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SciWriteLabs 7.1: The New York Times’s Amy Harmon on neurodiversity and writing about autism

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Seth Mnookin is a Lecturer in MIT’s Graduate Program in Science Writing. His most recent book, The Panic Virus: The True Story Behind the Vaccine-Autism Controversy, was called a “tour de force” by The New York Times and “a book that should be required reading at every medical school in the world…a brilliant piece of reportage and science writing” by The Wall Street Journal.

He is also the author of the 2006 bestseller Feeding the Monster: How Money, Smarts, and Nerve Took a Team to the Top, which chronicles the challenges and triumphs of the John Henry-Tom Werner ownership group of the Boston Red Sox, and 2004′s Hard News: The Scandals atThe New York Times and Their Meaning for American Media, which was a Washington Post Best Book of the Year.

Since 2005, he has been a contributing editor at Vanity Fair, and he blogs regularly at The Public Library of Science. For more information, visit his website or follow him on Twitter, Google+, or Facebook.

On December 26, The New York Times featured the second installment in “Autism, Grown Up,” an ongoing series by Pulitzer Prize-winning science writer Amy Harmon. The 5,113-word, front-page story, titled “Navigating Love and Autism,” chronicled the courtship and romance of 21-year-old Jack Robison and 20-year-old Kirsten Lindsmith, both of whom have been diagnosed (and self-identify) as having Asperger syndrome.

Similar to Harmon’s first piece in this series, “Autistic and Seeking a Place in the World,” “Navigating Love and Autism” is an incredibly intimiate piece of journalism. It’s freckled with vignettes that wouldn’t feel out of place in short stories by Raymond Carver or Andre Dubus. But the intimacy and narrative flow shouldn’t obscure readers from the incredible effort that went into writing this piece – or the incredible amount of science reporting and research that allowed Harmon to be confident making the statements she made.

Over the last few weeks, I’ve been running lightly edited transcripts of e-mail interviews between Harmon and me about her work, science writing and reporting, and the evolving media landscape on my blog at the Public Library of Science; because of the wide interest expressed by readers, they’re going to be reprinted here. (The first entry is below, the second piece will be posted on Friday, and the final installment will run next week.) Nature.com readers interested in further exploring the issues raised in these conversations can also check out SciWriteLabs, an ongoing feature I curate that addresses issues relevant to science journalism. Finally, David Dobbs interviewed Harmon a few months ago for a great piece in The Open Notebook, a site dedicated to “the story behind the best science stories.”

 

New York Times science reporter Amy Harmon

 

SM: I want to start by going back to some articles you wrote back in 2004 that touched, either directly or indirectly, on the neurodiversity movement. That was a fairly bold topic for the newspaper of record to be tackling. What made you write about it at that time?

AH: I was interested in Asperger syndrome in 2004 because I had an adult family member who I thought fit the description. That person was not interested in being diagnosed, but I figured others must be. The diagnosis itself had only entered the Diagnostic and Statistical Manual a decade earlier, and was just beginning to be widely known.

At the time I was part of a new group of reporters assigned to write what we called “How We Live” stories, about trends in American life, so the idea fit my beat. And when I called around, and visited some support groups, I found that this was in fact happening on a fairly large scale: adults who had previously thought of themselves as fundamentally flawed because of their social oddness were finding some relief in tracing it to a neurological condition.

I never met the librarian I used in my lede to that first piece (“Finding Out: Adults and Autism; An Answer, but Not a Cure, for a Social Disorder,”4/29/04), I only spoke to him on the phone, but I will never forget how visceral his story felt, just listening to it – he wept, he told me, when he came across an article in an academic journal describing Asperger’s. Because he recognized himself.

There was a huge outpouring of response to that article, from people who saw themselves in it and people who thought they saw friends or family members. I heard from lot of people wondering “hey, am *I* on the spectrum? Is my spouse? My relative?’’ etc.  One of those people was the then-editor of the Week in Review, who urged me to do a follow-up piece. And I had wanted to address the eye-rolling that goes on about the Asperger’s diagnosis, which some people see as basically a medical excuse for bad behavior.

