitalise the ‘b’ in ‘boson’.

    It was a petty victory of a petty demand, but few realised that it was also misguided. Bose made the first known (or at least published) attempts to understand the particles that would come to be called bosons – but neither he nor Einstein anticipated the existence of the Higgs boson. There have also been some arguments (justified, I think) that Bose wasn’t awarded a Nobel Prize for his ideas because he didn’t make testable predictions; Einstein received the Nobel Prize for physics in 1915 for anticipating the photoelectric effect. The point is that it was unreasonable to expect Bose’s work to be highlighted, much less attributed, as some had demanded at the time, every time we find a new boson particle.

    What such demands only did was to signal an expectation that the reflection of every important contribution by an Indian scientist ought to be found in every major discovery or invention. Such calls detrimentally affect the public perception of science because they are essentially contextless.

    Let’s imagine that discovery of the Higgs boson was the result of series of successes, depicted thus:

    O—o—o—o—o—O—O—o—o—O—o—o—o—O

    An ‘O’ shows a major success and an ‘o’ shows a minor success, where major/minor could mean the relative significance within particle physics communities, the extent to which physicists anticipated it or simply the amount of journal/media coverage it received. In this sequence, Bose’s paper on a certain class of subatomic particles could be the first ‘O’ and the discovery of the Higgs boson the last ‘O’. And looking at this sequence, one could say Bose’s work led to a lot of the work that came after and ultimately led to the Higgs boson. However, doing that would diminish the amount of study, creativity and persistence that went into each subsequent finding – and would also ignore the fact that we have identified only one branch of endeavour, leading from Bose’s work to the Higgs boson, whereas in reality there are hundreds of branches crisscrossing each other at every o, big or small – and then there are countless epiphanies, ideas and flashes, each one less the product of following the scientific method and more of a mysterious combination of science and intuition.

    By reducing the opportunity to celebrate Bose’s work by pointing to just the Higgs boson point on the branch, we lose the opportunities to know and celebrate the importance of Bose’s work for all the points in between, but especially the points that we still haven’t taken the trouble to understand.

    Recently, a couple people forwarded to me a video on WhatsApp of an Indian-American electrical engineer named Nisar Ahmed. I learnt when in college (studying engineering) that Nisar Ahmed was the co-inventor, along with K. Ramamohan Rao, of the direct cosine transform, a technique to transmit a given amount of information using fewer bits than those contained in the information itself. The video introduced Ahmed’s work as the basis for our being able to take video-conferencing for granted; direct cosine transform allows audiovisual data to be compressed by two, maybe three orders of magnitude, making its transmission across the internet much less resource-intensive than if it had to be transmitted without compression.

    However, the video did little to address the immediate aftermath of Ahmed’s and Rao’s paper, the other work by other scientists that built on it, as well as its use in other settings, and rested on the drawing just one connection between two fairly unrelated events (direct cosine transform and their derivatives, many of them created in the same decade, heralded signal compression, but they didn’t particularly anticipate different forms of communication).

    This flattening of the history of science, and technology as the case may be, may be entertaining but it offers no insights into the processes at work behind these inventions, and certainly doesn’t admit any other achivements before each development. In the video, Ahmed reads out tweets by people reacting to his work as depicted on the show This Is Us. One of them says that it’s because of him, and because of This Is Us, that people are now able to exchange photos and videos of each other around the world, without worrying about distance. But… no; Ahmed himself says in the video, “I couldn’t predict how fast the technology would move” (based on his work).

    Put it simply, I find such forms of communication – and thereunto the way we are prompted to think about science – objectionable because they are content with ‘what’, and aren’t interested in ‘when’, ‘why’ or ‘how’. And simply enumerating the ‘what’ is practically non-scientific, more so when they’re a few particularly sensational whats over others that encourage us to ignore the inconvenient details. Other similar recent examples were G.N. Ramachandran, whose work on protein structure, especially Ramachandran plots, have been connected to pharmaceutical companies’ quest for new drugs and vaccines, and Har Gobind Khorana, whose work on synthesising RNA has been connected to mRNA vaccines.

  • A false union in science journalism

    At what point does a journalist become a stenographer? Most people would say it’s when the journalist stops questioning claims and reprints them uncritically, as if they were simply a machine. So at what point does a science journalist become a stenographer? You’ll probably say at the same point – when they become uncritical of claims. I disagree: I believe the gap between being critical and being non-critical is smaller when it comes to science journalism simply because of the nature of its subject.

