Nevertheless, biological imagery is routinely used when writing about cities as well as companies. Typical phrases include “the DNA of the company,” “the metabolism of the city,” “the ecology of the marketplace,” and so on.
But if cities are indeed some sort of superorganism, then why do almost none of them ever die? There are, of course, classic examples of
Consequently, the amount of energy needed to support an average person living in the United States has risen to an astounding 11,000 watts. This social metabolic rate is equivalent to the entire needs of about a dozen elephants.
This may seem self-evident, but it is surprising how small a role, if any, the generalized concept of energy plays in the conceptual thinking of economists and social scientists.
There is always a price to pay when energy is processed; there is no free lunch. Because energy underlies the transformation and operation of literally everything, no system operates without consequences. Indeed, there is a fundamental law of nature that cannot be transgressed, called the Second Law of Thermodynamics, which says that whenever energy is transformed into a useful form, it also produces “useless” energy as a degraded by-product: “unintended consequences” in the form of inaccessible disorganized heat or unusable products are inevitable.
There are no perpetual motion machines. You need to eat to stay alive and maintain and service the highly organized functionality of your mind and body. But after you’ve eaten, sooner or later you will have to go to the bathroom. This is the physical manifestation of your personal entropy production.
This fundamental, universal property resulting from how all things interact by interchanging energy and resources was called entropy by the German physicist Rudolf Clausius in 1855. Whenever energy is used or processed in order to make or maintain order within a closed system, some degree of disorder is inevitable—entropy always increases.
To maintain order and structure in an evolving system requires the continual supply and use of energy whose by-product is disorder. That’s why to stay alive we need to continually eat so as to combat the inevitable, destructive forces of entropy production. Entropy kills.
Scaling simply refers, in its most elemental form, to how a system responds when its size changes.
Scaling arguments have led to a deep understanding of the dynamics of tipping points and phase transitions (how, for example, liquids freeze into solids or vaporize into gases), chaotic phenomena (the “butterfly effect” in which the mythical flapping of a butterfly’s wings in Brazil leads to a hurricane in Florida), the discovery of quarks (the building blocks of matter), the unification of the fundamental forces of nature, and the evolution of the universe after the Big Bang.
A greatly underappreciated case in point is the hidden role that scaling plays in medicine. Much of the research and development on diseases, new drugs, and therapeutic procedures is undertaken using mice as “model” systems. This immediately raises the critical question of how to scale up the findings and experiments on mice to humans.
This is a simple example of classic linear thinking. Surprisingly, it is not always easy to recognize linear thinking, despite its apparent simplicity, because it often tends to be implicit rather than explicit.
GDP, like almost any other quantifiable characteristic of a city, or indeed of almost any complex system, typically scales nonlinearly.
This systematic “value-added” bonus as size increases is called increasing returns to scale by economists and social scientists, whereas physicists prefer the more sexy term superlinear scaling.
A profound consequence of this rule is that on a per gram basis, the larger animal (the woman in this example) is actually more efficient than the smaller one (her dog) because less energy is required to support each gram of her tissue (by about 25 percent). Her horse, by the way, would be even more efficient. This systematic savings with increasing size is known as an economy of scale.
Over the past quarter of a century, terms like complex adaptive systems, the science of complexity, emergent behavior, self-organization, resilience, and adaptive nonlinear dynamics have begun to pervade not just the scientific literature but also that of the business and corporate world as well as the popular media.
Momentum, energy, and temperature are classic examples of quantities that are precisely defined in physics but are used colloquially or metaphorically in everyday language. Having said that, however, there are a sizable number of really big concepts whose precise definitions still engender significant debate. These include life, innovation, consciousness, love, sustainability, cities, and, indeed, complexity.
A typical complex system is composed of myriad individual constituents or agents that once aggregated take on collective characteristics that are usually not manifested in, nor could easily be predicted from, the properties of the individual components themselves.
In a similar fashion, a city is much more than the sum of its buildings, roads, and people, a company much more than the sum of its employees and products, and an ecosystem much more than the plants and animals that inhabit it.
In general, then, a universal characteristic of a complex system is that the whole is greater than, and often significantly different from, the simple linear sum of its parts.
This collective outcome, in which a system manifests significantly different characteristics from those resulting from simply adding up all of the contributions of its individual constituent parts, is called an emergent behavior.
The important lesson that we learn from these investigations is that in many such systems there is no central control.
