Conscious: A Brief Guide to the Fundamental Mystery of the Mind,

 which, as its title implies, addresses big questions about consciousness, its origins, where it exists in nature, and if it could be generated by artificial intelligence. I thought I was tackling the most pressing inquiries, but through the process of writing that book, I encountered another, perhaps even more important, question: Is consciousness fundamental? That is, could it be an irreducible property of the universe, existing alongside those that physics has already begun to understand, such as gravity, electricity, and the strong and weak nuclear forces?

In search of answers, I looked to the physicists, neuroscientists, and philosophers who are exploring this question in their work. These conversations took on a life of their own, eventually crystallizing into an audio documentary tracking my quest. An exclusive excerpt from that work is included below—a special conversation with author and neuroscientist David Eagelman about how our brains construct reality and the scientific utility of studying illusions. Over time, I became convinced that a view of the universe in which consciousness is fundamental is a possibility. This revolutionary idea challenges traditional neuroscience and quantum physics, shattering what we think we know about ourselves and scientific phenomena as foundational as space and time.

It's easy for us, as humans, to take consciousness for granted. But when we take a closer look at all that science has told us about the universe, we're quickly faced with this greatest of all mysteries. Why do certain configurations of matter cause that matter to light up from the inside with felt experience? Why does any collection of matter in the universe, even brain processing, feel like anything at all?​​

There's a wonderful quote from the philosopher Rebecca Goldstein about the mystery of consciousness, which captures this idea and helps us understand the relationship between the physical brain and the more mysterious experience of consciousness. She writes, "Sure, consciousness is a matter of matter. What else could it be? Since that's what we are. But still, the fact that some hunks of matter have an inner life is unlike any other properties of matter we have yet encountered, much less accounted for. The laws of matter in motion can produce this. All this? Suddenly matter wakes up and takes in the world." ♦

Chapter 5 of Lights On, ft. Anil Seth & David Eagleman

NSCIOUS: A Brief Guide to the Fundamental Mystery of the Mind

 and writer and producer of the forthcoming audio documentary series, 

Three-dimensional anatomical diagram of human head, 1885.

Advance Copy features exclusive excerpts from forthcoming books by leading novelists, essayists, poets, artists, and scientists.

Lights On

One day in 2010, I got a headache. The pain was not severe, but it was constant—accompanied by a strange feeling of belatedness which meant that, when I first became conscious of it, I knew it had already been going on for some time, lingering just beneath the threshold of awareness. How long exactly, I couldn’t say—weeks, definitely. Maybe it had been years.

After about a month I visited the doctor. In those days, this was not a knee-jerk response. This must have been at the start of June because it was warm out, and I remember that I was on my way to return a suitcase and two shopping bags full of overdue library books—something that, to my discredit, I did only twice a year, on the first Monday after the end of the winter and the summer terms.

The doctor had an earnest, warbling, confident way of speaking that, in spite of her evident commitment to the tenets of mainstream medicine, gave her the unshakeable air of an alternative healer. She explained that what I was experiencing were called tension headaches, an ailment that was common among students and during exam season practically universal. I said that I didn’t feel very tense. The doctor asked whether the pain felt like a tightness across both sides of the head. A kind of squeezing? Like an elastic band being pulled tight? Like a fist clenching around your skull? I said that it did not feel like these things. Yes, she said, nodding meaningfully. Every person experiences tension differently.

The doctor asked me what medication I’d been using to manage the pain. I was thrown by this question; the thought had not occurred to me. This was, in many ways, quite surprising, since I have never been a person to make a virtue out of forbearance and actually consider my tolerance to pain to be less developed than the average. In the case of this headache, however, my attitude was edging closer to that of Franz Kafka. A century earlier, the writer told his soon-to-be fiancée Felice Bauer that he never took aspirin because doing so, he said, created "a sense of artificiality" that in his opinion was far worse than any "natural affliction." Aspirin had been developed a few years earlier in the laboratories of the Bayer Company. Originally intended to treat rheumatism, it quickly gained popularity among healthy consumers looking to ease the ordinary pains of modern living. However, for Kafka it was vital to pay attention to every aspect of one’s existence, no matter how small or seemingly trivial; which was why, as he later said, he made a habit of viewing his life through “microscopical eyes.” As Kafka explained to Felice, if you had a headache, you had to undergo the experience of pain and treat it as a sign, before examining your entire life, right down to its most minute detail, “so as to understand where the origins of your headaches are hidden.”

The idea of taking painkillers struck me as irresponsible, even reckless, like disconnecting a fire alarm because it has interrupted your sleep. Besides, the pain itself was bearable. Only its persistence concerned me, the meaning of it. Like Kafka, I wanted to understand the headache. The doctor told me to come back in a few weeks if things hadn’t got better, sooner if they got worse. I left her office holding a bottle of aspirin, which I promptly deposited in the bin.

In her short essay “In Bed,” Joan Didion writes about the chronic headaches that she suffered from on a weekly basis. Didion begins by explaining that migraine is an inherited condition, a “physiological error.” By the end of the essay, however, Didion is describing a sly complicity between the migraine and its sufferer:

We have reached a certain understanding, my migraine and I. It never comes when I am in real trouble … It comes instead when I am fighting not an open but a guerrilla war with my own life, during weeks of small household confusions, lost laundry, unhappy help, canceled appointments, on days when the telephone rings too much and I get no work done and the wind is coming up.

The migraines that regularly kept Didion hauled up in bed appear to be an unbearable yet not entirely unwelcome remission from the aching responsibilities of everyday life. And in this sense, a sort of pain relief.

My headache was nothing like that. My headache was very bearable. Terribly bearable. So that instead of extricating me from my everyday life, it pushed me deeper into it. I became irascible, morose. My entire life came to resemble one of those days when the wind is coming up; one of those days when in answer to the question “what’s wrong?” we are obliged, through gritted teeth, to answer “nothing” so as to spare ourselves the graver indignity of uttering “everything.”

As summer wore on I occasionally noticed myself not noticing the headache. I might be swimming, or making love, or reading, and it would happily occur to me that I no longer felt any pain. However, this reflection always served to drive it out of hiding, and the mild, negligible pain would resume its place at the forefront of my mind. These were not spells of remission, therefore, so much as lapses of attention. As time passed, they became fewer and farther between.

By autumn I had started noticing lots of other little anomalies. I became forgetful. Words kept escaping me. In a crowded bar one evening, I spent 15 minutes trying to guess where I’d met the bespectacled, aloof young man in front of me, certain that he was playing a game, not letting on. Until, annoyed and frankly a little unnerved, he finally said, “Look, I’m just trying to get a drink.” I developed a twitch in my left eye, which would refer down to my middle finger, so that in lectures I always seemed to be tapping out the unsteady beat to some inaudible tune. One pupil became slightly larger than the other and coffee started tasting weird and metallic. One morning I turned on the tap and had no idea whether the water was hot or cold.

I developed a very mild but persistent case of the hiccups, just one, two, maybe three solitary little hiccups each day. Can hiccups be caused by brain cancer? I asked Google. Yes, it answered—if it is advanced.

My symptoms multiplied. At some point I began to keep a list of all these things as they arose, doing so on a loose sheet of paper headed SYMPTOMS, which I stowed in my sock drawer. Reading back over that list, it struck me that it resembled the descriptions of illnesses that I browsed online. But I also felt there was the risk in setting all this down on paper that it would give weight and solidity to a set of experiences whose most maddening quality was their shimmering insubstantiality. It’s true that there were times when these phenomena occurred simultaneously, times when they condensed into something like a palpable disease. Or at the risk of putting things a little dramatically, when these sensory glitches had seeped so deeply into my experience of the world that, as I once explained to a friend, it felt as if reality itself was becoming sick. However, these periods were punctuated by spells of relative calm. Days would pass by without incident, perhaps when I was busy, happily industrious, unconsciously embedded in life. But in a pattern that was becoming familiar, no sooner would I reflect on the absence of these disturbances than I would start to notice them again.

You could say that my attention was producing these things; you could say it was revealing them.

Hypochondria can function like a sort of waiting room, albeit one in which not everyone’s name will finally be called.

For all its tenacity, there is something wispy about hypochondria, with its preference for the slight and subtle, its attunement to what might be nothing at all. To be a hypochondriac is to assign the most important role in one’s life to something that no one else believes is real, and therefore to embrace a certain tenuousness. Little wonder it is often called “phantom illness.”

I think this is why my hypochondria was always worst at night: with nothing else to distract it, my mind latched onto vaguer things. Shapes flickered overhead, my ears sang, while thoughts that had been successfully banished during the day passed freely into consciousness. Most crucifying of all was the thought that I had let another day slip by, another day in which, had initiative and resolve not once again been found wanting, I might have done something about it. That whatever was going to happen to me, it would be entirely my fault. No sooner would this thought occur to me than a parade of awful images would dance across my mind’s eye.

Friends knew about all of this, knew that I worried about my health, that I was spending a lot of time at the doctor. But I don’t think any of them really understood just how much of my mind had been given over to these fears which, even at their peak, I knew might be unfounded. None of this speaks to any failure of empathy; the gap separating our minds was greater than that. In fact, even for me, as I look back today, it is only with a sort of amused contempt that I can look upon that anxious sleeper.