    The scientific enterprise in itself is an attempt to arrive at the truth by critiquing existing truths in different contexts and by simultaneously subtracting biases. The bulk of what we understand to be science journalism is aligned with this process: science journalists critique the same material that scientists do as well, even when they’re following disputes between groups of scientists, but seldom critique the scientists’ beliefs and methods themselves. This is not a distinction without a difference or even a finer point about labels.

    One might say, “There aren’t many stories in which journalists need to critique scientists and/or their methods” – this would be fair, but I have two issues on this count.

    First, both the language and the narrative are typically deferential towards scientists and their views, and steer clear of examining how a scientist’s opinions may have been shaped by extra-scientific considerations, such as their socio-economic location, or whether their accomplishments were the product of certain unique privileges. Second, at the level of a collection of articles, science journalists who haven’t critiqued science will likelier than not have laid tall, wide bridges between scientists and non-scientists but won’t have called scientists, or the apparatuses of science itself, out on their bullshit.

    One way or another, a science journalism that’s uncritical of science often leads to the impression that the two enterprises share the same purpose: to advance science, whether by bringing supposedly important scientific work to the attention of politicians or by building the public support for good scientific work. And this impression is wrong. I don’t think that science journalists have an obligation to help science, and I also don’t think that science journalists should.

    As it happens, science journalism is often treated differently than, say, journalism that’s concerned with political or financial matters. I completely understand why. But I don’t think there has been much of an effort to flip this relationship to consider whether the conception and practice of science has been improved by the attention of science journalists the way the practices of governance and policymaking have been improved by the attention of those reporting on politics and economics. If I was a wagering man, I’d wager ‘no’, at least not in India.

    And the failure to acknowledge this corollary of the relationship between science and science journalism, leave alone one’s responsibility as a science journalist, is to my mind a deeper cause for the persistence of both stenographic and pro-science science journalism in some quarters. I thought to write this down when reading a new editorial by Holden Thorpe, the editor of Science. He says here:

    It’s not just a matter of translating jargon into plain language. As Kathleen Hall Jamieson at the University of Pennsylvania stated in a recent article, the key is getting the public to realize that science is a work in progress, an honorably self-correcting endeavor carried out in good faith.

    Umm, no. Science is a work in progress, sure, but I have neither reason nor duty to explain that the practice of science is honourable or that it is “carried out in good faith”. (It frequently isn’t.) Granted, the editorial focuses on communicators, not journalists, but I’d place communicators on the journalism side of the fence, instead of on the science side: the purposes of journalists and communicators deviate only slightly, and for the most part both groups travel the same path.

    The rest of Thorpe’s article focuses on the fact that not all scientists can make good communicators – a fact that bears repeating if only because some proponents of science communication tend to go overboard with their insistence on getting scientists to communicate their work to a non-expert audience. But in restricting his examples to full-blown articles, radio programmes, etc., he creates a bit of a false binary (if earlier he created a false union): that you’re a communicator only if you’ve produced ‘packages’ of that size or scope. But I’ve always marvelled at the ability of some reporters, especially at the New York Times‘ science section, to elicit some lovely quotes from experts. Here are three examples:

    This is science communication as well. Of course, not all scientists may be able to articulate things so colourfully or arrive at poignant insights in their quotes but surely there are many more scientists who can do this than there are scientists who can write entire articles or produce engaging podcasts. And a scientist who allows your article to say interesting things is, I’m sure you’ll agree, an invaluable resource. Working in India, for example, I continue to have to give reporters I commission from extra time to file their stories because many scientists don’t want to talk – and while there are many reasons for this, a big and common one is that they believe communication is pointless.

    So overall, I think there needs to be more leeway in what we consider to be communication, if only so it encourages scientists to speak to journalists (whom they trust, of course) instead of being put off by the demands of a common yet singular form of this exercise, as well as what we imagine the science journalist’s purpose to be. If we like to believe that science communication and/or journalism creates new knowledge, as I do, instead of simply being adjacent to science itself, then it must also craft a purpose of its own.

    Featured image credit: Conol Samuel/Unsplash.

  • The omicron variant and scicomm

    Somewhere between the middle of India’s second major COVID-19 outbreak in March-May this year and today, a lot of us appear to have lost sight of a fact that was central to our understanding of COVID-19 outbreaks in 2020: that the only way a disease outbreak, especially of the novel coronavirus, can be truly devastating is if the virus collaborated with poor public health infrastructure and subpar state response. (Similarly, even a variant deemed mild in, say, the UK could lead to disaster in Chennai.) The virus alone doesn’t lead to catastrophic outcomes.