The study of complex systems has taught us to be wary of naively breaking the system down into independently acting component parts. Furthermore, a small perturbation in one part of the system may have giant consequences elsewhere. The system can be prone to sudden and seemingly unpredictable changes—a market crash being a classic example. One or more trends can reinforce other trends in a positive feedback loop until things swiftly spiral out of control and cross a tipping point beyond which behavior radically changes.
The scaling law, however, is nonlinear and says that metabolic rates don’t double but, in fact, increase by only about 75 percent, representing a whopping 25 percent savings with every doubling of size.
They are all “power laws” and are typically governed by an exponent (the slope of the graph), which is a simple multiple of 1⁄4, the classic example being the 3⁄4 for metabolic rate. So, for example, if the size of a mammal is doubled, its heart rate decreases by about 25 percent. The number 4 therefore plays a fundamental and almost magically universal role in all of life.13
The growth theory also explains a curious paradoxical phenomenon that you might have pondered, namely, why we eventually stop growing even though we continue to eat. This turns out to be a consequence of the sublinear scaling of metabolic rate and the economies of scale embodied in the network design.
The scaling exponent for companies is around 0.9, to be compared with 0.85 for the infrastructure of cities and 0.75 for organisms. However, there is considerably more variation around precise scaling among companies than for organisms or cities. This is especially so in their early stages of development as they jostle for a place in the market.
Similarly, for large animals, the need to dissipate heat generated by their metabolism and physical activity can become problematic because the surface area through which it is dissipated is proportionately much smaller relative to their volume than for smaller ones. Elephants, for example, have solved this challenge by evolving disproportionately large ears to significantly increase their surface area so as to dissipate more heat.
Or, as Galileo so graphically put it: “the smaller the body the greater its relative strength. Thus a small dog could probably carry on his back two or three dogs of his own size; but I believe that a horse could not carry even one of his own size.”
Ants appear to be, at least superficially, much stronger than human beings. However, as we have learned from Galileo, relative strength systematically increases as size decreases.
The reason for this vast difference in impact despite an apparently small increase in magnitude is that the Richter scale expresses size in terms of orders of magnitude.
This kind of scale where instead of increasing linearly as in 1, 2, 3, 4, 5 . . . we increase by factors of 10 as in the Richter scale: 101, 102, 103, 104, 105 . . . is called logarithmic.
the logarithmic technique is ubiquitously used across all areas of science. The brightness of stars, the acidity of chemical solutions (their pH), physiological characteristics of animals, and the GDPs of countries are all examples where this technique is commonly utilized to cover the entire spectrum of the variation of the quantity being investigated.
An essential component of science that often distinguishes it from other intellectual pursuits is its insistence that hypothesized claims be verified by experiment and observation. This is highly nontrivial, as evidenced by the fact that it took more than two thousand years before Aristotle’s pronouncement that objects falling under gravity do so at a rate proportional to their weight to actually be tested—and when carried out, to be found wanting.
Sadly, many of our present-day dogmas and beliefs, especially in the nonscientific realm, remain untested yet rigidly adhered to without any serious attempt to verify them—sometimes with unfortunate or even devastating consequences.
A major challenge of the medical and health industry is to ascertain the quantifiable baseline scale of life, and consequently the extended suite of metrics for the average, healthy human being, including how large a variation or deviation from them can be tolerated.
Although trained as a mathematician, Quetelet was a classic polymath who contributed to a wide range of scientific disciplines including meteorology, astronomy, mathematics, statistics, demography, sociology, and criminology.
At a detailed, high-resolution level, we may have great freedom in determining events into the near future, but at a coarse-grained, bigger-picture level where we deal with very long timescales life may be more deterministic than we think.
So who was Isambard Kingdom Brunel, and why is he famous? Many consider him the greatest engineer of the nineteenth century, a man whose vision and innovations, particularly concerning transport, helped make Britain the most powerful and richest nation in the world. He was a true engineering polymath who strongly resisted the trend toward specialization.
She made a small number of transatlantic crossings before being ignominiously transformed into a ship for laying cables. The first resilient transatlantic telegraph cable was laid by the Great Eastern in 1866, enabling reliable telecommunication between Europe and North America, thereby revolutionizing global communication.
And of even greater significance, the laws of thermodynamics and the concepts of energy and entropy extend far beyond the narrow confines of steam engines and are universally applicable to any system where energy is being exchanged, whether for a ship, an airplane, a city, an economy, your body, or the entire universe itself.
Thus, by making the length and speed of the model ship have the same Froude number as that of the full-size version, one can determine the dynamical behavior of the full-size ship before building it.