“Everyone who is born holds dual citizenship, in the kingdom of the well and in the kingdom of the sick,” writes Susan Sontag at the beginning of 

. “Although we all prefer to use only the good passport, sooner or later each of us is obliged, at least for a spell, to identify ourselves as citizens of that other place.”

With these metaphors, Sontag is suggesting that there is a clear border separating health and sickness. This is a defining feature of the medicine that has flourished in the liberal economies of the West—where, as Artie Vierkant and Beatrice Adler-Bolton have argued in 

, “health” and “sickness” are heavily politicized, and policed, terms that determine who does and who does not deserve access to state provisions that are always, and by definition, supposed to be scarce. The Marxist critic David Harvey has gone so far as to argue that sickness under capitalism is defined as the inability to work. This is the reflection that leads Deleuze to hear an expression of hypochondria in Bartleby’s enigmatic statement “I would prefer not to”—words that wreak havoc and disrupt the flow of capital in Melville’s famous “Story of Wall Street.” And so we might say that, a full citizen of neither kingdom, the hypochondriac quietly protests capitalism’s ableist demand that the “healthy” body always be a productive body.

A recent Autoimmune Association survey found that more than 45 percent of patients who go on to be diagnosed with autoimmune diseases have been labelled hypochondriacs in the early stages of their illnesses, while in the United States half of those who go on to be diagnosed with endometriosis—a potentially debilitating condition affecting 10–15 percent of people with wombs—report being initially misdiagnosed with a psychological condition, with physical diagnosis taking on average seven and a half years from the first appearance of symptoms.

This is a recent chapter in a long history of conditions being labelled psychosomatic when their symptoms fall outside the paradigms of current knowledge. In the nineteenth century, for instance, sufferers of multiple sclerosis were often regarded as hysterics, while the neurological symptoms of tertiary syphilis were regarded as a form of moral insanity. It is only very recently (largely due to the sheer extent of long COVID) that the sufferers of post-viral conditions have begun to receive widespread recognition for the physiological basis of their symptoms.

However, we have to acknowledge that here we are also in the territory of the so-called “contested” diagnoses such as Morgellons disease, a condition with no accepted medical basis, whose self-proclaimed sufferers have formed themselves into online advice and advocacy groups as they aspire to the patienthood that would recognize (and listening to some of them, one is tempted to say alleviate) their suffering. For psychiatry, sufferers of Morgellons are indeed sick, but not in the way they think; in fact they are suffering from a mental illness called “delusional parasitosis.” Meanwhile in the late nineteenth century, when around one in 10 adult men in Britain had syphilis—a disease that could lie dormant for decades and which, at that time, had no test or cure—newspapers and psychiatry manuals began warning of an epidemic of a new disease, responsible for a string of suicides, that was variously called syphilophobia or venereal hypochondriasis.

All of which is to say that hypochondria is never simply the patient’s condition. The question of who the hypochondriac is, what’s the matter with them, always speaks to the current position of medical knowledge—the ways in which, at any given moment, its categories account for, and do not fully account for, the spectrum of human suffering. Hypochondria, therefore, can function like a sort of waiting room, albeit one in which not everyone’s name will finally be called.

We would prefer to believe that there is a definite border separating the normal and the pathological because this would make it possible, at least in theory, to know for certain that one is on the right side of it. If the hypochondriac is rarely a welcome presence, then surely this is partly down to the way they cast light on the unsteady boundary separating health and illness, the fact that it is not fixed once and for all, the way it continues to shift as diseases are discovered, reformulated, reimagined.

We might say, then, that hypochondria serves as a useful, if humbling, reminder of the limits of medicine’s knowledge. In which case, the peremptory confinement of the hypochondriac to the ranks of the mentally ill—a patient whose symptoms might be treated, say, with antidepressants or some sessions of CBT (an “anxietyectomy”)—represents a denial of those limits. Moreover, making this judgment would require us to assume a diagnostic omniscience that begins to make the hypochondriac’s uncertainty seem like the more credible position. I’m not denigrating medical knowledge, but I am suggesting that by suspending the diagnostic impulse—our claim to know for certain either way—we’re able to catch sight of an uncomfortable question that is posed by the hypochondriac. A question that cuts right to the core of all our relationships, as thinking beings, to our physical bodies: to what extent do we ever 

If the hypochondriac is rarely a welcome presence, then surely this is partly down to the way they cast light on the unsteady boundary separating health and illness.

“Strictly speaking, there is no science of health,” writes the philosopher Georges Canguilhem. “Health is organic innocence. It must be lost, like all innocence, so that knowledge may be possible.” If health is a form of innocence, a sort of unselfconscious flourishing, then what does this mean for an era of ever-extending knowledge about disease? What happens to health in societies that are concerned, precisely, with health?

In premodern times, disease adhered closely to the subjective experience of illness. This is because there were only very limited tools for distinguishing the latent and the manifest: to be sick was to feel unwell. Across the Enlightenment the two steadily begin parting ways, but the seismic shift occurred in the second half of the nineteenth century, with the development of X-rays and microbiology, technologies that broke the old alliance between eye and world by making it possible to see the invisible vectors and lesions of disease. Like Descartes, the pioneers of these technological developments laid bare the chasm between experience and reality: increasingly disease was something that could exist in the body without erupting into consciousness.

In industrialized countries over the last century and half, developments in medicine, sanitation, and hygiene mean that the landscape of death has been transformed beyond recognition. For 100 years between 1750 and 1850, U.K. life expectancy hovered at around 40. Across the same span, between 1850 and 1950, it rose from 40 to 68, reaching 81 by 2020. In 1908 a third of deaths were in under-fives; today that figure is less than one in a 100. In 1908 fewer than one person in 10 would live to 75; today fewer than one in three will die before reaching that age.

Changes with regards to who is dying have been accompanied and abetted by changes to how people are dying. In 1908 infectious disease accounted for 20 percent of deaths; today (with a brief anomaly in 2020–21) it accounts for 7 percent. Across the same period, deaths caused by chronic, progressive diseases have steadily increased. In 1908 cancer was responsible for around one death in 20. Death no longer bursts in rudely on the scene of life; it advances slowly, tactfully, governed by a set of recognizable customs.

One effect of all this has been to assign a new role to the notion of “awareness.” In 1907 the surgeon and early cancer activist Charles Childe published 

The Control of a Scourge, Or How Cancer Is Curable

, addressed to a general readership. In it he warns, “You measure your disease by the amount of suffering it causes you, a natural but ghastly error.” This means that cancer’s innocent victims are often “quite naturally lulled by the entire absence of symptoms into a sense of security.”

In the decades that followed, innocence would become one of the greatest threats to a person’s physical well-being. Starting in the 1930s, cancers that respond better to treatment before they have become very advanced—at a period during which any manifestations are discreet and quotidian—became a frequent topic of public information campaigns, aided by the rise of mass media. In the United States, the American Society for the Control of Cancer (the forerunner of the American Cancer Society) delivered the message that “Delay Kills!” Between 1936 and 1948 a “Women’s Field Army,” kitted out in khaki, informed the public about the value of smear tests, clinical and self-performed breast exams, and practicing vigilance toward early warning signs. In this “fight,” the Society deployed the weapons of a growing publicity industry: a WWII–era poster claimed that more people died each fortnight from a delayed cancer diagnosis than had died at Pearl Harbor.

In the decades since then, awareness campaigns have become commonplace. A few years ago I remember seeing posters around London warning “You can’t always see the signs” and encouraging people to check their stools for early signs of bowel cancer. These sorts of campaigns publicize the gap between subjective experience and organic reality: between how well you might feel and how sick you might be.

In this gap there is also a lot of money to be made. Since the late 1990s, websites such as WebMD and Healthline have grown into multimillion-dollar businesses by disseminating lists of early warning signs. “Did you know your nails can reveal clues to your overall health?” begins a typical article on WebMD. These articles tend to emphasize the arbitrariness of the relationship between signifier and signified: “A touch of white here, a rosy tinge there, or some rippling or bumps may be a sign of disease in the body. Problems in the liver, lungs, and heart can show up in your nails. Keep reading to learn what secrets your nails might reveal.” All this makes for pretty compelling copy, at least for the right sort of reader, which is obviously important for a business model that works by monetizing attention. The success of these companies indicates a shift in reading habits: where in the twentieth century health organizations used the tools of the advertising industry to publicize health risks, today private companies publicize health risks to sell consumer products.

originally applied to the reading not of literature but of the first and most perplexing text: the human body. These campaigns and articles are an exercise in practical criticism. They train people to be suspicious readers of their bodies. To be truly healthy, one must be more critical with regard to one’s experience of subjective well-being. A sunken nail bed? A headache? A sore? How long has this mild cough been going on? Did I always become so bloated after dinner? Don’t my gums bleed each time I brush my teeth?

Under contemporary conditions, the ideal of perfect health becomes something of a self-contradicting enterprise, since the only way it can be ensured is through a practice of conscious scrutiny that is incompatible with any holistic ideal. In the words of Wendell Berry:

From our constant and increasing concerns about health, you can tell how seriously diseased we are. Health, as we may remember from at least some of the days of our youth, is at once wholeness and a kind of unconsciousness. Disease (dis-ease), on the contrary, makes us conscious not only of the state of our health but of the division of our bodies and our world into parts.