    Just as India’s second outbreak was picking up speed, there was a considerable awareness that the delta variant was wreaking as much havoc as we were letting it. In fact, the Indian government was more than letting it. But since the outbreak began to subside in kurtotic fashion and, much later, as the omicron variant appeared on the scene, the focus on the latter has appeared to overwhelm – at least in public discourse – the extent to which we’re prepared (or not) to face it. Put another way, the focus on the omicron variant and the contexts in which it has been discussed have remained far too scientific. I’m not saying that it should become less scientific but that the social should start finding mention more.

    I realise that everyone is weary of the pandemic and would like if it ended already, and together with the fact that most people in India’s cities have received their two doses of some COVID-19 vaccine, it might seem to everyone that there’s sufficient ground to persist with the idea that the omicron variant couldn’t possibly be devastating, and that we can all return to some kind of normal soon. Now, this is one kind of fatigue. There appears to be a second kind also, based on the fact that the delta variant was the first “major” variant, in a manner of speaking, and the way we talked about it and acted in its potential (and menacing) presence co-evolved with its dispersal through the population.

    The omicron variant, on the other hand, affords both scientists and science communicators the option to simply refer to the narratives and discourses we developed with the delta variant, simply updated to match what we’re finding out about omicron. And this, not surprisingly, has led to a bit of laziness as well. The form I find most lazy, and most annoying, is some scientists’ insistence on pointing to graphs of the number of cases over time in different countries and saying, “If this doesn’t shake us out of our slumber, what will?”

    This is scientism, pure and simple, even if it’s not on the nose: pointing to case trends alone isn’t going to solve anything, especially not in the face of the sort of significant, demographic-wide yearning for a ‘new normal’, or in fact any kind of normal, instead of more and more upheavals. In fact, consider the fact that for most of 2020, most poor people in India believed that if the novel coronavirus had an infection fatality rate of just 1%, it was no big whoop, and that they would continue going to work and eke out a living. Let’s be clear, this is perfectly reasonable. The idea of letting the virus take its course through the population went sideways in Sweden, but in India, if something has a 1% chance of getting you really sick – or even killing you – it’s tragically the case that it quickly falls down a long list of threats, most of which are often much more lethal, beginning, in too many parts of the country, with breathing the air around you or drinking the water that’s available to you.

    To repeat in this context exhortations based solely on graphs printed in English and shared on Twitter that rapidly rising case-loads elsewhere on the planet should suffice to nudge us out of the Indian subcontinent’s collective torpor is a deference to facts that, I’m very tempted to say, understand only 1% of what is going on. Even if these exhortations are directed at state leaders and government officials, they are really misdirected: as I have written before in the context of Anthony Fauci’s senseless interview responses, if the government hasn’t done something that’s obvious to everyone, the reason just can’t be that it hasn’t seen the chart or the numbers you’ve seen to reach your conclusions. The only way such statements could make some sense is if they are intended to galvanise public opinion, but even then, I’m not convinced.

    And seeing these scientists do what they do strikes me that just as much as we’d like to encourage scientists to communicate science as often as is possible, there may be virtue in casting science communication as much in terms of what it does as what it doesn’t. For example, as the number of cases due to the omicron variant of the novel coronavirus is increasing in different parts of the world, socially responsible science communication requires us to not stop at pointing at graphs but to continue to reflect on and articulate how much – or how little – the greater transmissibility of the variant means in and of itself. And in my view, not doing this would just be socially anti-responsible communication: sticking to the science, and accomplishing little overall.

  • The problem with rooting for science

    The idea that trusting in science involves a lot of faith, instead of reason, is lost on most people. More often than not, as a science journalist, I encounter faith through extreme examples – such as the Bloch sphere (used to represent the state of a qubit) or wave functions (‘mathematical objects’ used to understand the evolution of certain simple quantum systems). These and other similar concepts require years of training in physics and mathematics to understand. At the same time, science writers are often confronted with the challenge of making these concepts sensible to an audience that seldom has this training.

    More importantly, how are science writers to understand them? They don’t. Instead, they implicitly trust scientists they’re talking to to make sense. If I know that a black hole curves spacetime to such an extent that pairs of virtual particles created near its surface are torn apart – one particle entering the black hole never to exit and the other sent off into space – it’s not because I’m familiar with the work of Stephen Hawking. It’s because I read his books, read some blogs and scientific papers, spoke to physicists, and decided to trust them all. Every science journalist, in fact, has a set of sources they’re likely to trust over others. I even place my faith in some people over others, based on factors like personal character, past record, transparency, reflexivity, etc., so that what they produce I take only with the smallest pinch of salt, and build on their findings to develop my own. And this way, I’m already creating an interface between science and society – by matching scientific knowledge with the socially developed markers of reliability.