So I did a follow-up piece for the Review about a new term that I had not managed to work into the first story — “neurodiversity’’ – and the nascent movement calling for acceptance of all flavors of human oddity, which were increasingly being linked to variations in brain wiring.

That led to one more piece, about what was then a small but vocal group of people on the autism spectrum who were saying they did not want to be cured, that autism was part of who they were. I was fascinated by this polarization of the spectrum, with parents of the more severely affected and typically non-verbal doing everything they could to find a cure, and others, who could express themselves, saying they were part of a civil rights movement for tolerance of neurological differences.

Others have since written more about the neurodiversity movement – including David Wolman, in a memorable 2008 Wired piece, and more recently Steve Silberman, whose tweets and blog posts on the subject are thoughtful and unbelievably comprehensive (he is working on a book about it).

I might have written more then, but I had my daughter that year, and soon after I got back from maternity leave I started writing about new genetic technologies, which led to a series on a cancer clinical trial. When I finished that, at the end of 2010, I pretty much immediately returned to autism, and it was interesting to see how the landscape had changed.

SM: You noted that you were “fascinated by this polarization of the spectrum.” I’ve never covered a story that’s engendered as strong reactions as writing about autism. Did you hear from people who were upset by your stories — and if so, what types of reader responses did you get?

AH: After the 2004 story about people with autism saying “don’t cure us” ran, I got mail from parents whose children are more severely impaired who were really upset. And of course I could see that – what did these so-called autistic people mean, what did I mean, they shouldn’t try to cure their children? Children who were completely uncommunicative, who hurt themselves, whose lives seemed so horribly limited by this condition?

To have only a single term to refer to people with the vast range of autism’s manifestations strikes me as problematic. I see the importance of recognizing what are believed to be the common neurological roots of the different forms of impairment. I also see why “Asperger syndrome” has come to be considered by many experts too ill-defined to be meaningful. But there has got to be some more accurate and evocative way to describe the differences. It’s something I really struggled with in these recent stories. I don’t like “mild autism” because that seems to downplay the considerable challenges faced by people like Jack or Kirsten. And I tried to avoid the terms “high-functioning” and “low-functioning” because they are so vague–does verbal ability equate to function? Not necessarily. Are we just talking about IQ? But IQ is so hard to measure in individuals with autism. What about people who are hyper-articulate and score high on IQ tests but can’t hold a reciprocal conversation?

I heard from parents of more severely affected children after the “Navigating Love” story ran too, but these letters were a bit different. It’s not that they didn’t like the story. It was more that they feel the kind of autism they deal with every day has been marginalized. Because the vast majority of the growth in diagnosis comes from including people like Jack and Kirsten, they’ve kind of come to dominate in the popular image of what autism is. (I do hope to address that segment of the spectrum in a future story.)

I also heard from people on the spectrum who disliked various elements of the story, like the part where Jack and Kirsten contemplate treatments that might make it easier for them to gain insight into other people, including each other, because it implied that there was something wrong with them. (And, in the judgment of these readers, that is not the case.) Another person said the story implied that autistic people could only have romantic relationships with other autistic people. Of course it’s always difficult to try to illuminate the condition of a group of people by writing in-depth about one or two individuals, so I can see where all these complaints are coming from. But I did also hear from a lot of people on the spectrum who said the story gave them insight and a sense of hope. And maybe my favorite emails came from so-called “neurotypicals” — i.e., people who are NOT on the spectrum — who said they saw shades of their own relationship challenges in Jack and Kirsten’s. The main difference, one person said, is that “they are much more honest.”

 

Story-telling, Statistics, And Other Grave Scientific Insults

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In the second of our series of guest blog posts, Aaron Clauset (homepage, blog), Assistant Professor of Computer Science and Member of the Colorado Initiative in Molecular Biotechnology at the University of Colorado at Boulder, discusses the tensions between number- and narrative-based descriptions in science.