Perhaps this is really what Freud meant when he said that hypochondria exposes the limits of our knowledge. Not an absence of knowledge, a gap that could be filled with new information, but a more categorical deficiency: the failure of knowledge to ever bring about the states of health, happiness, or even certainty which we prefer.

Hence the dialectical traps in which hypochondriacs are liable to ensnare themselves: the hypochondriac wants to feel healthy, vibrant, alive, yet in their desire to be certain of these things, they constantly find themselves feeling the opposite.

“Ours is an age which consciously pursues health, and yet only believes in the reality of sickness,” writes Susan Sontag. Health has become elusive in a society in which people are encouraged to scrutinize all aspects of their mental and bodily well-being: today being well means forever wondering just how “well” one really is. ♦

Will Rees is a writer and editor living in London. He is a founder and editor of Peninsula Press, which he co-founded in 2018.

Hypochondria

In recent weeks, as a new administration in Washington has worked diligently to possibly destroy our government (or merely, as Elon Musk claims, to trim its fat), Americans have learned a great deal about how that government works. They’ve also learned about the roles and responsibilities of a few unheralded agencies with obscure acronyms for names. One of these is the Office of Management and Budget, or OMB: a vast office that oversees federal operations and the census, and which is often responsible for determining the data and systems by which our tax dollars are allocated and spent. 

One of the OMB’s legacies, which I’ve been thinking about a lot lately, was issued in 1977. That’s when the office adopted Directive No. 15, which established four standard racial categories by which Americans could be grouped: White, Black, Asian/Pacific Islander, and American Indian/Alaska Native. The OMB’s civil servants had identified a need for consistent racial data across the government, per a series of civil rights acts that had been recently signed into law. Yet these categories—racial labels that the OMB argued had no basis in genetic science—became the standard by which government, society, and a great deal of scientific research would come to approach the vexed topic of race, and still do so today.

The four categories comprising “OMB Race” were themselves borrowed from what I call “UNESCO Race”—an understanding of human difference that the United Nations’ scholarly wing, not long after the UN’s founding in the aftermath of World War II, proclaimed as humanity’s gold standard in 1951. UNESCO’s conception of race was based not in skin color but continent of origin; and it explicitly affirmed equality among peoples and rejected White supremacy. It also rebutted the eugenicist ideas of the Nazis and many other governments—including our own—whose approach to public health, immigration, and other realms reflected a tacit embrace of the idea that humanity was in fact comprised of different racial subspecies, identifiable by skin-color but possessed of other intrinsic traits, whose mixing was to be avoided.

Yet UNESCO’s continental framework was an idea as old as race itself, a concept that naturalists in seventeenth-century Europe had invented to sort through the flood of data returning with explorers and colonists traveling the globe. In ensuing centuries, as race was used to justify slavery and conquest and other ills, the bases and contours of racial ideas would shift—from Enlightenment thinkers’ expounding of the notion that only Europeans had a capacity for reason, to Charles Darwin’s affirmation that humans were a single species comprised of several subspecies, and on to modern eugenicists’ belief, riffing on Darwin, in a genetic hierarchy to those subspecies. But nothing underscores the persistent grip of continental “race thinking” on society like the fact that even our most concerted attempts to combat centuries of racism today have often ended up re-affirming race as an idea based on genes specific to discrete continental populations.

That was certainly the case with OMB Race, whose categories remained based on a continent-of-origin understanding of racial difference. And the OMB’s categories, which remain with us still, would have fateful consequences as genetic science rapidly progressed across the last decades of the twentieth century and into this one.

Since Darwin’s time, geneticists had used family pedigree maps of bloodlines to track down health and disease-causing genes in humans. But as scientists found ways to isolate and analyze specific sequences of DNA within genes in the tail end of the twentieth century, and as they learned to manipulate those sequences with new chemistry and informatic technologies, modern genetics was eclipsed by “genomics,” the study of all the DNA sequences in an organism. Genome scientists deployed novel techniques for mapping and cloning DNA to learn a great deal about the basic mechanics of human DNA that apply to every person. They found that DNA—deoxyribonucleic acid—is the machinery in our cells that encodes all the proteins (hormones, enzymes, antibodies) that we need to live. And they confirmed that every one of our cells contains the same DNA that’s passed down to us from our ancestors, via our parents’ egg and sperm, in the twenty-three chromosomes that lie in our cells’ nuclei. (A tiny bit of DNA, known as mtDNA, also resides in our cells’ mitochondria.)

In 1986, the famed discoverer of the double helix, 

, along with several other leading genome scientists working at the Salk Institute, U.S. National Institutes of Health (NIH), and U.S. Department of Energy (DOE), called for a global initiative to sequence a human genome. The aim of these researchers––many of whom were homing in on sequences associated with cancer and other debilitating illnesses—was to produce a reference that anyone anywhere in the world could use to better understand DNA sequences. In 1989, Francis Collins, a researcher at the Howard Hughes Medical Institute in Maryland, used an innovative mapping technique he had developed to find the gene responsible for cystic fibrosis. Within months, his team and others around the world were able to pinpoint disease genes that had stumped geneticists for over a century. With this proof of concept, the federal government swiftly moved to fund the proposed genome project, allocating three billion dollars to James Watson at the NIH and the molecular biologist David J. Galas at the DOE.

Over the next couple years, 17 nations joined the NIH and DOE to launch the first Human Genome Project. Watson and Galas soon passed leadership to Francis Collins and Ari Patrinos, leader of the DOE’s Biological and Environment Research division. In these first years of the Human Genome Project, none of the project leaders discussed global diversity or race. They merely sourced DNA from the most convenient repositories on hand—those in northwestern Europe and the United States. At the same time, the Surgeon General and officials across America’s chief public health departments such as the Department of Health and Human Services (HHS), Centers for Disease Control and Prevention (CDC), and Food and Drug Administration (FDA) were working hard to figure out how to implement OMB race in their operations. The Surgeon General and HHS had published reports about the long-overdue need for racial minorities’ inclusion in health research and greater research into racial health disparities. To ensure that U.S. health science was fulfilling these briefs, the NIH mandated in 1992 that all publicly funded researchers tabulate the race of their study participants. Thus was the Human Genome Project indelibly shaped by existent discussions of a faux-scientific concept, fiercely lodged in our imaginations and our societies alike. Our genome’s mapping, which should have been predicated on helping bury race forever, was primed instead to perpetuate old lies about human difference.

Once scientists were required to report the race of their study’s participants according to the OMB taxonomy—White, Black, American Indian and Alaska Native, or Asian and Pacific Islander—they had to decide just how they were going to sample DNA and affix racial data to it. And this wasn’t only so in the United States. The Human Genome Project relied on collaboration by scientists and governments from around the world. But as the U.S. Health Department extended OMB race to more U.S. federal agencies that handled research abroad and the Project entered its final phase in the mid-1990s, it was the NIH that initiated much of its work. The U.S. government and leaders in American public health often administered its projects. And in 1997, the FDA also extended the use of OMB categories to drug research worldwide by requiring all new drug applications to tabulate safety and efficacy by OMB Race. This meant that drug makers interested in marketing drugs on an international scale had to report dosage recommendations by the racial scheme that the OMB had concocted for social purposes.

Seeing that the project’s own collection had no OMB data, that same year the NIH created a repository of samples that it gathered and stored using OMB Race. This racially stratified “Polymorphism Discovery Resource” would become the basis for nucleotide mapping projects and research throughout government, academic, and industry science for years to come. As the NIH worked to make the United States a leader in genomic science and diverse and equitable public health, Francis Collins and Craig Ventner, among other leaders of the Human Genome Project, began formulating a new understanding of race that matched the way sociologists and other scholars had come to view it: as a social construction formed in part by racial bias and racism, and constantly reinforced and enacted by extant inequalities and institutions in society. But these scientific leaders also insisted on examining how this social identity could interact with our genetics. They appeared in the international news media to exclaim that, without the social component, race was “a bogus idea” and that “ranking people” was something we needed to “get . . . out of our heads”; but they also called for using federal guidelines to bring racial minorities into genomics to better understand the diseases from which they suffered.

At a White House ceremony held in the East Room to commemorate the Genome Project’s first draft of the human genome, President Bill Clinton remarked on the project’s step forward for humankind, drawing attention to race: “In genetic terms, all human beings, regardless of race, are more than 99.9 percent the same.” Collins and Venter joined Clinton, Britain’s Prime Minister Tony Blair, and world leaders from Japan, China, Germany, and France in celebrating unity and denying inaccurate and harmful definitions of race. Collins delighted in sharing the news that “the only race we are talking about is the human race.” Venter added, “The concept of race has no genetic or scientific basis.” Yet within months, at a press conference, Collins issued a new statement on race that articulated the more nuanced genomic view implying that racial health disparities could be caused by legacies of gene-environment interactions accumulating disease disparities in different races over time.

From a genetic perspective, there is no logic to grouping people based on their identity as White, Black, American Indian or Alaskan Native, and Asian or Pacific Islander. 

