In an essay entitled “Economic Possibilities for Our Grandchildren” he published in 1930 at the beginning of the Great Depression, the British economist John Maynard Keynes famously predicted that a century of technological progress would bring both abundance and leisure. For the first time, he wrote, we will be faced with a permanent problem – how to occupy the leisure, which science and compound interest will have won for us, “to live wisely and agreeably and well.”
Keynes’s essay has resurfaced recently in the context of growing anxiety over whether automation kills jobs, which Keynes’s predicted it would. Technical improvements in manufacture and transport, he wrote, “have been proceeding at a greater rate in the last ten years than ever before in history.” That could lead to a “new disease,” namely “technological unemployment…due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour.” As the Economist recently observed, readers of Keynes’s essay at the time of publication might not have heard of the problem Keynes suggested—“but they were certain to hear a lot more about it in the years to come.” Technological innovation has historically delivered more long-run employment than it has reduced. Could that be changing in the twenty-first century?
The accelerating advances that Keynes described in his essay are plainly visible today in communications. In the biosciences perhaps the most dramatic example of accelerating advance is the rising productivity and declining cost of DNA sequencing, which has outstripped the doubling of computer chip price-performance every two years under Moore’s law.
Keynes learned economics at King’s College from Alfred Marshall whose foundational Principles of Economics (1890) was the standard textbook for decades. Today, what we understand about biology and the brain is insinuating itself into economics. Fields like molecular biology, brain imaging, and computational modeling are combining to reveal how the brain’s physical structures use neural networks to interact and produce a characteristic response to information from the environment and, indeed, the economy. As a colleague and I recently wrote:
Twentieth-century economics saw many new schools arise ranging from Keynesianism, to econometrics, to utility maximization, to rational expectations / efficient markets, to psychology-based behavioral economics. Now biology is being brought to bear on the mysteries of Adam Smith’s “invisible hand,” John Maynard Keynes’ “animal spirits,” and twenty-first-century innovation. Computers are being put to the task of exploring how the flow of information in the brain influences incentives, reward seeking, greed and fear versus cooperation and altruism in decision making, and what can be understood—and perhaps predicted—about collective human behavior in market economies.
Keynes was not privy to what the biological and social sciences are revealing about incentives—about what impels people to behave the way they do. Our response to economic incentives is being shown to be more complex than neoclassical economics allows. One wonders whether the research would change Keynes’s mind. He considered the ‘money motive’ to be essential for capitalism, with its attendant social customs and economic practices, to function properly. When the time of material abundance and abundant leisure arrives, as Keynes predicted it would, capitalism can be discarded. “Avarice and usury and precaution must be our gods for a little longer still,” he wrote in the concluding remarks of his essay. “For only they can lead us out of the tunnel of economic necessity into the daylight.” Surges of innovation are typically accompanied by labor-market doomsayers, the Economist observed “but technological progress has never previously failed to generate new employment opportunities.” How long, however, are we willing to hang on to our gods if technological change is actually accompanied by major social dislocation from mass unemployment?
Alfred Marshall, 1921.
The computational models that inform us about economic trends and human behavior including Keynes’s own theory of aggregate demand, employment, and economic activity owe a great debt to Alan Turing who entered King’s College as a scholar the year after Keynes published his essay. Turing read mathematics as an undergraduate. He was introduced to the writing of John von Neumann on the logical foundations of quantum mechanics followed by Bertrand Russell and Alfred North Whitehead’s Principia Mathematica. Soon he found his stride, being awarded a distinguished degree in 1934, a King’s College junior research fellowship in 1935, and a Smith’s Prize in 1936 to pursue research on probability theory. That was just the beginning of his remarkable intellectual journey in mathematical logic, computer science, cryptography, and biological emergence.