    I choose to trust those people, processes and institutions that display these markers. I call this an act of faith for two reasons: 1) it’s an empirical method, so to speak; there is no proof in theory that such ‘matching’ will always work; and 2) I believe it’s instructive to think of this relationship as being mediated by faith if only to amplify its anti-polarity with reason. Most of us understand science through faith, not reason. Even scientists who are experts on one thing take the word of scientists on completely different things, instead of trying to study those things themselves (see ad verecundiam fallacy).

    Sometimes, such faith is (mostly) harmless, such as in the ‘extreme’ cases of the Bloch sphere and the wave function. It is both inexact and incomplete to think that quantum superposition means an object is in two states at once. The human brain hasn’t evolved to cognate superposition exactly; this is why physicists use the language of mathematics to make sense of this strange existential phenomenon. The problem – i.e. the inexactitude and the incompleteness – arises when a communicator translates the mathematics to a metaphor. Equally importantly, physicists are describing whereas the rest of us are thinking. There is a crucial difference between these activities that illustrates, among other things, the fundamental incompatibility between scientific research and science communication that communicators must first surmount.

    As physicists over the past three or four centuries have relied increasingly on mathematics rather than the word to describe the world, physics, like mathematics itself, has made a “retreat from the word,” as literary scholar George Steiner put it. In a 1961 Kenyon Review article, Steiner wrote, “It is, on the whole, true to say that until the seventeenth century the predominant bias and content of the natural sciences were descriptive.” Mathematics used to be “anchored to the material conditions of experience,” and so was largely susceptible to being expressed in ordinary language. But this changed with the advances of modern mathematicians such as Descartes, Newton, and Leibniz, whose work in geometry, algebra, and calculus helped to distance mathematical notation from ordinary language, such that the history of how mathematics is expressed has become “one of progressive untranslatability.” It is easier to translate between Chinese and English — both express human experience, the vast majority of which is shared — than it is to translate advanced mathematics into a spoken language, because the world that mathematics expresses is theoretical and for the most part not available to our lived experience.

    Samuel Matlack, ‘Quantum Poetics’, The New Atlantic, 2017

    However, the faith becomes more harmful the further we move away from the ‘extreme’ examples – of things we’re unlikely to stumble on in our daily lives – and towards more commonplace ideas, such as ‘how vaccines work’ or ‘why GM foods are not inherently bad’. The harm emerges from the assumption that we think we know something when in fact we’re in denial about how it is that we know that thing. Many of us think it’s reason; most of the time it’s faith. Remember when, in Friends, Monica Geller and Chandler Bing ask David the Scientist Guy how airplanes fly, and David says it has to do with Bernoulli’s principle and Newton’s third law? Monica then turns to Chandler with a knowing look and says, “See?!” To which Chandler says, “Yeah, that’s the same as ‘it has something to do with wind’!”

    The harm is to root for science, to endorse the scientific enterprise and vest our faith in its fruits, without really understanding how these fruits are produced. Such understanding is important for two reasons.

    First, if we trust scientists, instead of presuming to know or actually knowing that we can vouch for their work. It would be vacuous to claim science is superior in any way to another enterprise that demands our faith when science itself also receives our faith. Perhaps more fundamentally, we like to believe that science is trustworthy because it is evidence-based and it is tested – but the COVID-19 pandemic should have clarified, if it hasn’t already, the continuous (as opposed to discrete) nature of scientific evidence, especially if we also acknowledge that scientific progress is almost always incremental. Evidence can be singular and thus clear – like a new avian species, graphene layers superconducting electrons or tuned lasers cooling down atoms – or it can be necessary but insufficient, and therefore on a slippery slope – such as repeated genetic components in viral RNA, a cigar-shaped asteroid or water shortage in the time of climate change.

    Physicists working with giant machines to spot new particles and reactions – all of which are detected indirectly, through their imprints on other well-understood phenomena – have two important thresholds for the reliability of their findings: if the chance of X (say, “spotting a particle of energy 100 GeV”) being false is 0.27%, it’s good enough to be evidence; if the chance of X being false is 0.00006%, then it’s a discovery (i.e., “we have found the particle”). But at what point can we be sure that we’ve indeed found the particle we were looking for if the chance of being false will never reach 0%? One way, for physicists specifically, is to combine the experiment’s results with what they expect to happen according to theory; if the two match, it’s okay to think that even a less reliable result will likely be borne out. Another possibility (in the line of Karl Popper’s philosophy) is that a result expected to be true, and is subsequently found to be true, is true until we have evidence to the contrary. But as suitable as this answer may be, it still doesn’t neatly fit the binary ‘yes’/’no’ we’re used to, and which we often expect from scientific endeavours as well (see experience v. reality).

