Andrew Zolli

This blog is returning from hiatus, with a new, occasional series on thinking about complex problems.

At a recent convening of leaders in public health, Dr. David Fleming, of PATH, shared what has become a common observation regarding the relationship between spending and outcomes on US healthcare: namely, that the US spends far more than any other nation (both per-capita and in total dollars) on the health of our citizens, yet achieves results (measured in terms of life expectancy) which place us last on the list of developed nations:

This fact has featured prominently in debates over the design of the US healthcare system, fueling arguments on all sides. Yet a much more interesting picture emerges, Dr. Fleming showed, when you look at life expectancy by county, rather than nationally:

Here we see how US counties perform when compared to the world’s ten-best performing countries in terms of life expectancy. The darkest blue counties are up to 15 years ahead of the world’s best performing countries; the darkest red counties are up to fifty years behind.

What becomes immediately clear from even a casual glance is how place-based US health performance is. America’s least-well-performing communities are clustered in the American Deep South — there are counties in rural Alabama, for example, where life expectancy substantially lags that of say, Vietnam or Bangladesh. Conversely, there are certain Northeastern and California communities that are so far ahead it may take even the most advanced economies another decade just to catch up to them.

The absence of these distinctions in our everyday debates over healthcare illustrates what statisticians call the tyranny of the average, a term used describe the consequences of using averages as indicators of the performance of complex systems.

Average indicators mask the “lumpy” reality of many complex phenomena, and generally, dumb down our thinking and our debates. They suppress our understanding of both the negative and positive outliers in a given domain. Aggregate educational statistics about a city, for example, can “hide” a failing school, just as readily as they can “hide” school that is outperforming. They are an enemy of accountability and a disincentive to action.

Averages also shape our view of what constitute “normal” phenomena in the popular imagination, and they reinforce our assumptions about what “normal” responses to those phenomena should be. The real world, of course, is much more diverse. Psychologists, for example, are learning that there is a far wider array of healthy responses to adverse life events than our default cultural categories suggest. As PACE University’s Anthony Mancini writes:

 “Reliance on average responses has led to the cultural assumption that most people experience considerable distress following loss and traumatic events, and that everyone can benefit from professional intervention. After 9/11, for example, counselors and therapists descended on New York City to provide early interventions, particularly to emergency service workers, assuming that they were at high risk of developing posttraumatic stress disorder. In fact, most people—even those who experience high levels of exposure to acute stress—recover without professional help.

And we now know that many early interventions are actually harmful and can impede natural processes of recovery. For example, critical incident stress debriefing, a once widely used technique immediately following a traumatic event, actually resulted in increased distress three years later among survivors of motor vehicle accidents who received this treatment, compared to survivors who received no treatment.”

The Tyranny of the Average is given perfect mathematical expression in Anscombe’s quartet, four datasets that appear nearly identical when described with simple statistics, but reveal a completely different picture when graphed. All of these datasets have exactly the same average, variance and correlation – yet the underlying behavior of the system they represent is completely hidden until you look at the data spatially:

Each of these variations describes a different reality, and each of those realities require a different range of strategies if we wanted to drive intentional (and presumably beneficial) change. There are many strategies which might improve one variation, but actually harm the others.

For many complex social phenomena, such “lumpy” distributions are often fractal – repeating at every resolution. Just as some counties dramatically over- or under-perform their peers in healthcare, so too one community within a county may do so, and one neighborhood within that community, and one block within that neighborhood.

You can see this in evidence in the State of Mississippi, which ranks 50^th in the country in terms of infant mortality, with 9.08 infant deaths per 1000 live births. (This is called the “IMR” or “Infant Mortality Rate.) Drill down on this “averaged” statewide indicator and, as you might expect, you’ll find wild disparities at the county level, with some counties doing dramatically worse (or better) than their peers:

Immediately, you may think this is a good proxy map of where the maternal health system is strongest and where it is weakest. Yet even this map hides something significant, and distorting – the shocking disparity between the IMR for black and white mothers. Here’s the relevant comparison data for the twenty most populous counties in Mississippi:

As you can see, in every single county on the list, the IMR for black mothers is higher than it is for white mothers. In Alcorn county, for example, the IMR for black mothers is 30.8 deaths per 1000 births – 275% higher than it is for white mothers who live in the same county. (The IMR in North Korea, in contrast, is ‘only’ 22.) In Pearl River County, the IMR for black mothers is 24.9, an incredible 344% higher than the IMR for white mothers of 5.6. Yet, on the above map, Pearl River only merits a severity ranking of 2 (on a scale of 1-5) because the aggregate statistic effectively “hides” this unequal racial outcome.

Two observations stand out here: first, for those seeking to encourage positive social and ecological change, having higher-resolution statistics is not only tactically essential, it’s politically and even morally essential. Without them, you can’t see the texture of the problem you’re confronting – and you can’t build the interest groups, stakeholders, accountability frameworks or political case necessary to measure and drive change.