With the release of the Human Genome Project’s first draft map in 2000, a new version of race dawned—“Genomic Race.” Like OMB Race and its immediate predecessors, Genomic Race revolves around a fictitious continental-genetic scheme (White, Black, Asian, Pacific Islander, Indigenous American) and views all races as being human, descended from a single origin, and of a single species. But unlike UNESCO’s conception upon which OMB Race is based, Genomic Race argues for research that combines social­, environmental, and genomic data to explain the amalgam of factors that make race real. It inadvertently positions its own science of gene­-environment interactions—how DNA impacts and is impacted by social experiences—as what will reveal the varying physiologies and pathologies we see in today’s races.

Scientists working in this paradigm believe in using genomics to illuminate the interaction of racial bias with genetic processes in the body—how race gets “under the skin,” and sickens us—making us more aware of the simultaneous social and biological nature of race. But like the paradigms of yesteryear, Genomic Race fails to dismantle the genetically deterministic view of race. In using continental and quasi-continental schemes of analysis like OMB Race, it reinforces the belief that racial differences are due to our genetics.

After the Human Genome Project first draft map appeared, the NIH donated its OMB-classified DNA samples to a new project comprising the Human Genome Project’s British sponsor, the Wellcome Trust, and 13 pharmaceutical and biotech companies. These companies established The SNP Consortium, named for single nucleotide polymorphisms, often called SNPs (pronounced “snips”), which are the most common type of genetic variation among people. Their goal was to develop an applied map of the human genome that could be used to enhance our understanding of disease and help facilitate research. In little more than a year, The SNP Consortium located over a million genomic variants and showed that humans passed down segments of nucleotides in chunks: what researchers called “haplotypes.” Genomic scientists rejoiced that they now had a clear path to understanding human diversity—to map these chunks of DNA in our cells.

Haplotype mapping promised to shorten the process of finding genetic culprits of disease, requiring a fraction of the time and cost of other forms of genome mapping. It also promised to generate important information about race: to make it easier to compare DNA in people and groups all over the world, revealing the history of human evolution and migration. Haplotype mapping would finally tell us what global diversity meant in terms of disease disparities—which OMB races had which diseases, and why.

In 2002, the NIH and The SNP Consortium, along with the Wellcome Trust and governmental agencies in Canada, China, and Japan, launched the International HapMap Project (what I refer to as “HapMap”). Following OMB guidelines, HapMap attempted to collect DNA from people believed to be indigenous to various continents.

Not every community embraced that mission of DNA collection. Some Native American representatives from the Arhuaco, Chippewa, Lakota, Navajo, and Paiute nations protested genetic analysis of indigenous American DNA because they did not agree with prior genome project interpretations of DNA lineages. These groups rejected the idea that Native American peoples were part of a single genetic lineage or that a DNA test could prove a person’s tribal membership. Especially given the government’s use of blood quantum laws, which limited claims to citizenship or land based on a person’s percentage of “native blood,” genetic testing was and remains a fraught topic in many native communities. Ultimately, HapMap decided to sample only DNA from Africa, Asia, and Europe, and to group those samples into continentally distinct collections. HapMap soon became the largest DNA repository in the world, one that scientists from nearly every country used in their research. This racialized database enabled Genomic Race to become the gold standard in health science worldwide.

HapMap’s leadership—scientists like Aravinda Chakravarti, a co-director with Francis Collins of the Polymorphism Discovery Resource and David Altshuler, leader of The SNP Consortium—were extremely sensitive to the quandary of addressing race. They saw how eugenics had produced a health science that served only Whites, and how eugenics had structured modern medicine to exclude racial minorities from research and healthcare. As leaders in American public health, they determined to make genomics a diverse, equitable, and inclusive science; they understood that without a strong inclusionary program, the effects of drugs and treatments on communities with minority ancestries would remain understudied, as would their basic genetics.

Good intentions abound in genomic science, but good intentions are not enough. 

Project leaders compelled external researchers using HapMap samples to report any analyses with labels that either noted the population origins from which the DNA had been sampled or an acronym of their preferred ethnic terms. In the case of DNA that the project grouped as “African,” samples had to be referred to as “Bantu-speaking populations in Africa,” for example, or “YRI” for “Yoruba of Ibadan, Nigeria.” DNA characterized as “Caucasian” was to be referred to as “populations in Europe” or “CEU” for “Utah residents with Northern and Western European ancestry from the CEPH collection.” The DNA from individuals grouped as “Asian” was to be referred to as “populations in East Asia” or “CHB/JPT” for “Han Chinese/Japanese.” So, though project leaders attempted to communicate geographical and cultural specificity by grouping collections by continent, they prompted continental analysis and comparison according to OMB Race. Genomic Race made race and genetics seem inextricably linked, while obscuring the social reality of race that it purportedly desired to expose.

HapMap’s DNA collection and labeling, in the main, perpetuated the longstanding misconception that racial groups were genetically real. More in-depth haploypte mapping of groups living in Africa, though, showed once and for all that all humans evolved from a single ancestor in Sub-Saharan Africa, and that humans are indeed one unified species. Tracing the lineages of specific haplotypes, researchers showed that there are very few human groups that correspond to what scientists would call a distinct genetic population, or a “population isolate.” Groups overlapped and intermixed, not remaining genetically distinct, mating only with people in their own culturally or geographically distinct group (what scientists call “endogamous”), as the term implies. Though a population isolate could potentially arise if a group has remained apart from the rest of the world—for example, a group living on a remote island with no inflow of outsiders, or one residing in a mountainous territory without migration—very few groups have ever remained so isolated.

Haplotype analyses have shown that even ethnic groups that scientists once assumed met the criteria for endogamy have less shared genetic ancestry than was previously believed. For example, a group once deemed a population isolate is the Parsi community. Parsis, who number in the 20,000s, comprise a group of Persians who migrated from ancient Iran to what is today India and Pakistan to practice their religion, Zoroastrianism. Another population isolate is the Sherpa community of Nepal and Tibet who, living in remote regions of the Himalayas, have adapted to the highest altitudes on the planet.

As technology has advanced, scientists have gotten a better look into the genomes of these groups, and some have retreated from identifying them as “isolates.” Genomic analysis has shown that Parsis, for example, have been more cross-cultural than was previously known, and have been endogamous only periodically. Over half of their gene pool today can be attributed to ancestral DNA lineages common in other South Asian groups (as compared to Iranians who attribute less than 10 percent of their ancestral DNA to such lineages). Likewise, Sherpas display patterns of genetic ancestry similar to those of other Tibetan, Burmese, and Nepalese groups that are not considered isolates (blends of South and East Asian lineages).

In addition to debunking myths of isolation, haplotype analysis has shown that traits and diseases that were previously thought to only benefit or harm one group hailing from one specific continent are shared by others in faraway parts of the world. Rare traits, such as the ability to breathe at high altitude, exist in populations worldwide—Europe, Asia, and the Americas—as do rare conditions: Black people aren’t the only group who get sickle cell disease and Jewish people aren’t the only group who get Tay-Sachs. The genomic prevalence of these rarities in so many populations shows how similarly humans have evolved in different parts of the world, how far we have traveled, and how much we have “mixed” with the humans we have encountered.

Rare traits are sometimes shared by very distant and different peoples. In the case of high-altitude breathing, we see evolutionary similarities among Sherpas in the Himalayas and dwellers in the Andes. We can trace lactose tolerance in a number of ancient farming communities in Sweden, South India, and Sudan. Sickle cell disease is common among the ancestral populations of western and central Africa, India, the Arab Peninsula, the Mediterranean, and parts of South America, Central America, and the Caribbean. Tay-Sachs is prevalent among the Amish, Ashkenazi Jews, Cajun, and French Canadians, but has also been on the rise in Chinese populations for several decades.

All the high-resolution haplotype mapping has led genome scientists to formulate a new nomenclature of haplogroups, grouping similar haplotypes that have been shown to come from a common ancestor, and labeling them with letters and numbers (“U5,” “M14,” etc.). These codes refer to real sequences of DNA, not anything beyond that such as race or ethnicity, nationality or language, or even traits or diseases. Haplogroup M21a, associated with my mother’s native northern Indonesian ancestry, for example, is but a small fragment of my larger genome. M21a does not encode specific genetic functions in me that would make me the same as everyone who has inherited DNA from Indonesia, and it most certainly does not make me the same as all others with Asian heritage (that is, all who share my race). By the same token, haplogroup EM2 has been associated with African American ancestry. But the EM2 haplogroup is one of many short sequences of DNA that is shared by some Black people’s genomes but isn’t present in the genome of all Black people. In other words, there is no common, universal “Black” DNA.

The neutral coding of haplogroups in alphanumeric sequences helps us avoid confusing haplogroups, which refer to genetic ancestry from very specific pinpoints on the globe, with continental race. No haplogroup is shared by all Indonesians or all African Americans, which challenges the notion that our genomes hold “Asian” or “Black” DNA. The diversity and admixture of haplogroups show that scientists should not group DNA samples or populations into discrete races as global genome projects have done, and that genomic research should not deploy the language of race as Genomic Race has done.

No matter how well-meant, using OMB Race as a proxy for genetic variation is faulty because it inaccurately draws a genetic distinction between groups of people based on the continents their ancestors came from. These categories simply don’t correspond to biological differences. From a genetic perspective, there is no logic to grouping people based on their identity as White, Black, American Indian, Alaskan Native, Asian or Pacific Islander. There is a wide range of diversity within groups local to a continent, and there can be a large amount of similarity between groups across different continents. The inaccurate fixation on continental groupings of race then leads to a social and political reality that remains incredibly harmful for every human being in the world.