    (Minor detour: While rational solutions are ideally refutable, faith-based solutions are not. Instead, the simplest way to reject their validity is to use extra-scientific methods, and more broadly deny them power. For example, if two people were offering me drugs to suppress the pain of a headache, I would trust the one who has a state-sanctioned license to practice medicine and is likely to lose that license, even temporarily, if his prescription is found to have been mistaken – that is, by asserting the doctor as the subject of democratic power. Axiomatically, if I know that Crocin helps manage headaches, it’s because, first, I trusted the doctor who prescribed it and, second, Crocin has helped me multiple times before, so empirical experience is on my side.)

    Second, if we don’t know how science works, we become vulnerable to believing pseudoscience to be science as long as the two share some superficial characteristics, like, say, the presence and frequency of jargon or a claim’s originator being affiliated with a ‘top’ institute. The authors of a scientific paper to be published in a forthcoming edition of the Journal of Experimental Social Psychology write:

    We identify two critical determinants of vulnerability to pseudoscience. First, participants who trust science are more likely to believe and disseminate false claims that contain scientific references than false claims that do not. Second, reminding participants of the value of critical evaluation reduces belief in false claims, whereas reminders of the value of trusting science do not.

    (Caveats: 1. We could apply the point of this post to this study itself; 2. I haven’t checked the study’s methods and results with an independent expert, and I’m also mindful that this is psychology research and that its conclusions should be taken with salt until independent scientists have successfully replicated them.)

    Later from the same paper:

    Our four experiments and meta-analysis demonstrated that people, and in particular people with higher trust in science (Experiments 1-3), are vulnerable to misinformation that contains pseudoscientific content. Among participants who reported high trust in science, the mere presence of scientific labels in the article facilitated belief in the misinformation and increased the probability of dissemination. Thus, this research highlights that trust in science ironically increases vulnerability to pseudoscience, a finding that conflicts with campaigns that promote broad trust in science as an antidote to misinformation but does not conflict with efforts to install trust in conclusions about the specific science about COVID-19 or climate change.

    In terms of the process, the findings of Experiments 1-3 may reflect a form of heuristic processing. Complex topics such as the origins of a virus or potential harms of GMOs to human health include information that is difficult for a lay audience to comprehend, and requires acquiring background knowledge when reading news. For most participants, seeing scientists as the source of the information may act as an expertise cue in some conditions, although source cues are well known to also be processed systematically. However, when participants have higher levels of methodological literacy, they may be more able to bring relevant knowledge to bear and scrutinise the misinformation. The consistent negative association between methodological literacy and both belief and dissemination across Experiments 1-3 suggests that one antidote to the influence of pseudoscience is methodological literacy. The meta-analysis supports this.

    So rooting for science per se is not just not enough, it could be harmful vis-à-vis the public support for science itself. For example (and without taking names), in response to right-wing propaganda related to India’s COVID-19 epidemic, quite a few videos produced by YouTube ‘stars’ have advanced dubious claims. They’re not dubious at first glance, if also because they purport to counter pseudoscientific claims with scientific knowledge, but they are – either for insisting a measure of certainty in the results that neither exist nor are achievable, or for making pseudoscientific claims of their own, just wrapped up in technical lingo so they’re more palatable to those supporting science over critical thinking. Some of these YouTubers, and in fact writers, podcasters, etc., are even blissfully unaware of how wrong they often are. (At least one of them was also reluctant to edit a ‘finished’ video to make it less sensational despite repeated requests.)

    Now, where do these ideas leave (other) science communicators? In attempting to bridge a nearly unbridgeable gap, are we doomed to swing only between most and least unsuccessful? I personally think that this problem, such as it is, is comparable to Zeno’s arrow paradox. To use Wikipedia’s words:

    He states that in any one (duration-less) instant of time, the arrow is neither moving to where it is, nor to where it is not. It cannot move to where it is not, because no time elapses for it to move there; it cannot move to where it is, because it is already there. In other words, at every instant of time there is no motion occurring. If everything is motionless at every instant, and time is entirely composed of instants, then motion is impossible.