The New York Times (and the NYT Magazine) has been running a series of pieces about math, science and society written by John Allen Paulos, a mathematics professor at Temple University and author of several popular books. His latest piece caught my eye because it’s a topic close to my heart: stories vs. statistics. That is, when we seek to explain something1, do we use statistics and quantitative arguments using mainly numbers or do we use stories and narratives featuring actors, motivations and conscious decisions?2 Here are a few good excerpts from Paulos’s latest piece:

…there is a tension between stories and statistics, and one under-appreciated contrast between them is simply the mindset with which we approach them. In listening to stories we tend to suspend disbelief in order to be entertained, whereas in evaluating statistics we generally have an opposite inclination to suspend belief in order not to be beguiled. A drily named distinction from formal statistics is relevant: we’re said to commit a Type I error when we observe something that is not really there and a Type II error when we fail to observe something that is there. There is no way to always avoid both types, and we have different error thresholds in different endeavors, but the type of error people feel more comfortable may be telling…

I’ll close with perhaps the most fundamental tension between stories and statistics. The focus of stories is on individual people rather than averages, on motives rather than movements, on point of view rather than the view from nowhere, context rather than raw data. Moreover, stories are open-ended and metaphorical rather than determinate and literal.

It seems to me that for science, the correct emphasis should be on the statistics. That is, we should be more worried about observing something that is not really there. But as humans, statistics is often too dry and too abstract for us to understand intuitively, to generate that comfortable internal feeling of understanding. Thus, our peers often demand that we give not only the statistical explanation but also a narrative one. Sometimes, this can be tricky because the structure of the two modes of explanation are in fundamental opposition, for instance, if the narrative must include notions of randomness or stochasticity. In such a case, there is no reason for any particular outcome, only reasons for ensembles or patterns of outcomes. The idea that things can happen for no reason is highly counter intuitive3, and yet in the statistical sciences (which is today essentially all sciences), this is often a critical part of the correct explanation4. For the social sciences, I think this is an especially difficult balance to strike because our intuition about how the world works is built up from our own individual-level experiences, while many of the phenomena we care about are patterns above that level, at the group or population levels5.

This is not a new observation and it is not a tension exclusive to the social sciences. For instance, here is Stephen J. Gould (1941-2002), the eminent American paleontologist, speaking about the differences between microevolution and macroevolution (excerpted from Ken McNamara’s “Evolutionary Trends”):

In Flatland, E.A. Abbot’s (1884) classic science-fiction fable about realms of perception, a sphere from the world of three dimensions enters the plane of two-dimensional Flatland (where it is perceived as an expanding circle). In a notable scene, he lifts a Flatlander out of his own world and into the third dimension. Imagine the conceptual reorientation demanded by such an utterly new and higher-order view. I do not suggest that the move from organism to species could be nearly so radical, or so enlightening, but I do fear that we have missed much by over reliance on familiar surroundings.

An instructive analogy might be made, in conclusion, to our successful descent into the world of genes, with resulting insight about the importance of neutralism in evolutionary change. We are organisms and tend to see the world of selection and adaptation as expressed in the good design of wings, legs, and brains. But randomness may predominate in the world of genes—and we might interpret the universe very differently if our primary vantage point resided at this lower level. We might then see a world of largely independent items, drifting in and out by the luck of the draw—but with little islands dotted about here and there, where selection reins in tempo and embryology ties things together. What, then, is the different order of a world still larger than ourselves? If we missed the world of genic neutrality because we are too big, then what are we not seeing because we are too small? We are like genes in some larger world of change among species in the vastness of geological time. What are we missing in trying to read this world by the inappropriate scale of our small bodies and minuscule lifetimes?

To quote Howard T. Odum (1924-2002), the eminent American ecologist, on a similar theme: “To see these patterns which are bigger than ourselves, let us take a special view through the macroscope.” Statistical explanations, and the weird and diffuse notions of causality that come with them, seem especially well suited to express in a comprehensible form what we see through this “macroscope” (and often what we see through microscopes). And increasingly, our understanding of many important phenomena, be they social network dynamics, terrorism and war, sustainability, macroeconomics, ecosystems, the world of microbes and viruses or cures for complex diseases like cancer, depend on us seeing clearly through some kind of macroscope to understand the statistical behavior of a population of potentially interacting elements.