The second is that many of our 21^st-century problems may ultimately be better understood in terms of place, rather than in terms of problem-set. Poverty, limited social power, environmental degradation, underfunded education, poor health access and other issues often cluster spatially – and mutually reinforce one another. But sometimes, they don’t. Understanding the difference is essential if we’re to avoid one-size-fits-all solutions.

To do that, we need a revolution in data collection and reporting – including the production of new kinds of indicators that not only tell us the health of the overall system, but can decompose that larger picture into its constituent parts – and reveal the nuanced ‘texture’ of a place in both space and time.

“The world is full of magic things, patiently waiting for our senses to grow sharper.”
―W.B. Yeats

Human perception is a fickle, paradoxical instrument.

Our visual sense, while more acute than that of many species, is hardly the keenest in the animal kingdom. An eagle, for instance, has eyesight so sharp it can spot small prey more than three kilometers away. The next time you happen upon one in the wild, know that it saw you coming from afar, and waited patiently for you to arrive.

Birds are also “tetrachromats”; in addition to the spectra that are visible to humans, they possess a fourth kind of cone in their retinas, which allows them to see ultraviolet wavelengths of light. A very few human beings have inherited a genetic variant that confers tetrachromacy; they describe living in a world of spectacular subtlety and vibrancy, wholly unavailable to the rest of us, in which hundreds of unseen variations lurk in what we might otherwise label “green” or “blue.”

Other animals, especially small ones, sense time in ways that we might consider super-human. A common housefly processes about four times more visual information each second than a human being. Their “mental movie” is composed of two hundred and fifty frames per second; ours, a paltry sixty. As a consequence, some zoologists believe that a fly’s experience of time is radically slowed. To them, we appear as lumbering beasts, haplessly waving our rolled-up newspapers in slow motion.

One could fill a book with such unflattering comparisons, but don’t pity the poor humans. Over thousands of years of self-compounding refinement, we have managed to augment our otherwise provincial senses far beyond what any other animal might hope for. Indeed, this increasing sensual acuity is a central theme in the story of human progress.

Consider: In the 5th century BCE, the Greek philosopher Democritus first developed the (at the time, unobvious) idea that the world was filled with small, indivisible particles—άτομα. His contemporary, Aristotle, thought this idea was ludicrous, and the idea languished for centuries.  Today, along the border between France and Switzerland, physicists at the Large Hadron Collider regularly accelerate subatomic particles to 99.999999% of the speed of light, and then smash them together in violent explosions that simulate the earliest moments after the Big Bang. In the resulting flash, which lasts for only a few billionths of a second, they glimpse the esoteric particles that form the basic building blocks of the universe. To even attempt this feat required the invention of detectors that are so exquisitely sensitive that they must be continually readjusted to compensate for minute fluctuations in the gravitational pull of the moon.

In a similar vein, we have peered further out into the inky darkness—and thus, further back in time—than any other animal. The universe is 13.7 billion years old. Human beings have built an instrument—the Planck Space Telescope—that has detected the dim remnants of radiation emitted when the cosmos was a mere 380 thousand years old—or 0.00002 billion years after its birth. Said another way: if the entire history of the cosmos were compressed into a year, we human beings have peered all the way back to the first ten minutes.

These Olympic feats of enhanced perception are among the crowning achievements of our species. Yet even as we celebrate them, our workaday senses remains stubbornly parochial.

Walking down the street, we easily sense changes that occur at a one or two meters per second, especially if those changes occur where our experience tells us they ought to. But, we’re terrible at sensing changes that unfold significantly faster—or slower—than our preferred speed, or occur where our experiences haven’t conditioned us to look.

This parochialism is part of the reason why we so poorly understand the world around us. Our planet is vastly larger and more complex than our ability to readily comprehend, and moves at speeds, and scales, and with interdependencies that do not conform to our everyday modes of thinking. If it did, climate change would have been solved long ago.

Paradoxically, humanity’s civilizing instinct inflames these perceptual biases. Civilization can be understood, in part, as the imposition of a kind of human-scale regularity upon the world. From inside it, it’s easy to forget that we nest, unsteadily, within the larger complexity of the whole—and not the other way around.

Now, thankfully, humanity is developing new technologies that can help us sense the world at scale, and make change visible in ways that are much more amenable to human cognition. And that matters, because seeing the world, deeply and in its totality, is the first step on the path to communion, empathy, and stewardship.

Mangroves spread in fractal patterns along the remote Keep River in Australia.
Image courtesy of Planet Labs.

For the past several years, I’ve been lucky enough to work with Earth-imaging specialists, planetary scientists, engineers and others who regularly peer at the world through a suite of these new instruments.

Uncontrolled peat fires in Indonesia, exacerbated by a strong El Nino.
Image courtesy of Planet Labs.