Some years ago, I interviewed genome scientists around the world on what they think about this chaos in categorization. I was struck repeatedly by the extent to which they not only embraced the disarray but thrived on it. Elite scientists, who wielded a great deal of power and routinely engaged in public outreach, wanted as much leeway as possible to articulate their own labels. They wanted to be able to use racial and quasi-racial labels in subject recruitment, and to use other kinds of labels, like ethnic or linguistic, when referring to DNA sequences. They also wanted to use racial,quasi-racial, or even nationalistic labels in reporting if their research subjects wanted them to do so. This freedom enabled them to align their reporting with their subjects’ self-determined political labels, for example, using the participants’ term “African American” instead of “East” or “West African.” They needed labeling to be ambiguous and flexible, from the earliest stages of recruitment to the latest stages of publication, so they could maintain their authority over the research process. As a result, they allowed for slippages in labeling even when those slippages seemed contradictory.

As long as genetic sampling and reporting are tagged to OMB Race, we will continue to see race in terms of DNA differences that don’t exist—and continue to miss how and why race, though it has no basis in our genes, remains painfully real.

Talking with these scientists more recently, I have come to sympathize with their struggles as researchers walking a tightrope plaited with strands of population categorization, political representation, and interpersonal respect. But I have also concluded that label slippage confuses the public about the meaning of race and can introduce misinformation that fuels existing racism. There are many horrifying examples of the harm caused by misinterpreting genomic science. In 2022 a 19 year old in upstate New York, named Payton Gendron, cited genomic research in the manifesto he posted to Discord and Google, before he live-streamed himself killing 10 and wounding three Black shoppers at a Tops Friendly supermarket in Buffalo. He had misinterpreted study findings to mean that races had different intellectual aptitudes. But there are also many more subtle examples of misinformation that endangers people of color, such as when a doctor misreads a genomic study report that suggests a racial finding where there isn’t one and then mistreats a patient accordingly. Research into physicians’ knowledge about genetics and race, as well as their prescription practices by race, shows that physicians’ misunderstandings about genetics and race hurt their ability to diagnose and treat patients of color, and poor medical outcomes widen racial health gaps.

Today’s leading genome scientists have attempted to divert our attention and resources away from old-school notions of race, and many of them have tried to get us thinking in more complicated terms. But decades out from HapMap and the 1000 Genomes Project, we are still steeped in a genetics of race. We still see research and reporting awash in what sociologist Paul Giroy calls “race-thinking” in ways that harm the very groups we intend to help.

There have been other grave but perhaps less obvious barriers to scientists’ inclusionary work. Many genomic researchers have been vocal about “Eurocentrism” and have criticized past scientists for studying Whites only. But giving people of color the chance to donate their own DNA to genomic studies, or to take part in cutting edge science, does not increase access to basic healthcare, not to mention quality healthcare. And it does nothing to prevent the daily onslaught of racism that threatens people of color and leads to poorer health outcomes.

There is harm in equating race-based research inclusion with racial equity. As scientists of color have appealed to laypeople of color to get involved with DNA research, they have inadvertently contributed to racially siloed databases on a par with the siloed collections of the major international genome projects. This reservoir of data has only enabled the systemic practice of comparing the DNA of races as if they were genetically distinct populations—Africans versus Europeans versus Asians and so on.

When the geneticist Rick Kittles, who founded the hugely successful DNA-testing company African Ancestry, says, “When I go into West Africa, people see themselves in what I do and I make sure of that,” or when HapMap’s Charles Rotimi, an eminent Nigerian-born researcher at NIH, says you need “somebody that [people] can relate to, to participate in a study like this,” we must question the endpoint of research inclusion. The scholar Alondra Nelson, who ran the White House Office of Science and Technology Policy during the Biden Administration, warned of the danger of “authentic expertise”: such expertise can be a double-edged sword if it’s used to bring the racially oppressed into an even more genetically deterministic system that does nothing to challenge the social structures that cause oppression in the first place.

Good intentions abound in genomic science, and a complex understanding of what is at stake rules the field, whose leaders are committed to racial justice and to dispelling deterministic misinformation about race. But good intentions are not enough. Complex understandings are also not enough. Scientists can “speak truth to power,” as the political rallying cry says. But as long as genetic sampling and reporting are tagged to OMB Race and common categories, bracketing and therefore lacking sociopolitical analysis, we will continue to see race in terms of DNA differences that don’t exist—and continue to miss how and why race, though it has no basis in our genes, remains painfully real. ♦

 What's Real About Race?: Untangling Science, Genetics, and Society 

Dr. Rina Bliss is an associate professor of sociology at Rutgers University. The following is adapted from her new book, 

What's Real About Race?

Eclipse

The Frontier 

Ariana Reines is an American poet, playwright, performance artist, and translator. The following is excerpted from her latest book, 

Wave of Blood

When I received my first hardbound copy of 

, fresh off the press, the Large Hadron Collider in Geneva, Switzerland, was still about a decade away from powering up. Back then, of course, no one had any inkling that a mere nine days after the collider finally turned on, in September of 2008, it would abruptly shut down. A tiny loose joint led to an electrical overload that cascaded into some of the superconducting magnets warming and a section of equipment buckling. The damage shut the machine down for about a year, but in late 2009 the Large Hadron Collider came roaring back, propelling protons at nearly light-speed in opposite directions around its 27-kilometer tunnel—among the emptiest and coldest stretches in the solar system—and guiding them into collisions at energies far beyond any previously achieved in the laboratory.

To coincide with the commissioning of the collider, I wrote a 

 op-ed summarizing the major reasons for building it: find the Higgs particle, confirm supersymmetry, provide evidence for extra dimensions of space, encounter something completely unexpected. I was careful not to give equal likelihood to each of the goals that had coaxed the world to spend billions of dollars on the collider (they are listed above in descending order of anticipated likelihood), and I also included another potential outcome: that we find nothing at all. I noted that finding nothing would rank among the most radical outcomes, as it would require some long-cherished and deeply convincing ideas to be jettisoned. But it would also be the most challenging outcome to report: an exclamation point in the headline "Collider Finds Nothing!" would coax a hurried click from physicists but surely from no one else.

As the world knows, the collider was kind to physicists and journalists alike. On July 4, 2012, at a stirring press conference at the Geneva facility, spokespersons Fabiola Gianotti and Joe Incandela were surrounded by hundreds of researchers, including an eighty-three-year-old Peter Higgs, as they officially announced the discovery of the elusive particle bearing his name. The camera covering the event caught an emotional Higgs (the person), a tear welling in his eye. Higgs wasn't the only researcher responsible for the prediction of the Higgs particle—scientists who deserve credit include François Englert (who subsequently shared the Nobel Prize with Higgs), Robert Brout, Gerald Guralnik, Carl Hagen, Tom Kibble, and no doubt others too. But Higgs's journey represents the yellowest of brick roads that theorists dream of following.

In the 1960s, Higgs and others were struggling to understand how various particles that were central to the emerging standard model of particle physics would acquire mass. The conundrum was that symmetry principles underlying the theoretical equations seemed to require the particles to be massless, much like the photon, but the data showed clearly that the particles were massive. Faced with mounting tension between theory and experiment, Higgs found common ground: if space were filled with a field, much as a sauna is filled with steam, the equations could preserve their massless symmetry while particles would pick up mass from an environmental influence—a kind of exotic friction as the particles plowed through the Higgs mist.

However beautiful our equations, however seductive our ideas, they are relevant to describing reality only when experiment establishes that they are.

Higgs realized that if his proposal were correct, this invisible space-filling field would have a visible signature: a tiny but dense "nugget" of the field would show up as a particle—the Higgs particle. And how to knock that nugget loose (more precisely, convert energy into a particle excitation of the Higgs field)? One way would be to slam protons together in energetic collisions that would thwack the Higgs field much as a belly flop thwacks water, creating a spray of particles that, according to the calculations, should contain the Higgs. Nearly a half century after Peter Higgs wrote his paper, this is indeed how the Large Hadron Collider succeeded in producing Higgs particles.

The odyssey from a puzzle pitting theory against experiment to a mathematical proposal for reconciliation and then, most importantly, to experimental data confirming the mathematics is the very odyssey theorists hold in the highest regard. However beautiful our equations, however seductive our ideas, they are relevant to describing reality only when experiment establishes that they are. The confirmation of the Higgs particle ranks among the most important modern examples of mathematics illuminating the road to reality, and it led many scientists to anticipate that the discovery of yet more particles predicted by mathematical studies, would not be far behind.

The "super" in superstring theory refers to a deep mathematical symmetry called supersymmetry. It is only the supersymmetric version of string theory that has a chance of describing our world. Supersymmetry requires a host of particles well beyond those that scientists have so far discovered. Indeed, for every particle so far revealed, supersymmetry requires a partner particle: for the electron, the predicted partner is the selectron, for the neutrino there should be the neutrino, for quarks there should be squarks. These "sparticles" are the "superpartners" of the known particles.