    To ‘break’ the paradox, we need to identify and discard one or more primitive assumptions. In the arrow paradox, for example, one could argue that time is not composed of a stream of “duration-less” instants, that each instant – no matter how small – encompasses a vanishingly short but not nonexistent passage of time. With popular science communication (in the limited context of translating something that is untranslatable sans inexactitude and/or incompleteness), I’d contend the following:

    • Awareness: ‘Knowing’ and ‘knowing of’ are significantly different and, I hope, self-explanatory also. Example: I’m not fluent with the physics of cryogenic engines but I’m aware that they’re desirable because liquefied hydrogen has the highest specific impulse of all rocket fuels.
    • Context: As I’ve written before, a unit of scientific knowledge that exists in relation to other units of scientific knowledge is a different object from the same unit of scientific knowledge existing in relation to society.
    • Abstraction: 1. perfect can be the enemy of the good, and imperfect knowledge of an object – especially a complicated compound one – can still be useful; 2. when multiple components come together to form a larger entity, the entity can exhibit some emergent properties that one can’t derive entirely from the properties of the individual components. Example: one doesn’t have to understand semiconductor physics to understand what a computer does.

    An introduction to physics that contains no equations is like an introduction to French that contains no French words, but tries instead to capture the essence of the language by discussing it in English. Of course, popular writers on physics must abide by that constraint because they are writing for mathematical illiterates, like me, who wouldn’t be able to understand the equations. (Sometimes I browse math articles in Wikipedia simply to immerse myself in their majestic incomprehensibility, like visiting a foreign planet.)

    Such books don’t teach physical truths; what they teach is that physical truth is knowable in principle, because physicists know it. Ironically, this means that a layperson in science is in basically the same position as a layperson in religion.

    Adam Kirsch, ‘The Ontology of Pop Physics’, Tablet Magazine, 2020

    But by offering these reasons, I don’t intend to over-qualify science communication – i.e. claim that, given enough time and/or other resources, a suitably skilled science communicator will be able to produce a non-mathematical description of, say, quantum superposition that is comprehensible, exact and complete. Instead, it may be useful for communicators to acknowledge that there is an immutable gap between common English (the language of modern science) and mathematics, beyond which scientific expertise is unavoidable – in much the same way communicators must insist that the farther the expert strays into the realm of communication, the closer they’re bound to get to a boundary beyond which they must defer to the communicator.

  • Scicommers as knowledge producers

    Reading the latest edition of Raghavendra Gadagkar’s column in The Wire Science, ‘More Fun Than Fun’, about how scientists should become communicators and communicators should be treated as knowledge-producers, I began wondering if the knowledge produced by the latter is in fact not the same knowledge but something entirely new. The idea that communicators simply make the scientists’ Promethean fire more palatable to a wider audience has led, among other things, to a belief widespread among scientists that science communicators are adjacent to science and aren’t part of the enterprise producing ‘scientific knowledge’ itself. And this perceived adjacency often belittles communicators by trivialising the work that they do and hiding the knowledge that only they produce.

    Explanatory writing that “enters into the mental world of uninitiated readers and helps them understand complex scientific concepts”, to use Gadagkar’s words, takes copious and focused work. (And if it doesn’t result in papers, citations and h-indices, just as well: no one should become trapped in bibliometrics the way so many scientists have.) In fact, describing the work of communicators in this way dismisses a specific kind of proof of work that is present in the final product – in much the same way scientists’ proofs of work are implicit in new solutions to old problems, development of new technologies, etc. The knowledge that people writing about science for a wider audience produce is, in my view, entirely distinct, even if the nature of the task at hand is explanatory.

    In his article, Gadagkar writes:

    Science writers should do more than just reporting, more than translating the gibberish of scientists into English or whatever language they may choose to write in. … Science writers are in a much better position to make lateral comparisons, understand the process of science, and detect possible biases and conflicts of interest, something that scientists, being insiders, cannot do very well. So rather than just expect them to clean up our messy prose, we should elevate science writers to the role of knowledge producers.

    My point is about knowledge arising from a more limited enterprise – i.e. explanation – but which I think can be generalised to all of journalism as well (and to other expository enterprises). And in making this point, I hope my two-pronged deviation from Gadagkar’s view is clear. First, science journalists should be treated as knowledge producers, but not in the limited confines of the scientific enterprise and certainly not just to expose biases; instead, communicators as knowledge producers exist in a wider arena – that of society, including its messy traditions and politics, itself. Here, knowledge is composed of much more than scientific facts. Second, science journalists are already knowledge producers, even when they’re ‘just’ “translating the gibberish of scientists”.