My own journey to appreciating Turing’s genius came about not through his conceiving of the modern computer in 1935, his notion of a Universal Machine (today called a Turing Machine) or the ‘Turing test’ for determining whether a machine demonstrates human behavior, or even Turing’s heroism in deciphering the German Enigma code during World War II. It was while exploring the economic geography of the early industrial era, a field pioneered by Keynes’s professor Alfred Marshall, that I came across Turing’s ideas about biological emergence. An edited volume of Turing’s writings on Morphogenesis (1992) opens with a caricature by his mother Sara “of Alan at hockey,” dated “springtime 1923.” The curious thing about the drawing is that, while most players are huddled around the one of the goals in the outdoor arena, Turing is off to the side investigating a flower emerging just off the field. His mother titled the sketch ‘Hockey or Watching the Daisies Grow’. In the final years of his life – he died by his own hand in 1954 – the wonder Turing displayed at such emergence while playing hockey came, so to speak, full flower. He immersed himself in trying to understand the physical and chemical processes that produce pattern formation in nature and that are responsible for phyllotaxis, the arrangements of leaves on the stems of plants. While investigating morphogenesis, Turing “achieved the distinction of being the first to engage in the computer-assisted exploration of nonlinear dynamical systems,” wrote B. Jack Copeland and Diane Proudfoot in ‘Alan Turing’s Forgotten Ideas in Computer Science‘ published in Scientific American in 1999. Turing wrote computer programs that model how certain patterns occur in nature, whether the petal arrangement in flowers, the seed arrangement in pine cones, or the spots and stripes on animals,
Developmental biologist Lewis Wolpert uses the French flag to help illustrate the complex, nonlinear dynamics of biological gradients and the challenge for regenerating tissue: “Given that a line of cells that can be blue, red, or white, how should they communicate with each other so as to form a French flag that is one-third red, one-third white, and one-third blue, and continue to do so even when parts are removed?” Wolpert asks in his book The Triumph of the Embryo. Wolpert found the answer in the ability of cells in regenerating systems to ‘know’ where they are in a coordinate system, a gradient, to possess positional information. It was Turing who put us on the path to understanding the chemistry of growth in biological gradients, that is, in complex organisms like us. Turing pioneered critical features of our current understanding of form in development, or morphogenesis, as well as pattern formation. We know today that both processes are controlled by genes.
Economists interested in economic geography are learning from biological models of emergence such as the development of the daisy described by Turing. In his brief and incomplete ‘Outline of the Development of a Daisy’, Turing writes: “At a certain point in the development of the daisy the anatomical changes begin. From this point, as has been mentioned, it becomes hopelessly impracticable to follow the process mathematically.”
So it is with complex dynamic systems including clusters of innovation such as the thriving Cambridge cluster (Silicon Fen) with its 1,500 companies employing more than 50,000 people. If Turing had had at his disposal the oracular hypercomputer he had envisioned, he could have laid out nature’s daisy program for the whole world to see. The intricacies and mysteries of Cambridge’s cluster dynamics would likewise be readily apparent.
That would please Hermann Hauser. The Austrian-born serial technology entrepreneur was one of the founders of the Cambridge Network and is a pioneer of Europe’s venture capital industry through Amadeus Capital Partners, a firm he founded in 1997. Hauser moved quickly into the entrepreneurial realm in 1977 after earning a doctorate degree in physics from the Cavendish Laboratory at King’s College, which named him Honorary Fellow in 1998, an honor with which he joins Keynes.
I met Hauser at Stem Cells Asia 2010 in Seoul where I gave a talk. He was casually dressed and was wearing sneakers, which set him apart from other attendees. Hauser has an unassuming, easy-going manner. He talked about how he does not invest in the pharmaceutical sector but expressed great interest in the potential of cell therapy to treat disease and regenerative medicine to restore function in diseased and damaged organs and tissues. We discussed advances in organ regeneration using stem cells or progenitor cells to refurbish a diseased or dysfunctional organ. Pattern recognition is part of this process.
As a serial entrepreneur, Hauser is interested in how entrepreneurs are educated and trained. Psychological research is also coming into play: stressing risk tolerance in behavior and personality as well as the “know-how” of entrepreneurship, for example, could help would-be entrepreneurs to reframe their decisions, mitigating the negative perception of risk in starting a new venture. Geography also could play a role. Hauser agrees, writing in Nature: “One of the beneficial effects of entrepreneurial clusters in regions such as Silicon Fen may be that the increased networking and contact amongst the entrepreneurs works to create a culture that normalizes a more risk-tolerant type of decision-making.” An entrepreneur’s natural ability is founded on the interaction of genes and environment, Hauser contends. In 1997 only 17 percent of entrepreneurs in the portfolio of Amadeus Capital were serial entrepreneurs. By 2009 about 70 percent were serial entrepreneurs, contributing substantially to the numerous high-tech companies in the Cambridge region. “Know-how is transmitted ‘in the air’ within these high-technology clusters,” Hauser wrote, borrowing Alfred Marshall’s phrase. In an email exchange Hauser sent me a passage from Marshall’s Principles of Economics: “When an industry has chosen a locality for itself, it is likely to stay there long: so great are the advantages which people following the same skilled trade get from near neighbourhood to one another. The mysteries of trade become no mysteries; but are as it were in the air, and children learn many of them unconsciously.”