Although supersymmetry was developed in the framework of string theory, physicists subsequently developed a version that applies to quantum field theory, and more particularly to the phenomenally successful quantum field theory of the known particles, the standard model. The supersymmetric version of the standard model makes the same prediction of superpartner particles, which is why even non-string theorists ranked finding them as a major goal of the Large Hadron Collider. But, you might ask, without the motivation of string theory, why would physicists be at all interested in modifying the triumphant standard model to include supersymmetry?

One reason is that with supersymmetry the strengths of the electromagnetic, weak nuclear, and strong nuclear forces converge to very nearly the same value on short distance scales, an important clue toward unification. But a more basic motivation for supersymmetry is entwined with the Higgs saga. Long before the Higgs particle was detected experimentally, physicists completed calculations showing that the Higgs mass would be particularly sensitive to the quantum influences of the many other particles with which it interacted. Indeed, the quantum influences would drive the Higgs mass billions and billions of times larger than the value subsequently revealed by the Large Hadron Collider (the measured mass of the Higgs particle is about 125 times the mass of the proton). Supersymmetry offered a solution to the mismatch: the superpartner particles would influence the Higgs mass too, but according to the calculations, these new contributions would cancel those coming from ordinary particles, thwarting the push toward a far larger Higgs mass.

Over the years, many physicists deemed this role for supersymmetry deeply compelling. Many, too, were charmed by supersymmetry's mathematical structure, which naturally culminates a long history of incorporating symmetry principles into physics. I remember well the pervasive feeling back in the 1980s during my graduate school days that supersymmetry was among those ideas that were simply too beautiful to be wrong. And so it seemed just a matter of time before the superpartner particles would be produced, the problem with the Higgs mass resolved, and an intrinsic quality of string theory confirmed. Champagne bottles in physics departments the world over were poised to pop.

So, all these years later, where do we stand?

Well, more than a decade since the Large Hadron Collider successfully found the Higgs, the headline summarizing subsequent progress would indeed read "Collider Finds Nothing!" The hunt continues, as an exhaustive search for the superpartners is a long and arduous task. But what are the implications if the trend continues and the superpartner particles fail to turn up?

Most concretely, physicists will once again face the puzzle of the Higgs mass: without the cancelations provided by superpartner particles, some other mechanism must be identified to keep the Higgs mass from exploding. But of most concern to our focus here, what would the absence of superpartner particles mean for string theory?

Well, if we could conclude that string theory was ruled out, I'd be thrilled. Not thrilled that string theory was wrong, but thrilled to have definitively settled the question of string theory's relevance to describing reality. I stress this point because a scientist's close association with a theory can easily be misconstrued as a commitment to supporting the theory even in the face of damning evidence. Let me be explicit: My commitment is not to string theory, or to any other proposal for nature's deep workings. My commitment is to advancing science toward truth. If data, or in this case the absence of data, could rule out string theory, that would be a resolute truth-directed step, and that is a step I would enthusiastically take. Don't get me wrong, I would be disappointed that string theory's mathematics did not realize the theory's promise of providing a unified, predictive, and confirmed description of reality. But that sentiment would pale in comparison to the profound appreciation for learning now—not a year from now or ten years from now or twenty-five years from now—that the string theory community's time and energy needed to pivot.

Perhaps one day we will have such evidence ruling out string theory, but the failure to find supersymmetry will not be the source. The reason is one of scale. To probe smaller and smaller distances we need larger and larger energies. In string theory, the central scale is the Planck scale, which in terms of length is about a billionth of a billionth the size of an atomic nucleus, and in terms of energy is about a hundred billion billion times the mass of a proton. By contrast, at the Large Hadron Collider's highest setting, it can probe lengths only as small as a thousandth the size of an atomic nucleus, with an energy that's only as large as ten thousand times the mass of a proton. And so, to probe the Planck scale we'd need an accelerator about a million billion times more powerful than the Large Hadron Collider.

If we had such a Planckian-scale collider, and if string theory is a correct theory of nature, supersymmetry would manifest in the data. But with today's coarse technology (coarse compared to the Planck scale) the supersymmetric quality of string theory can easily be obscured, much as the quantum qualities of the atomic world are obscured on the comparatively coarse scales of everyday life. Concretely, it might be that the superpartner particles exist but their masses lie well beyond the collider's reach, explaining why we've not detected them.

This is not a new realization. Since the earliest research on supersymmetry, theorists recognized that the fundamental equations did not specify the mass of the superpartner particles, and so there was always a chance that the Large Hadron Collider would lack the power to produce them.

Although I and many colleagues considered that chance to be small, there were theorists at that time who emphasized that string theory seems to favor superheavy superpartners, far too massive for the Large Hadron Collider or even any remotely realistic next-generation colliders to produce. It is worth spending a moment to appreciate their reasoning, especially now that the data are tipping things in their favor.

—Calabi-Yau shapes—share the property that they keep focus on supersymmetry, preventing it from being obscured as we examine the theory's implications at energies well below the Planck scale. In fact, in the original research paper that introduced Calabi-Yau shapes into string theory, the authors required that the extra dimensions protect supersymmetry, ensuring that their tiny geometry thins the quantum fog that would otherwise shroud the superpartners, and with that stipulation the mathematics led them to Calabi-Yau shapes.

But there are a great many other possibilities beyond Calabi-Yau shapes that string theory can happily use (that is, shapes that solve the equations of string theory) and such shapes do not protect the supersymmetric quality from being obscured. For these choices of the extra dimensions, string theory does not predict that superpartner particles will be within reach of the Large Hadron Collider, or for that matter any collider we could build in the foreseeable future. What's more, there are a great many more shapes that obscure supersymmetry than there are those that protect it. In the past, researchers (like me) who were deeply impressed by the mathematical beauty of supersymmetry, its capacity to address the puzzle with the Higgs mass, its natural unification of force strengths, its ability to simplify horrendously difficult calculations through justifiable approximations, and even its compelling proposals for dark matter were reluctant to study anything but the case of unobscured supersymmetry. But with no evidence for superpartners forthcoming from the Large Hadron Collider, this attitude is changing and researchers have been broadening their studies to include the much larger class of shapes that do not preserve supersymmetry. So, rather than ruling string theory out, the failure to find superpartners is instead shifting various research agendas within string theory itself.

Pulling back from the details, the challenge these developments underscore is that string theory does not make specific, unambiguous predictions that can be tested with current technology. Many of us had hoped that finding the superpartner particles would be the first in a series of breakthroughs that would, discovery by discovery, walk beyond the physics of the standard model and inch closer to string theory. But the goal of finding the superpartners was always a well-motivated hope and not a sharp prediction. Without equations that yield definitive values for the masses of the superpartners, there's ample opportunity for them to be too hefty for the reach of today's colliders and, more than likely, those of tomorrow.

To be sure, if colliders could reach nearly Planck-scale energies, we'd be in a very different situation, as direct probes of string physics would be possible. We would still need to understand the theory with greater depth to make detailed comparisons between calculations and data, but in that imagined setting experiment would guide theorizing much as it has across a significant stretch of the history of physics. Coming back to the reality of today's technology, at a remove of fifteen orders of magnitude from the Planck scale, such direct experimental contact is unlikely.

 Let me be explicit: My commitment is not to string theory, or to any other proposal for nature’s deep workings. My commitment is to advancing science toward truth.

Does the lack of testable particle-physics predictions mean that string theory belongs to the realm of metaphysics? Detractors of string theory have argued, some with an oddly overheated zealotry, that the answer is yes. I find such assessments of little value. Any approach to quantum gravity, string theory or otherwise, will have core physics that is directly relevant to the Planck scale, and because this scale is so far beyond our technological reach, developing experimental tests will be extremely challenging. Such is the nature of the most ambitious theoretical research that walks along the very edge of knowledge. It surely does not mean the research fails to qualify as physics and should be abandoned.

But without experimental contact, how should we judge string theory?

We should use the very approach followed by those with the most on the line: young scientists deciding on their research careers as well as mature investigators striving to advance knowledge. As a matter of course, even without a formal assessment, these researchers are constantly evaluating the field's progress and achievements. And over the years, such evaluations have convinced some scientists that the advance toward experiment was too slow for their research expectations, and so they have left the field.

But others, indeed so many others that string theory has been berated for attracting too many of the highest-caliber scientists, have found that the pace of new theoretical discoveries and novel physical insights is so rapid and thrilling that they are propelled onward with vigor and excitement.

The point is, there is no right or wrong here. It is a matter of personal scientific taste. Those who want to work on projects that have a close and ongoing dialogue with experimental data should pass by string theory and focus their energies on other research fields. Those who want to explore unsolved problems at the interface of our deepest physical theories-quantum mechanics and general relativity-should focus on string theory (or any of the competing approaches). Everyone else should respect these choices. The best and brightest of our researchers deserve free rein in their careful deliberations regarding where to invest their talents.