Some of these colleagues, at a company called Planet Labs, are deploying the largest constellation of Earth-observing satellites in human history. When fully operational, this system will collectively image the entire surface of the Earth, in high resolution, every day.

Luuq, Somalia rests in a large oxbow in the Jubba River, and is currently a haven for hundreds of Somalia’s “internally displaced persons.”
Image courtesy of Planet Labs.

Through the Planet Labs satellites (called Doves) and other Earth-imaging tools, on any given day, one can witness the world of the Anthropocene—the Age of Humans—in all its complexity. Agricultural fires signal the onset of the planting season in Brazil. Refugee camps expand along the Turkish border with Syria. Ice-flows dissolve off the coast of Nova Scotia. The Amazonian rainforest is slowly, and illegally denuded. Monolithic manufacturing complexes spread out in China. Megacities in Africa push ever outward. Crater-like remnants of nuclear bomb tests scar the Nevada desert. The density of nighttime illumination hints at the relative poverty, and equity, of human societies.

Nevada’s “Plutonium Valley”, where nuclear explosions, were tested in the 1950s, will remain radioactive for 400 generations.
Image courtesy of Planet Labs.

Not all of this sensing is done with satellites. At the University of Washington, computer scientist Ricardo Martin Brualla and his colleagues have developed software tools that harvest countless digital snapshots that we post on the Internet and synthesize them into films that show the aggregate change in one place over time.

 (Above: The retreat of the Briksdalsbreen glacier in Norway, and the rise of the Las Vegas skyline, recomposed from hundreds of Internet photos, by Ricardo Martin Brualla and colleagues. Used by permission.)

For the first time in our history, broad access to these kinds of tools and imagery make visible, for anyone, the hidden dynamism of the planet—a dynamism that we spy occasionally, and only liminally, in our everyday life.

These images reveal not only change, but also vast diversity. Look upon the Earth long enough, and you will find almost every adjective fulfilled, somewhere. The world is beautiful, of course. But it is also sometimes ugly. It is intensely intertwined with human affairs, although it is sometimes indifferent or even overtly hostile to them. In some places, we are instruments of the world’s ruin; in others, less frequently, its regeneration.

In 1901, the writer and Nobel laureate Maurice Maeterlinck published “The Life of the Bee”, which popularized the idea that humanity owes our continued survival to the dutiful pollinator. “It is … estimated that more than a hundred thousand varieties of plants would disappear if the bees did not visit them,” Maeterlinck noted, “and possibly even our civilization, for in these mysteries all things intertwine.”

Today, we are getting perilously close to testing Maeterlinck’s hypothesis empirically. Bee colonies, which are responsible for billions of dollars of agriculture, food security, and ecosystem services, are collapsing around the world. It would not take the death of the last hive for life to become grim for at least some of the people, plants and animals who depend on bees, either directly or indirectly.

But precisely how many bee colonies have to collapse before the larger system fails? Are we near the tipping point? Here, we are on much murkier ground.

The same dynamic holds true in our understanding of countless other marquee challenges of our present age, from ocean warming and climate change, to the genetic basis of cancer, the performance of electrical grids, digital networks, and even the stock market. While all of these complex systems have compensatory elements, there is a point when the accumulation of damage becomes unrecoverable, and catastrophic collapse follows. But when?

Last month, network theorists Jianxi Gao, Baruch Barzel and Albert-László Barabási published an important paper in Nature, “Universal resilience patterns in complex networks,” which takes us a significant step closer to determining these pernicious tipping points. The authors present a universal mathematical framework which allows one to compute a straightforward “resilience function” (or perhaps more aptly, a “collapse threshold”) for any complex system – its point of no return.

Until now, the only way to identify such thresholds was to painstakingly map the interactions of all of the individual elements in the system – a task that was impractical or impossible in most circumstances. (Even our most sophisticated models of the climate, run on supercomputers, model only a fraction of the forces acting upon it.) Gao, Barzel and Barabási have taken much of that complexity out, collapsing it into a single indicator of system health. As such, if borne out, this work will certainly find its way into applied resilience domains – especially disaster risk reduction, climate adaptation and finance.

The above video, which acts as a companion to the paper, does a terrific job of explaining the work (and key concepts of ecological resilience in general).

Continuing the recent theme of bringing emotional richness to social media, FastCo.Exist has details of Introjis, emoticons designed for introverts by designer Rebecca Evie Lynch.

Introjis allow introverted users to express a natural and healthy affinity for solitude or quietude, and wordlessly express the occasional distress or fatigue that comes from being in the crowd too long. They’re an evocative counterpoint to more traditional emojis, which express a different range of emotional temperatures.

The “No to the invitation, but thank you!” Introji

The “I want to leave the party” Introji

The “Let’s sit quietly and do our own thing” Introji