Cambridge, where Marshall taught a century ago, has become a low-risk area for doing high-risk things, Hauser says, borrowing the phrase from a Cambridge bioscience entrepreneur.
The risk-taking characteristic of entrepreneurs like Hauser has been key to the idea of progress ever since the French economist Jean Baptiste-Say brought the term entrepreneur into general use at the beginning of the eighteenth century. If there is a symbolic moment for risk-taking in the context of relentless inquiry, it occurred centuries earlier. One day when he was a young man wandering in the Tuscan countryside, Leonardo da Vinci came upon the mouth of a huge cave. As he stood in front of it, he was seized by the question of what to do—to explore or to retreat: “I had been there for some time, when there suddenly arose in me two things, fear and desire—fear of that threatening dark cave; desire to see if there was some marvelous thing within.” After negotiating the line between curiosity and fear, he resolved his dilemma by venturing into the cave of the unknown to see what he might find. The ‘marvelous thing within’ was, in a very real sense, the human body as he imagined it, carefully observed it, and recreated it in two dimensions with his hand. He pondered the mystery of reproduction and development in a room filled with corpses and their contents—organs, vessels, muscles, bone, and limbs. Leonardo undertook the exploratory task at a time when such dissections, Charles Nicholl writes in his biography Leonardo da Vinci: Flights of the Mind, “were beset by taboos and doctrinal doubts.”
A King’s College graduate and Royal Society of Literature fellow, Nicholl has also written about the lives of Christopher Marlowe, Arthur Rimbaud, Thomas Nashe, and William Shakespeare. He took five years to research and write Flights of the Mind, Leonardo’s flights into the artistic and scientific unknown through observation, experimentation, and creation. Long before Turing, Leonardo was exploring bodily proportions and natural patterns and expressing them visually through the mathematics of geometry. He planted the seeds for many of today’s technologies. In Nicholl’s account, for example, a NASA scientist who reconstructed a working model of Leonardo’s robot knight, an automated war machine, described it as “the first known example in the story of civilization of the programmable analogue computer.” Leonardo’s humanoid robot made its debut around 1495. From the sixteenth century, with a “cumulative crescendo” after the eighteenth, Keynes wrote in his essay, “the great age of science and technical inventions began, which since the beginning of the nineteenth century has been in full flood” swept along by “automatic machinery and the methods of mass production.”
Nicholl reminds us that dissection was a messy thing in Leonardo’s day. It took a special genius “to make visual sense of the unfamiliar landscape of glutinous and collapsing forms” and then to draw them with such precision, beauty, and transparency, particularly under the constant threat of being discovered by the authorities. Taking an umbilical cord from a deceased mother with child, Leonardo held it aloft, examined it, and drew it into his anatomical masterpiece, The Fetus in the Womb. He called it the “great mystery.”
Five centuries after Leonardo’s foray into a Tuscan cave, a story appeared on the front page of The New York Times that harkened back to Leonardo’s great mystery. Written by veteran science reporter Nicholas Wade, who earned a bachelor of arts degree in natural science from King’s College, the story was headlined ‘Scientists Cultivate Cells at Root of Human Life‘. Wade’s opening sentence made it clear this was not just another of the research advances that occupy an ever-growing segment of the daily news: “Pushing the frontiers of biology closer to the central mystery of life, scientists have for the first time picked out and cultivated the primordial human cells from which an entire individual is created.”
Wade’s story appeared in 1998 upon the publication of a study in Science in which James Thomson and his research team showed that they had isolated and grown embryonic stem cells from human blastocysts obtained from a fertility clinic. A great debate over the moral status of the human embryo ensued. Since then Wade has written three books about genetics and human evolution: Before the Dawn (2007), The Faith Instinct (2009), and A Troublesome Inheritance (2014). Perhaps no writer today has sought as energetically as Wade to bring to the general public the story of what genetic variation from genomic studies means for understanding early human migration and subsequent human development and culture. Not since our ancestral population, in Wade’s words, “was still confined to its homeland in northeast Africa but had begun to show the first signs of modern behavior” has technology allowed us to look so deeply into our own evolutionary experience.