In making such choices, some young researchers have nevertheless asked me when I expect string theory to confront data in a meaningful way. In the earlier days of string theory, my answer echoed the sentiment I articulate above. Namely, we all root for experimental contact, but as there are no crystal balls, researchers need to decide for themselves whether they can happily go forward even if such contact should fail to materialize during their productive years. My answer has since changed. I still note how important the question of experimental contact is, but I also note that a stunning breakthrough has shifted the character of the question. I will describe the result in more detail shortly, but here's the elevator pitch: We now have powerful evidence that—shockingly—string theory and quantum field theory are actually different languages for expressing one and the same physics. In consequence, the experimental luster of quantum field theory casts a newfound experimental glow on string theory. Make no mistake, to establish string theory experimentally we need to confirm a definitive string theoretic prediction. But the unexpected equivalence between string theory and the most rigorously tested framework in the history of science quantum field theory is strong evidence that by working on string theory we are pursuing physics, not metaphysics. ♦

Brian Greene is world-renowned for his groundbreaking discoveries in the field of superstring theory, including the co-discovery of mirror symmetry and the discovery of spatial topology change. He is the director of Columbia’s Center for Theoretical Physics.

The Elegant Universe

In 1960, Ella Fitzgerald was at the height of her career, widely regarded as among the best jazz singers in the world. An experienced performer by any measure, she would typically perform 45 weeks a year. On Saturday, February 13, 1960, Lady Ella took the stage at Deutschlandhalle in Berlin in front of 12,000 fans. After singing a repertoire of popular songs from memory, including “Misty,” “The Lady Is a Tramp,” and “Summertime,” she and the band began “Mack the Knife,” first made popular by her collaborator Louis Armstrong five years earlier. Although many might not have seen the show it came from, 

, the audience knew the song well—­it had been a number 1 hit for Bobby Darin just a year before—and they cheered as soon as they heard the first line, “Oh the shark has pearly teeth, dear . . .”

After the third chorus, about a minute and a half in, Ella forgets the words. Without losing a beat, or her composure, she continues to sing perfectly in time: “Ah, what’s the next chorus, to this song now? This is the one now, I don’t know . . .” She continues improvising lyrics, occasionally inserting a remembered word or two from the song. When the next chorus comes around, still stymied, she riffs on the song’s history by referencing Darin’s and Armstrong’s versions, then self-deprecatingly sings that she’s “making a wreck of ‘Mack the Knife.’ ” The band keeps playing and after modulating up a half step, a new chorus starts. Having now made up words to two entire choruses on the spot while never losing the rhyme scheme, she begins to scat while imitating Louis Armstrong. The audience goes wild.

In the history of live performance, this stands as one of the most mesmerizing, thrilling demonstrations of mastery. And what is mastery if not the ability to deal with the unexpected as though it was expected? To take an error and turn it into something better than if there had been no error at all? This level of mastery requires deep memory for the tools of one’s craft, arrived at through thousands of hours of practice, memorization of procedures, facts, and conventions, until one’s art or craft reaches a state of automaticity, what some call the flow state.

We witnessed this type of mastery in a wholly different domain with “Sully” Sullenberger, the pilot who improvised a safe recovery of US Airways flight 1549 in 2009 after it lost power in both engines over New York. Sullenberger describes what went through his mind, and his words could equally apply to Ella’s extraordinary performance. “Because I had learned my craft so well . . . I knew my profession so intimately, I could set clear priorities, and so I chose the highest priority items. And then I had the discipline to ignore everything I did not have time to do as being only distractions and potential detriments to performance.” Landing the plane required that he not think deliberately so much as act out of training and instinct, on automatic pilot as it were—the flow state. Without memory, there can be no flow. But memory is not an all-or­-nothing entity. It flows in bits and pieces; it stops and starts and sputters and spurts. Our left cerebral hemisphere then stitches the pieces together with what it thinks are plausible inferences to fill in the gaps.

Although there was less at stake in Berlin that day than on the Hudson, Ella exhibited the same kind of presence of mind and mastery as Sully did—she prioritized and didn’t panic. Ella’s highest priority was that the show must go on, and she ignored everything nonessential. Getting the words exactly right was far less important than keeping it swingin’ with the familiar melody and rhythms.

When we listen to that magical recording, we hear that Ella has at her disposal a number of cues to the nature of the song—her memory for “Mack the Knife” has not been completely slashed. Her memory for the melody and rhythm are intact and precise. We hear her playing with the beat, as she’s done throughout the song so far, using the rhythmic technique of swing that propels each phrase into the next in a long­short, long-short rhythm; she creates groove, even when forgetting the lyrics. The next line is supposed to be “There’s a tugboat, down by the river, don’t you know?” Do you notice what Ella did? She remembered the last word of the line: 

. She also remembered, or reconstructed, the internal rhyme of lyricist Marc Blitzstein, with the long o- sound of 

 when she sings “I don’t know.” Ella improvises her way into a self-deprecating last line that ends with the name of the song, just as her previous chorus did. She then skips to her memory of the final chorus, where the lyrics name-check characters from the opera: Jenny Diver, Sukey Tawdry, and Lucy Brown (Louis Armstrong added Lotte Lenya, a nod to one of the original leads in the show in both Germany and the United States, and wife of composer Kurt Weill).

Music—even more so than language—is a highly structured medium, meaning that the structure itself can help to scaffold one’s memories.

Ella’s stunning ad hoc performance earned her a Grammy award and was so admired that when Frank Sinatra sang “Mack the Knife” with the Quincy Jones Big Band in 1984, he incorporated some of Ella’s Berlin lyrics into his version, adding her name to Bobby Darin’s and Louis Armstrong’s in the list of singers who had previously covered the song. (Ella herself reprised pieces of the improvisation during a return to Berlin in 1962.)

As the seldom-sung final stanza of “Mack the Knife” goes,

There are some who are in darkness, and the others are in light
And you see the ones in brightness. Those in darkness drop from sight.

Ella was the bright light, and her performance of forgetting stands as one of the great monuments to memory and forgetting in the history of American music. The truth is that memory and forgetting are forever entwined. Ella retained an exquisite memory for the compositional structure, rhyme scheme, melody, the underlying harmony, accent structure, phrasing, and rhythms of the song. She had intact memory for the song’s history, who had sung it before, and the particular timbre of Louis Armstrong’s voice.

Most of us, of course, don’t possess the kind of mind—or voice—that Ella Fitzgerald did. But we all possess neural networks that represent the music we’ve heard, and these form vital windows for neuroscientists into how we build and access memories in general. The musical circuits in the brain contain potent clues as to how and why music can be an effective tool in treating injury, disease, and a range of mental and physical ills ranging from PTSD and depression to Parkinson’s and Alzheimer’s.

Our memory is largely governed by a brain structure called the hippocampus, which is shaped like a seahorse. It’s found in both halves of the brain, deep down inside, and it arranges the storage of short- and long-­term memory, including the connection of certain sensations and emotions to those memories. I’ve come to believe that memories aren’t actually 

 in the hippocampus the way you might store a book on a shelf. In the library of the brain, the hippocampus is the card catalog that tells you what shelf the memory is on, in which wing of the library.

The hippocampus evolved in humans and other mammals to help us find things: Where’s the water? Where’s the food? Where’s the shelter? (Who let the dogs out?) Memory for 

 things are is extremely important to secure food and shelter. The hippocampus evolved for 

, not for remembering things like your PIN number or the lyrics to a song, but we use it for those tasks anyway. In just the last five years or so we’ve learned that the best way to improve your general memory is to exercise your geonavigation skills because they make the hippo­campus function better, regardless of what type of information you are wanting to store in it. Go for a walk in a place you’ve never been! Especially on an uneven surface, where you have to negotiate obstacles like tree roots or holes. Or drive to a place you haven’t been before. If you’re not in a hurry, turn off the GPS in your car. All of this strengthens the functioning of the hippocampus. As does music.

Memory serves many disparate functions. Although it feels as though it is a single, unified faculty, it is a basket full of separately evolved capabilities. It’s certainly helping us with much more than spatial geonavigation. Memory tells us what foods have poisoned us or others, which people and animals are allies, foes, predators, or prey. Without memory, we could not have language, for we would not remember what words mean or how grammatical structure conveys their meaning.

The different kinds of memory systems humans have are sensory memory, procedural memory, semantic memory, episodic memory, geographic/spatial memory, and autobiographical memory. Sensory memory includes the afterimage you may have beneath your eyelids after seeing something, or the echo in your mind’s ear after you’ve heard something. Procedural memory, what we often call motor memory, keeps track of things like how to tie our shoes, how to use tools, how to drive a car, or brush our teeth.

Memory for specific events, or episodes, is called episodic memory, and memory for facts and general knowledge is called semantic memory. A quick rule of thumb is that if you remember 

 you experienced something, that is episodic. If you only remember the thing itself, it is probably semantic. Our semantic memory system is the storehouse for remembering everyday objects, historical events, and cultural practices—­things like 

. Extending the rule of thumb, if you know something but you 

 have a specific recollection of learning it, it is likely a semantic memory. Of course there are cases in which they blend: I remember learning my times tables by practicing them on my walk to school; I remember when I learned the name of the album 

 because I was over at my friend Glen McClish’s house and his older sister played the title cut on her JCPenney record player. The term “semantic” in this context comes from the Greek word “semantikos,” which means “significant.” The idea behind the term is that semantic memory stores the significant or meaningful information that we have acquired about the world around us, and it is thought to underlie our ability to reason, communicate, and understand language.

Autobiographical memory is the most intimate form of memory; it is necessary for our sense of self. 

I played little league softball and I was the centerfielder. I honeymooned in Hawaii. I know how to drive a manual transmission.

 These combine your personal, episodic history and other general self-knowledge: 

Am I someone who likes vanilla ice cream or chocolate? Am I an early bird or a night owl? What do I like to do in my spare time? Who were the great loves of my life?