One of the curious unintended consequences of these advances is that almost all automobiles, for example, now look alike because all manufacturers are solving the same equations to optimize similar performance parameters.
Perhaps the most famous dimensionless number is pi (π), the ratio of the circumference of a circle to its diameter. This has no units, because it is the ratio of two lengths, and has the same value for all circles everywhere, at all times, no matter how small or how large they are. π therefore embodies the universal quality of “circleness.”
We must all die so that the new can blossom, explore, adapt, and evolve. Steve Jobs put it succinctly3: No one wants to die. Even people who want to go to heaven don’t want to die to get there. And yet death is the destination we all share. No one has ever escaped it, and that is how it should be, because death is very likely the single best invention of life. It’s life’s change agent. It clears out the old to make way for the new.
Thompson was one of the last “Renaissance men” and is representative of a breed of multi-and transdisciplinary scientist-scholars that barely exists today. Although his primary influence was in biology, he was a highly accomplished classicist and mathematician.
Metabolic rate is the fundamental rate of biology, setting the pace of life for almost everything an organism does, from the biochemical reactions within its cells to the time it takes to reach maturity, and from the rate of uptake of carbon dioxide in a forest to the rate at which its litter breaks down.
This remarkably systematic repetitive behavior is called scale invariance or self-similarity and is a property inherent to power laws. It is closely related to the concept of a fractal, which will be discussed in detail in the following chapter. To varying degrees, fractality, scale invariance, and self-similarity are ubiquitous across nature from galaxies and clouds to your cells, your brain, the Internet, companies, and cities.
Whales live in the ocean, elephants have trunks, giraffes have long necks, we walk on two legs, and dormice scurry around, yet despite these obvious differences, we are all, to a large degree, nonlinearly scaled versions of one another.
If you tell me the size of a mammal, I can use the scaling laws to tell you almost everything about the average values of its measurable characteristics: how much food it needs to eat each day, what its heart rate is, how long it will take to mature, the length and radius of its aorta, its life span, how many offspring it will have, and so on. Given the extraordinary complexity and diversity of life, this is pretty amazing.
iso is Greek for “the same,” and metric is derived from metrikos, meaning “measure.”
Julian Huxley, himself a very distinguished biologist, was the grandson of the famous Thomas Huxley, the biologist who championed Charles Darwin and the theory of evolution by natural selection, and the brother of the novelist and futurist Aldous Huxley.
Jim and Brian patiently acted as my biology tutors, exposing me to the conceptual world of natural selection, evolution and adaptation, fitness, physiology, and anatomy, all of which were embarrassingly foreign to me. Like many physicists, I was horrified to learn that there were serious scientists who put Darwin on a pedestal above Newton and Einstein.
In what follows, I shall be using the terms “coarse-grained” and “zeroth order” interchangeably.
As a fitting tribute to this remarkable man, Andrew Robinson wrote a spirited biography of Young titled The Last Man Who Knew Everything: Thomas Young, the Anonymous Polymath Who Proved Newton Wrong, Explained How We See, Cured the Sick, and Deciphered the Rosetta Stone, Among Other Feats of Genius.
Long before the concept was invented, self-similarity was poetically expressed by the Irish satirist Jonathan Swift, the author of Gulliver’s Travels, in this whimsical quatrain: So, naturalists observe, a flea Hath smaller fleas that on him prey; And these have smaller still to bite ’em; And so proceed ad infinitum.
The take-home message is clear. In general, it is meaningless to quote the value of a measured length without stating the scale of the resolution used to make it. In principle, it is as meaningless as saying that a length is 543, 27, or 1.289176 without giving the units it’s measured in. Just as we need to know if it is in miles, centimeters, or angstroms, we also need to know the resolution that was used.
As Mandelbrot succinctly put it: “Smooth shapes are very rare in the wild but extremely important in the ivory tower and the factory.”
In other words, the behavior of the stock market is a self-similar fractal pattern that repeats itself across all timescales following a power law that can be quantified by its exponent or, equivalently, its fractal dimension.
In marked contrast to this, almost none of our man-made engineered artifacts and systems, whether automobiles, houses, washing machines, or television sets, invoke the power of fractals to optimize performance. To a very limited extent, electronic equipment such as computers and smart phones does, but compared with how you work they are extraordinarily primitive. On the other hand, human-engineered systems that have grown organically such as cities, and to a limited extent corporations, have unconsciously evolved self-similar fractal structures which have tended to optimize their performance.