Seeing clearly, however, depends on finding new and better ways to build our intuition about the general principles that take inherent randomness or contingency at the individual level and produce complex patterns and regularities at the macroscopic or population level. That is, to help us understand the many counter-intuitive statistical mechanisms that shape our complex world, we need better ways of connecting statistics with stories.

1 Actually, even defining what we mean by “explain” is a devilishly tricky problem. Invariably, different fields of scientific research have (slightly) different definitions of what “explain” means. In some cases, a statistical explanation is sufficient, in others it must be deterministic, while in still others, even if it is derived using statistical tools, it must be rephrased in a narrative format in order to provide “intuition”. I’m particularly intrigued by the difference between the way people in machine learning define a good model and the way people in the natural sciences define it. The difference appears, to my eye, to be different emphases on the importance of intuitiveness or “interpretability”; it’s currently deemphasized in machine learning while the opposite is true in the natural sciences. Fortunately, a growing number of machine learners are interested in building interpretable models, and I expect great things for science to come out of this trend. In some areas of quantitative science, “story telling” is a grave insult, leveled whenever a scientist veers too far from statistical modes of explanation (“science”) toward narrative modes (“”https://en.wikipedia.org/wiki/Just_So_Stories">just so stories"). While sometimes a justified complaint, I think completely deemphasizing narratives can undermine scientific progress. Human intuition is currently our only way to generate truly novel ideas, hypotheses, models and principles. Until we can teach machines to generate truly novel scientific hypotheses from leaps of intuition, narratives, supported by appropriate quantitative evidence, will remain a crucial part of science.

2 Another fascinating aspect of the interaction between these two modes of explanation is that one seems to be increasingly invading the other: narratives, at least in the media and other kinds of popular discourse, increasing ape the strong explanatory language of science. For instance, I wonder when Time Magazine started using formulaic titles for its issues like “How X happens and why it matters” and “How X affects Y”, which dominate its covers today. There are a few individual writers who are amazingly good at this form of narrative, with Malcolm Gladwell being the one that leaps most readily to my mind. His writing is fundamentally in a narrative style, stories about individuals or groups or specific examples, but the language he uses is largely scientific, speaking in terms of general principles and notions of causality. I can also think of scientists who import narrative discourse into their scientific writing to great effect. Doing so well can make scientific writing less boring and less opaque, but if it becomes more important than the science itself, it can lead to “”https://en.wikipedia.org/wiki/Pathological_science">pathological science".

3 Which is perhaps why the common belief that “everything happens for a reason” persists so strongly in popular culture.

4 It cannot, of course, be the entire explanation. For instance, the notion among Creationists that natural selection is equivalent to “randomness” is completely false; randomness is a crucial component of way natural selection constructs complex structures (without the randomness, natural selection could not work) but the selection itself (what lives versus what dies) is highly non-random and that is what makes it such a powerful process.

What makes statistical explanations interesting is that many of the details are irrelevant, i.e., generated by randomness, but the general structure, the broad brush-strokes of the phenomena are crucially highly non-random. The chief difficulty of this mode of investigation is in correctly separating these two parts of some phenomena, and many arguments in the scientific literature can be understood as a disagreement about the particular separation being proposed. Some arguments, however, are more fundamental, being about the very notion that some phenomena are partly random rather than completely deterministic.

5 Another source of tension on this question comes from our ambiguous understanding of the relationship between our perception and experience of free will and the observation of strong statistical regularities among groups or populations of individuals. This too is a very old question. It tormented Rev. Thomas Malthus (1766-1834), the great English demographer, in his efforts to understand how demographic statistics like birth rates could be so regular despite the highly contingent nature of any particular individual’s life. Malthus’s struggles later inspired Ludwig Boltzmann (1844-1906), the famous Austrian physicist, to use a statistical approach to model the behavior of gas particles in a box. (Boltzmann had previously been using a deterministic approach to model every particle individually, but found it too complicated.) This contributed to the birth of statistical physics, one of the three major branches of modern physics and arguably the branch most relevant to understanding the statistical behavior of populations of humans or genes.

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