A Troublesome Inheritance, Wade’s foray into the minefield of genetic variation and race, has not been well received by those who see race as a “social construct” with no basis in biology. Anxiety about a revival of eugenics in the genomics era is not entirely misplaced. After all, for all his brilliance Keynes served as director of the British Eugenics Society late in his life, calling the field “the most important, significant and, I would add, genuine branch of sociology which exists” shortly before his death in 1946. Writing before he published his ‘Economic Possibilities for Our Grandchildren’ essay, Keynes thought the time would come when “the community as a whole must pay attention to the innate quality as well as the mere number of its future members.”
Wade sees the issue as how best to sustain the fight against racism in light of new information from the human genome that bears on race. “My belief is that opposition to racism should be based on principle, not on science,” he wrote in the Huffington Post. “If I oppose racism and discrimination as a matter of principle, I don’t care what the science may say because I’ll never change my position. As it happens, however, the genome gives no support to racism, although it does clearly show that race has a biological basis, just as common sense might suggest.” Metabolism of drugs, for example, may be influenced by race and ethnicity as well as diet and other medications.
The $3 billion Human Genome Project was funded by Congress in 1990 for its promise of medical treatments, not for its value to evolutionary studies. A decade after President Bill Clinton announced in 2000 that the first draft of the human genome sequence was complete, in the eyes of some, Wade included, the human genomics field had yet to live up to its billing as a predictor of disease let alone as a foundation for a new generation of therapies. Under the New York Times headline ‘A Decade Later, Genetic Map Yields Few New Cures’, Wade observed that the linking common genetic variations tightly with disease risk had proved devilishly difficult. The tight linkage of disease risk seemed to be reserved for rare genetic variations, which could be identified with whole-genome sequencing. “That approach is now becoming feasible because the cost of sequencing has plummeted, from about $500 million for the first human genome completed in 2003 to costs of $5,000 to $10,000 that are expected next year,” Wade reported in June 2010. Several months earlier Wade had described how geneticists had given a preview of the power of personal genomics when they reported that whole-genome sequencing had enabled them to pinpoint rare mutations that cause recessive Mendelian disorders in families. The findings suggested to geneticists that it is possible to sequence the entire genome of a patient “at reasonable cost and with sufficient accuracy to be of practical use to medical researchers.” Less than four years later the scientific instrument company Illumina announced that it had developed technology that can sequence the genome of a human cell for $1,000, a milestone in the field.
At the end of the last millennium, the scientist and Nobel economist Robert W. Fogel was astonished that so soon after Kitty Hawk a man was standing on the moon. Fogel used the example in his presidential address to the American Economic Association to illustrate the challenge the economics profession faces in trying to keep up with the dizzying pace of technological change and the enormous advances in food production, nutrition, public health, and human longevity over the past three centuries. His timeline of technological innovation and population growth reflects the “cumulative crescendo” of scientific and technical advances beginning in the nineteenth century that Keynes wrote about in his essay. “We are slow in pondering such grand questions as the implications of the Human Genome Project, which is now nearing completion, and the emergence of molecular medicine for the future of economic life”
When he gave his talk in 1999, Fogel saw that the machines that Turing envisioned were transforming society. Innovation and entrepreneurship championed by the likes of Hauser were driving technological change. In societies with abundant food the human body had assumed greater proportions since the day that Leonardo, as described by Nicholl, had drawn it with such precision, beauty, and transparency. The gene and the cell were disclosing their operating instructions, a process of discovery that no one chronicled more completely than Wade. “We have entered an era in which purposeful intervention in evolutionary processes is passing beyond plant and animal breeding”, Fogel said. “The new growth economics needs to incorporate at least some aspects of directed, rapid human evolution.”
The children and grandchildren of Keynes’s generation were materially much better off than their parents and grandparents. One of the reasons is their own ingenuity. They launched revolutions in information technology and space exploration. They harnessed the power and versatility of biological science, genetics, and reproduction to feed the world and control fertility. Today the possibilities for our grandchildren, in addition to their task of managing the abundance and leisure that Keynes predicted, might well include managing their health and understanding their dispositions from knowledge of the three billion letters in their genetic code. The possibilities might include the editing of genomes to correct misspellings responsible for disease and mental illness and to alter the human germline thus altering our own cellular journey from its African origins.
Though Keynes mentions Darwin in his essay, the ability of our descendents to guide the evolution of our species is probably not something he had in mind while musing about the future of work. It makes the counsel he expressed toward the end of his essay all the more perspicacious: there will be no harm in making mild preparations for our destiny.