The onto part of this word is derived from the Greek word for “being,” while genesis means “origins,” so ontogenesis, or ontogeny, connotes the idea of the study of how we came to be.
According to the ancient Romans, the Hour of the Wolf means the time between night and dawn, just before the light comes, and people believed it to be the time when demons had a heightened power and vitality, the hour when most people died and most children were born, and when nightmares came to one.
I think this was my first truly serious inkling that there was more to life than money, sex, and football and began my long-term interest in questions of metaphysics and philosophical thought. I began to voraciously read all of the usual suspects from Socrates, Aristotle, and Job to Spinoza, Kafka, and Sartre, and from Russell and Whitehead to Wittgenstein, A. J. Ayer, and even Colin Wilson, though barely understanding anything of what any of them were saying (especially Wittgenstein, by the way).
Very few people have even approached this age. The oldest verified person ever was the Frenchwoman Jeanne Calment, who died in 1997 at the remarkable age of 122 years and 164 days.
When asked, she ascribed her longevity to a diet rich in olive oil, which she also rubbed into her skin, port wine, and the nearly one kilogram (2 lbs.) of chocolate she ate every week. Make of this what you will. By the way, you probably recognize Arles as the place where Vincent van Gogh went in order to develop his distinctive style of painting, living for a time with Paul Gauguin.
Although the detailed role and extent of oxidative damage in aging remains unclear, it has stimulated a mini-industry of antioxidant supplements such as vitamin E, fish oil, and red wine as some of those elixirs of life to combat aging.
As I have stressed earlier, changing just one component of a complex adaptive system without fully understanding its multilevel spatiotemporal dynamics usually leads to unintended consequences.
As I have already remarked, large animals live long lives slowly, whereas small ones live short lives fast, but in such a way that their biomarkers such as the total number of times their hearts beat remain approximately the same.
However, within species an individual like each of us can decrease its cellular metabolic rate simply by eating less, resulting in less metabolic damage per cell and potentially in an increase in its life span. This strategy is called caloric restriction.
I am somewhat biased toward them because I believe in the theory and the concept that lowering metabolism decreases damage, slows the aging process, and increases maximum life span.
Before completing this section, I would be remiss not to mention that Roy Walford, who played a seminal role in aging research, was a man of many talents. Among his many exploits, he gained a certain early notoriety when he and a fellow graduate student used statistical analysis to determine which roulette wheels at a casino in Reno, Nevada, were accidentally biased. By betting heavily on the ones that were most unbalanced, they cleaned up. The casinos eventually realized what was happening and banned them from betting. From his winnings Walford funded his medical school education as well as a year of sailing a yacht in the Caribbean.
Stewart Brand, who passionately felt that the image of the whole Earth from space would be a powerful symbol, evoking a sense of shared destiny among all people living on the planet. He relentlessly lobbied NASA to release the first images in 1967, which he then used on the cover of his highly influential Whole Earth Catalog, one of the great icons of the 1960s and ’70s.
Globally we use an enormous amount of energy, somewhere in the range of about 150 trillion kilowatt-hours a year. This is one of those astronomical numbers like the annual budget of the United States, whose magnitude and meaning are extremely difficult for most of us mere mortals to comprehend, making our eyes glaze over when we hear it.
I pointed out in the opening chapter that the 2,000 food calories a day you need to stay alive is equivalent to almost 100 watts, the power of a lightbulb. You are extraordinarily efficient in your use of energy relative to anything that is man-made. Your dishwasher, for example, requires more than ten times more energy per second than you do just to wash dishes, while your car uses it at a rate in excess of a thousand times more just to move you around.
Remarkably, concepts like energy and entropy, metabolism, and carrying capacity have not found their way into mainstream economics.
Even when integrated over the entire lifetime of all nuclear power plants this is less than one hundred people, and most of them died in the Chernobyl disaster in the USSR in 1986, while none died at Fukushima. On the other hand, many thousands may have contracted cancer and died, or will die prematurely, because of radiation exposure from such accidents, particularly from Chernobyl. But this should be “balanced” by the estimated 50 million people who are injured, maimed, or disabled each year by car accidents.
Many of us blithely use phrases like the “metabolism of a city,” the “ecology of the marketplace,” the “DNA of a company,” and so on, as if cities and companies were biological. Even as far back as Aristotle we find him continually referring to the city (the polis) as a “natural” organic autonomous entity.