    Specifically, the knowledge that science journalists produce differs from the knowledge that scientists produce in at least two ways: it is accessible and it makes knowledge socially relevant. What scientists find is not what people know. Society broadly synthesises knowledge from information that it weights together with extra-scientific considerations, including biases like “which university is the scientist affiliated with” and concerns like “will the finding affect my quality of life”. Journalists are influential synthesisers who work with or around these and other psychosocial stressors to contextualise scientific findings, and thus science itself. Even when they write drab stories about obscure phenomena, they make an important choice: “this is what the reader gets to read, instead of something else”.

    These properties taken together encompass the journalist’s proof of work, which is knowledge accessible to a much larger audience. The scientific enterprise is not designed to produce this particular knowledge. Scientists may find that “leaves use chlorophyll to photosynthesise sunlight”; a skilled communicator will find that more people know this, know why it matters and know how they can put such knowledge to use, thus fostering a more empowered society. And the latter is entirely new knowledge – akin to an emergent object that is greater than the sum of its scientific bits.

  • On the lab-leak hypothesis

    One problem with the debate over the novel coronavirus’s “lab leak” origin hypothesis is a problem I’m starting to see in quite a few other areas of pandemic-related analysis and discussion. It’s that no one will say why others are wrong, even as they insist others are, and go on about why they are right.

    Shortly after I read Nicholas Wade’s 10,000-word article on Medium, I pitched a summary to a medical researcher, whose first, and for a long time only, response was one word: “rubbish”. Much later, he told me about how the virus could have evolved and spread naturally. Even if I couldn’t be sure if he was right, having no way to verify the information except to bounce it off a bunch of other experts, I was sure he thought he was right. But how was Wade wrong? I suspect for many people the communication failures surrounding this (or a similar) question may be a sticking point.

    (‘Wade’, after the first mention, is shorthand for an author of a detailed, non-trivial article that considers the lab-leak hypothesis, irrespective of what conclusion it reaches. I’m cursorily aware of Wade’s support for ‘scientific racism’, and by using his name, I don’t condone any of his views on these and other matters. Other articles to read on the lab-leak topic include Nicholson Baker’s in Intelligencer and Katherine Eban’s in Vanity Fair.)

    We don’t know how the novel coronavirus originated, nor are we able to find out easily. There are apparently two possibilities: zoonotic spillover and lab-leak (both hypotheses even though the qualification has been more prominently attached to the latter).

    Quoting two researchers writing in The Conversation:

    In March 2020, another article published in Nature Medicine provided a series of scientific arguments in favour of a natural origin. The authors argued: The natural hypothesis is plausible, as it is the usual mechanism of emergence of coronaviruses; the sequence of SARS-CoV-2 is too distantly related from other known coronaviruses to envisage the manufacture of a new virus from available sequences; and its sequence does not show evidence of genetic manipulation in the laboratory.

    Proponents of the lab-leak hypothesis (minus the outright-conspiratorial) – rather more broadly the opponents of the ‘zoonotic-spillover’-evangelism – have argued that lab leaks are more common than we think, the novel coronavirus has some features that suggest the presence of a human hand, and a glut of extra-scientific events that point towards suspicious research and communication by members of the Wuhan Institute of Virology.

    However, too many counterarguments to Wade’s and others’ articles along similar lines have been to brush the allegations aside, as if they were so easily dismissed – like my interlocutor’s “rubbish”. And it’s an infuriating response. To me at least (as someone who’s been at the receiving end of many such replies), it smacks of an attitude that seems to say (a) “you’re foolish to take this stuff seriously,” (b) “you’re being a bad journalist,” (c) “I doubt you’ll understand the answer,” and (d) “I think you should just trust me”.

    I try not to generalise (c) and (d) to maintain my editorial equipoise, so to speak – but it’s been hard. There’s too much of too many scientists going around insisting we should simply listen to them, while making no efforts to ensure non-experts can understand what they’re saying, much less admitting the possibility that they’re kidding themselves (although I do think “science is self-correcting” is a false adage). In fact, proponents of the zoonotic-spillover hypothesis and others like to claim that their idea is more likely, but this is often a crude display of scientism: “it’s more scientific, therefore it must be true”. The arguments in favour of this hypothesis are also being increasingly underrepresented outside the scientific literature, which isn’t a trivial consideration because the disparity could exacerbate the patronising tone of (c) and (d), and render scientists less trustworthy.