 This autobiographical memory is separate from episodic memory. Like episodic memory, it indexes events that you were a part of, but it indexes much more: the memories of the things you did and thought, insights, places you’ve been, your political views, your values and morals—all the things that make you 

These different memory systems (geographic/spatial, sensory, procedural, episodic, semantic, and autobiographical) are subject to loss individually as the result of injury, disease, or trauma. The nature of memory, however, is that the different systems often provide access points to one another, cross-referencing and cross-correlating. Even autobiographical memory, which draws on both episodic and semantic memory, can be separately impaired; that is, dissociated from the other forms of memory. President Reagan, before he was diagnosed with Alzheimer’s, but probably suffering from it already, famously confounded an episode (a movie he acted in) with his autobiographical memory—he thought that the things that happened to the fictional character happened to the nonfictional him.

Memory is the heart of who we are, and the very private sense of what it is like to be us. Inextricably linked to memory formation are emotion and attention. Not everything we experience makes it into memory. If you are really paying attention to something, it’s much more likely to be encoded. Often the unconscious is deciding: What does this experience mean to me? What might I learn from this? How can I use this later? Say I walk into a house that I’m thinking of buying: I’m going to notice different things than if I’m thinking of robbing it. As a buyer I don’t care about the expensive coin collection in the glass case; I care about the leaky roof. Context profoundly influences what gets stored in memory! Also, we tend to remember those things that carry the biggest emotional wallop. This makes evolutionary sense: an emotional event, such as finding water when you’re lost and thirsty, or seeing a family member eat a plant that poisons them—needs to be encoded for survival.

A popular metaphor holds that memory is like a digital recording of our lives—when we want to recall something, we find the file in our memory banks and hit play. And we can fast forward, rewind, jump ahead, play in slow motion—our memory is scan­nable, and its “playback” is under our control. But this metaphor is not very good, because memories are subject to distortion or change over time, making it difficult to rely on what we pull out of our mental attic.

In reality, memory is more like film that has been edited and doctored, with entirely new scenes inserted, old ones rewritten with new characters, backgrounds, and dialogue, and some distorting lenses applied. Our recollections can be influenced by a range of external factors such as context, mood, and expectations, causing them to become altered. This can result in different people having different memories of the same event (in the book I describe how three Beatles and George Martin all had entirely different—and incompatible recollections—of critical Beatles sessions). Over time, our own memories of an event might change, sometimes drastically, as we recontextualize the experiences—we do this without conscious awareness and can’t help ourselves. These intruding distortions can also affect retrieval as we search our memory banks. If you’re searching your memory for that time you had shrimp scampi with your old high school friend Jim Ferguson, you may not find it because you and Jim never 

 shrimp scampi—you only talked about it—and this detail is somehow lost, merged, or rewritten. The maddening thing about all of this is that we are 

. This often is not true; psychologist Elizabeth Loftus has shown how easily and readily false memories can form.

Understanding the neuroanatomy of the different kinds of memory is crucial for working out how music therapy and music interventions can and do work. Memories of the emotional and autobiographical features of music—

 is the album she and I listened to in bed

—are prone to distortion like any memory. But the 

 components of music hold a privileged position: they tend to be more accurate than other memories, even for nonmusicians. Memory for the absolute pitches of songs that we know well are preserved in memory with great precision; the same is true for tempo, timbre, melody, harmony, and spatial location (such as, 

the cellos are supposed to be on my right

). Memory for the structure of the lyrics, if not each and every word, is also well preserved. We remember, with astonishing accuracy, the rhythms and notes that lyrics are attached to, the accent structure, the rhyme scheme, the pauses. Even if we only know a song fairly well, it’s likely we’ve encoded enough of this componential information that we can take a good guess at what the missing words are.

Why this privileged position for music? In general, it is easier to remember information when there is some sort of organization scheme inherent in the material. The most successful mnemonic devices are ones that contain a structure predictable enough that we can learn it (ideally, just through passive exposure, as we do with our native language). And music—even more so than language—is a highly structured medium, meaning that the structure itself can help to scaffold one’s memories. Because of this structure, we don’t need to remember every single musical detail in order to reconstruct our musical memory. Any one of the individual component attributes of rhythm, melody, timbre, lyrics, and phrase structure can help us to remember others, allowing us to make plausible inferences about what comes next.

Somewhere over the rainbow, skies are blue
And the dreams that you dare to dream really do __________

You may have forgotten what comes next, or you may never have heard the song and so never knew. But the mutually reinforcing constraints of rhythm, accent structure, meter, melody, and rhyme (it probably rhymes with 

) constrain the possible completions. How would you finish this? 

? Those might work in a Weird Al Yankovic song, but here they seem out of place. Really the only thing that fits is what Yip Harburg wrote for that lyric: 

. The lyric is memorable because structure and semantics—logic—reinforce it.

Musical memory is unique in that it combines procedural memory (motor memory) with auditory memory and a special kind of semantic memory, memory for the structural rules that hold everything together. Because there are so many redundancies in musical memories, they are among the most robust in our lives, surviving even advanced Alzheimer’s disease.

But musicianship requires much more precision; a multifactorial network of brain regions must cooperate. Ella was lucky in that she only lost the words. In other cases, the sounds can remain in our brains as auditory memory, but we have difficulty getting them out. I learned about this first-hand, in recent years, from my friend Rosanne Cash.

Once you’ve heard those same compositions hundreds of times, each time writing a memory trace into your brain, you have essentially rehearsed the song, as a musician might, without even knowing it.

In 2008, the New York Academy of Sciences invited Rosanne and me to perform music together and talk about what goes into creating music, both from the musician-composer side and from the scientific side. Rosanne had undergone brain surgery that affected her musicianship a year before. Rosanne is a rare jewel among marquee performers. She is more focused on the experience of those around her than on her own experience—she directs her attention to the crew, the sound engineer, the stagehands, the other musicians. She is the anti-diva. Knowing that I’d be flying down from Montreal in the winter—not a good time to bring an instrument on a plane—Rosanne offered to bring me one of her guitars to play. We had a wonderful time. We had played together informally at her house, but this was the first time we had performed in public. It was so completely natural and comfortable, it felt like we’d been doing it for years. The event led to a series of similar engagements during which we talk about music and the brain, play a few songs, talk some more, and play a few more songs. It’s a novel and intimate format; the audiences say that they feel like they’re eavesdropping on a pair of friends having dinner at the next table in a restaurant.

Prior to her surgery, Rosanne had been experiencing headaches for as long as she could remember. As she got older, they became debilitating. “Once, I even dropped to my knees, the pain was so intense,” she recalls. “But a lot of times, singing, playing music myself, I would move out of the headache. It would just dissolve. That’s an interesting thing about music. You know, people say it’s very healing. It is very healing, literally.” After ten years of misdiagnoses, she underwent an MRI that showed she had a “Chiari malformation,” a rare abnormality I had to look up, that caused a bit of cerebellar tissue to slide down into the spinal cavity in the neck, pushing against the brain stem, “the geographical equivalent of starting in Vancouver and wandering down to Houston,” Rosanne said. The only solution was neurosurgery. When Rosanne arrived in pre-op, the nurse asked her what she was there for. “I’m having a decompression craniectomy and laminectomy for Chiari 1 and syringomyelia,” she said. Rosanne knew far more about it than I did.

The cerebellum is responsible for the exquisite orchestration of movement, whether it’s lifting one’s leg up a stair, opening a jar of jam, or playing a musical instrument. Any disturbance there, no matter how slight, can have outsized consequences for movements from large to small to minuscule.

Following the surgery, Rosanne tried to play the piano again. Her cerebellum, unceremoniously poked and prodded, was having none of it. She could move her fingers just fine, but all of those precise movements and sequences that had been so carefully rehearsed over a lifetime were now lost. Undaunted, she set off on a path of cognitive and musical rehabilitation, getting out her second-grade piano books and teaching herself those pieces, one note at a time. At first it was frustrating. But gradually the dormant patterns came back to life. What had taken her decades to learn the first time around, she relearned within six months. It is an extraordinary property of memory that once you’ve learned something, even if you 

 you forgot it, you can retrain yourself and it comes back much more quickly than you think it will, given the fits and starts that characterize the early stages.

The intricate processing of music unfolds component by component, commencing from the very moment we perceive its resonating sounds. The waveform, whether it reaches our ears through live performances, speakers, or earbuds, undergoes a deconstruction process that gives rise to neural representations across three distinct dimensions: frequency, amplitude, and duration. These neural representations then traverse specialized pathways where they are transformed, gradually assuming the more familiar attributes of pitch, loudness, and rhythm. Through further specialized processing circuits, the rich world of music materializes into a mosaic of the nine dimensions that engage and shape our perception: melody, contour, harmony, timbre, meter, tempo, tactus, spatial location, and distance.

Accomplished musicians possess the capacity to construct higher-order representations encompassing chords (clusters of pitches), harmonic rhythm (progressions of chords), and phrase structure (such as the distinction between 8-bar and 12-bar blues). As these higher-order representations crystallize through repeated listenings or deliberate practice, they often coalesce into meaningful “chunks.” Chunking reduces memory load, by transforming a collection of disparate parts into a cohesive entity.