One of its original proponents was the well-known Japanese architect Kenzo Tange, the 1987 winner of the Pritzker Prize, considered to be the Nobel Prize of architecture. I find his designs, however, to be surprisingly inorganic, dominated by right angles and concrete and somewhat soulless, rather than having the curvaceous, softer qualities of an organism.
The concept of a business ecosystem has become a standard buzzword to connote a sort of Darwinian survival of the fittest in the marketplace. It was introduced in 1993 by James Moore, then at Harvard Law School, in an article he wrote titled “Predators and Prey: A New Ecology of Competition,
(You probably recognize Modena for its marvelous balsamic vinegar, not to mention as the home of Ferrari, Lamborghini, and Maserati. On my first visit there, David introduced me to their traditional balsamic vinegar, a remarkable elixir to be distinguished from the tamer stuff many of us nowadays use on our salads, but which costs a good deal more than some of the most expensive bottles of wine I’ve ever bought.)
In fact, the real essence of a city is its people—they provide its buzz, its soul, and its spirit, those indefinable characteristics we viscerally feel when we are participating in the life of a successful city. This may seem obvious, but the emphasis of those who think about cities, such as planners, architects, economists, politicians, and policy makers, is primarily focused on their physicality rather than on the people who inhabit them and how they interact with one another. It is all too often forgotten
Her writings are more like journalistic narratives, based primarily on anecdotes, personal experience, and a deep intuitive understanding of what cities are, how they work, and how they “should” work.
The pseudoscience of planning seems almost neurotic in its determination to imitate empiric failure and ignore empiric success.
There is no logic that can be superimposed on the city; people make it, and it is to them, not buildings, that we must fit our plans. . . . We can see what people like.
This is reflected in phrases he used such as “cleaning and purging” the city, or developing “a calm and powerful architecture,” and in his insistence that buildings be designed without ornamentation. Thank goodness that his grandiose plans were not acted upon so that we can still enjoy some of the more decadent urban embellishments of central Paris and Stockholm.
I am not attracted to straight angles or to the straight line, hard and inflexible, created by man. I am attracted to free-flowing, sensual curves. The curves that I find in the mountains of my country, in the sinuousness of its rivers, in the waves of the ocean, and on the body of the beloved woman. Curves make up the entire Universe, the curved Universe of Einstein. To which, by the way, he might have added Mandelbrot and fractals. It is ironic that despite this admirable declaration, Brasilia became emblematic of what a city should not be.
No doubt that’s why I ended up being an academic of modest means rather than a wealthy product of the Stanford entrepreneurial IT machine.
A crucial aspect of the scaling of companies is that many of their key metrics scale sublinearly like organisms rather than superlinearly like cities. This suggests that companies are more like organisms than cities and are dominated by a version of economies of scale rather than by increasing returns and innovation.
There are some wonderful examples of these geriatric survivors. For instance, the oldest shoemaker in Germany is the Eduard Meier company, founded in Munich in 1596, which became purveyors to the Bavarian aristocracy.
The world’s oldest company was purported to be Kongo Gumi, founded in Osaka, Japan, in 578. It was also a family business going back many generations, but after almost 1,500 years of continuously being in business it went into liquidation in 2006 and was purchased by the Takamatsu Corporation. And what was the niche market that Kongo Gumi cornered for 1,429 years? Building beautiful Buddhist temples.
Furthermore, it is not at all clear that the “official” organizational charts of companies represents the actuality of what the real operational network structures are. Who is really communicating with whom, how often are they doing it, how much do they exchange, and so on?
This astronomical time is linear and regular. But the actual clock by which we live our socioeconomic lives is an emergent phenomenon determined by the collective forces of social interaction: it is continually and systematically speeding up relative to objective astronomical time. We live our lives on the metaphorical accelerating socioeconomic treadmill.
The great John von Neumann, mathematician, physicist, computer scientist, and polymath, a man whose ideas and accomplishments have had a huge influence on your life, made the following remarkably prescient observation more than seventy years ago: “The ever accelerating progress of technology and changes in the mode of human life . . . gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue.”
Among von Neumann’s many accomplishments before he died at the relatively young age of fifty-three in 1957 are his seminal role in the early development of quantum mechanics, his invention of game theory, which is a major tool in economic modeling, and the conceptual design of modern computers universally referred to as the von Neumann architecture. So
Among the classic grand syntheses in modern science are Newton’s laws, which taught us that heavenly laws are no different from those on Earth; Maxwell’s unification of electricity and magnetism, which brought the ephemeral ether into our lives and gave us electromagnetic waves; Darwin’s theory of natural selection, which reminded us that we’re just animals and plants after all; and the laws of thermodynamics, which suggest that we can’t go on forever.