    Science communication and/or journalism are conspicuous by absence here, but I also think the problem with the scientists’ attitude is broader than that. Short of engaging directly in the activities of groups like DRASTIC, journalists take a hit when scientists behave like pedagogic communication is a waste of time. More scientists should make more of an effort to articulate themselves better. It isn’t wise to dismiss something that so many take seriously – although this is also a slippery slope: apply it as a general rule, and soon you may find yourself having to debunk in great detail a dozen ridiculous claims a day. Perhaps we can make an exception for the zoonotic-spillover v. lab-leak hypotheses contest? Or is there a better heuristic? I certainly think there should be one instead of having none at all.

    Proving the absence is harder than proving the presence of something, and that’s why everyone might be talking about why they’re right. However, in the process, many of these people seem to forget that what they haven’t denied is still firmly in the realm of the possible. Actually, they don’t just forget it but entirely shut down the idea. This is why I agree with Dr Vinay Prasad’s words in MedPage Today:

    If it escaped due to a wet market, I would strongly suggest we clean up wet markets and improve safety in BSL laboratories because a future virus could come from either. And, if it was a lab leak, I would strongly suggest we clean up wet markets and improve safety in BSL 3 and 4 … you get the idea. Both vulnerabilities must be fixed, no matter which was the culprit in this case, because either could be the culprit next time.

    His words provide an important counterweight of sorts to a tendency from the zoonotic-spillover quarter to treat articles about the lab-leak possibility as a monolithic allegation instead of as a collection of independent allegations that aren’t equally unlikely. For example, the Vanity Fair, Newsweek and Wade’s articles have all also called into question safety levels at BSL 3 and 4 labs, whether their pathogen-handling protocols sufficiently justify the sort of research we think is okay to conduct, and allegations that various parties have sought to suppress information about the activities at such facilities housed in the Wuhan Institute.

    I don’t buy the lab-leak hypothesis and I don’t buy the zoonotic-spillover hypothesis; in fact, I don’t personally care for the answer because I have other things to worry about, but I do buy that the “scientific illiberalism” that Dr Prasad talks about is real. And it’s tied to other issues doing the rounds now as well. For example, Newsweek‘s profile of DRASTIC’s work has been a hit in India thanks to the work of ‘The Seeker’, the pseudonym for a person in their 20s living in “Eastern India”, who uncovered some key documents that cast suspicion on Wuhan Institute’s Shi Zhengli’s claims vis-à-vis SARS-CoV-2. And two common responses to the profile (on Twitter) have been:

    1. “In 2020, when people told me about the lab-leak hypothesis, I dismissed them and argued that they shouldn’t take WhatsApp forwards seriously.”
    2. “Journalism is redundant.”

    (1) is said as if it’s no longer true – but it is. The difference between the WhatsApp forwards of February-April 2020 and the articles and papers of 2021 is the body of evidence each set of claims was based on. Luc Montagnier was wrong when he spoke against the zoonotic-spillover hypothesis last year simply because his reasoning was wrong. The reasons and the evidence matter; otherwise, you’re no better than a broken clock. Facile WhatsApp forwards and right-wingers’ ramblings continue to deserve to be treated with extreme scepticism.

    Just because a conspiracy theory is later proven to have merit doesn’t make it not a conspiracy theory; their defining trait is belief in the absence of evidence. The most useful response, here, is not to get sucked into the right-wing fever swamps, but to isolate legitimate questions, and try and report out the answers.

    Columbia Journalism Review, April 15, 2020

    The second point is obviously harder to fight back, considering it doesn’t stake a new position as much as reinforces one that certain groups of people have harboured for many years now. It’s one star aligning out of many, so its falling out of place won’t change believers’ minds, and because the believers’ minds will be unchanged, it will promptly fall back in place. This said, apart from the numerous other considerations, I’ll say investigations aren’t the preserve of journalists, and one story that was investigated to a greater extent by non-journalists – especially towards a conclusion that you probably wish to be true – has little necessarily to do with journalism.

    In addition, the picture is complicated by the fact that when people find that they’re wrong, they almost never admit it – especially if other valuable things, like their academic or political careers, are tied up with their reputation. On occasion, some turn to increasingly more technical arguments, or close ranks and advertise a false ‘scientific consensus’ (insofar as such consensus can exist as the result of any exercise less laborious than the one vis-à-vis anthropogenic global warming), or both. ‘Isolating the legitimate questions’ here apart – from both sides, mind you – needs painstaking work that only journalists can and will do.

    Featured image credit: Ethan Medrano/Pexels.

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