. . and to many Nobel Prizes.1 Emboldened by its great success, physicists endowed this fantastic vision with the grand title of the Theory of Everything. Demanding mathematical consistency between quantum mechanics and general relativity suggested that the basic building blocks of this universal theory might be microscopic vibrating strings rather than the traditional elementary point particles upon which Newton and all subsequent theoretical developments were based.
The “something” includes many of the concepts and ideas implicit in a lot of the problems and questions considered in this book: concepts like information, emergence, accidents, historical contingency, adaptation, and selection, all characteristics of complex adaptive systems whether organisms, societies, ecosystems, or economies.
Perhaps, then, the most surprising consequence of a visionary Theory of Everything is that it implies that on the grand scale the universe, including its origins and evolution, though extremely complicated, is not complex but in fact is surprisingly simple because it can be encoded in a limited number of equations, conceivably even just a single master equation.
The institute was intended to be truly multidisciplinary—it has no departments, only researchers. . . . Santa Fe and complexity theory have become almost synonymous . . . the institute, now situated on a hill on the town’s outskirts, must be one of the most fun places to be a scientist. The researchers’ offices, and the communal areas they spill into for lunch and impromptu seminars, have picture windows looking out across the mountains and desert. Hiking trails lead out of the car park. In the institute’s kitchen, you can eavesdrop on a conversation between a paleontologist, an expert on quantum computing, and a physicist who works on financial markets. A cat and a dog amble down the corridors and in and out of offices. The atmosphere is like a cross between the senior common room of a Cambridge college and one of the West Coast temples of geekdom, such as Google or Pixar.
think that Whitfield really got this singular combination of characteristics right: on the one hand, the ivory tower image of an Oxford or Cambridge college, a community of scholars devoted to the pursuit of knowledge and understanding for “its own sake” by following their proverbial noses wherever it might take them; on the other, the cutting-edge image of Silicon Valley grappling with problems of the “real” world, seeking innovative solutions and new ways of tackling the complexities of life.
There is almost no hierarchy, and its size is sufficiently small that everyone on-site can easily get to know everyone else; the archaeologist, economist, social scientist, ecologist, and physicist all freely interact on a daily basis to talk, speculate, bullshit, and seriously collaborate on questions big and small.
The institute has been internationally recognized as “the formal birthplace of the interdisciplinary study of complex systems” and has played a central role in recognizing that many of the most challenging, exciting, and profound questions facing science and society lie at the boundaries between traditional disciplines.
Among its founding fathers were two other major figures of twentieth-century academia, both Nobel laureates: Philip Anderson, a condensed matter physicist from Princeton University who had worked on superconductivity and was an inventor, among many other things, of the mechanism of symmetry breaking that underlies the prediction of the Higgs particle; and Kenneth Arrow from Stanford University, whose many contributions to the fundamental underpinnings of economics, from social choice to endogenous growth theory, have been hugely influential.
How times have changed! These days collaborations between physicists and economists are hardly rare occurrences—witness the huge influx onto Wall Street of physicists and mathematicians, many of whom have since become absurdly rich—but just twenty-five years ago it was almost unheard of, especially between two such distinguished thinkers.
Thus in 1947 was born one of the most successful enterprises in all of science, the Medical Research Council Unit (MRCU) within the famed Cavendish Laboratory at Cambridge, whose director was Lawrence Bragg. While under Perutz’s guidance the MRCU produced in just a few short years no fewer than nine Nobel prizes, one of which was the famous discovery of the double-helix structure of DNA by James Watson and Francis Crick.
This is particularly important in medicine. For example, the level of high-density lipoproteins (HDL) in blood—often referred to as “good” cholesterol—is negatively correlated with the incidence of heart attacks, suggesting that taking medications to increase HDL should lower the probability of having a heart attack. However, the evidence supporting this strategy is inconclusive: cardiovascular health does not seem to be improved by artificially raising levels of HDL. This might be because other factors such as genes, diet, and exercise simultaneously affect both HDL levels and the incidence of heart attacks
He identified the first three as (1) empirical observation (pre-Galileo), (2) theory based on models and mathematics (post-Newtonian), and (3) computation and simulation. My impression is that, in contrast to Chris Anderson, Gray viewed this fourth paradigm as an integration of the previous three, namely as a unification of theory, experiment, and simulation, but with an added emphasis on data gathering and analysis.