The Singularity Is Nearer: When We Merge with AI

by Ray Kurzweil

This transition is already underway, accelerated by the social changes necessitated by COVID-19. At the peak during the pandemic, up to 42 percent of Americans were working from home.[217] This experience will likely have a long-term impact on how both employees and employers think about work. In many cases the old model of nine-to-five sitting at a desk in a company office has been obsolete for years, but inertia and familiarity made it hard for society to change until the pandemic forced us to.

Another nanomaterial called black silicon has a surface composed of a vast number of atomic-scale needles smaller than the wavelength of light.[220] This nearly eliminates reflections from a cell, ensuring that more of the incoming photons create electricity. Princeton researchers have developed an alternative method of maximizing electricity by using a nanoscale mesh of gold atoms just 30 billionths of a meter thick to trap photons and increase efficiency.[221] Meanwhile, a project at MIT has created photovoltaic cells from sheets of graphene, a special form of carbon that is only one atom thick (less than a nanometer).[222]

Yet crop densities are now approaching the theoretical limit of how much food can be grown in a given outdoor area. One emerging solution is to grow multiple stacked layers of crops, referred to as vertical agriculture.[255] Vertical farms take advantage of several technologies.[256] Typically they grow crops hydroponically, meaning that instead of being grown in soil, plants are raised indoors in trays of nutrient-rich water. These trays are loaded into frames and stacked many stories high, which means that excess water from one level can trickle down to the next instead of being lost as runoff. Some vertical farms now use a new approach called aeroponics, where the water is replaced with a fine mist.[257] And instead of sunlight, special LEDs are installed to ensure that each plant gets the perfect amount of light.

Biological life is suboptimal because evolution is a collection of random processes optimized by natural selection. Thus, as evolution has “explored” the range of possible genetic traits, it has depended heavily on chance and the influence of particular environmental factors. Also, the fact that this process is gradual means that evolution can achieve a design only if all the intermediate steps toward a given feature also lead creatures to be successful in their environments. So there are surely some potential traits that would be very useful but that are inaccessible because the incremental steps needed to build them would be evolutionarily unfit. By contrast, applying intelligence (human or artificial) to biology will allow us to systematically explore the full range of genetic possibilities in search of those traits that are optimal—that is, most beneficial. This includes those inaccessible to normal evolution.

The ultimate goal is to put our destiny in our own hands, not in the metaphorical hands of fate—to live as long as we wish. But why would anyone ever choose to die? Research shows that those who take their own lives are typically in unbearable pain, whether physical or emotional.[290] While advances in medicine and neuroscience cannot prevent all of those cases, they will likely make them much rarer.

Humanity’s journey toward easier, safer, and more abundant life for all has been progressing for years, decades, centuries, and millennia. We truly have trouble imagining what life was like even a century ago, let alone before that. Our accelerating progress, with substantial gains over the past few decades and profound evolution over the next few decades, will catapult us forward in this positive direction, far beyond what we can now imagine.

a 2023 report by McKinsey, found that 63 percent of all working time in today’s developed economies is spent on tasks that could already be automated with today’s technology.[23] If adoption proceeds quickly, half of this work could be automated by 2030, while McKinsey’s midpoint scenarios forecast 2045—assuming no future AI breakthroughs. But we know AI is going to continue to progress—exponentially—until we have superhuman-level AI and fully automated, atomically precise manufacturing (controlled by AI) sometime in the 2030s.

It’s not clear whether Ned Ludd actually existed, but legend has it that he accidentally broke textile factory machinery, and any equipment damaged thereafter—either mistakenly or in protest of automation—would be blamed on Ludd.[25] When the desperate weavers formed an urban guerrilla army in 1811, they declared General Ludd their leader.[26] These Luddites, as they were known, revolted against factory owners—they first directed their violence primarily at the machines, but bloodshed soon ensued. The movement ended with the imprisonment and hanging of prominent Luddite leaders by the British government.[27] Ned Ludd was never found.

Since the start of the twenty-first century, the labor force has slightly shrunk as a proportion of the total population, but a major reason for this is that a higher percentage of Americans are now of retirement age.[67] In 1950, 8.0 percent of the US population was sixty-five or older;[68] by 2018 that had doubled to 16.0 percent, leaving relatively fewer working-age people in the economy.[69] The US Census Bureau projects—independent of any new medical breakthroughs that may be achieved in the coming decades—that over-sixty-fives will constitute 22 percent of the population by 2050.[70] If I am correct that significant life-extension technologies will become a reality by then, the proportion of senior citizens will be even higher. In absolute terms, though, the labor force itself is still growing. In 2000 the civilian labor force was estimated at 143.6 million out of a total population of 282 million, or 50.9 percent.[71] By 2022 the labor force had grown to 164 million workers out of around 332 million people, or 49.4 percent.[72]

Despite the long pattern of net job growth, some prominent economists have predicted that this time will be different. One of the leading proponents of the view that the upcoming onslaught of AI-based automation will be a net job killer has been Stanford professor Erik Brynjolfsson. He argues that, unlike previous technology-driven transitions, the latest form of automation will result in a loss of more jobs than it creates.[80] Economists who take this view see the current situation as the culmination of several successive waves of change.

The first wave is often referred to as “deskilling.”[81] For example, a driver of a horse-drawn carriage who needed extensive skills at handling and maintaining unpredictable animals was replaced by an automobile driver who required fewer such abilities. One of the main effects of deskilling is that it is easier for people to take new jobs without lengthy training. Craftsmen would have to spend years developing the wide range of skills involved in shoemaking, but once assembly-line machines took over much of this work, a person could get a job after a much shorter time learning to operate a machine. This meant that labor costs fell and shoes became more affordable, but also that low-paying jobs replaced higher-paying ones. The second wave is “upskilling.” Upskilling often follows deskilling, and introduces technologies that require more skill than what came before. For example, providing drivers with navigation technologies requires them to learn how to use electronics that were not previously part of the required skill set. Sometimes this means introducing machines that take an ever larger role in manufacturing but that require sophisticated skills to operate.

The oncoming wave, however, could be called “nonskilling.” Driverless-vehicle AI, for example, will replace human drivers altogether. As more and more tasks fall within the capabilities of AI and robotics, there will be a series of nonskilling transitions.

Although it will be technologically and economically possible for everyone to enjoy a standard of living that is high by today’s measures, whether we actually provide this support to everyone who needs it will be a political decision. By analogy, although there are occasional famines around the world today, they are not a result of insufficient food production, or because the secret to good agriculture is being kept in a few elite hands. Rather, famines usually happen because of bad governance or civil war.

What happens between now and then? In a personal dialogue I had with Daniel Kahneman, he concurred with my view that information technology has been growing and will continue to grow exponentially in price-performance and capacity and that this will ultimately encompass physical products such as clothing and food. He also agreed that we are headed toward an era of abundance that will meet our physical needs and that the primary struggle will then be to satisfy higher levels of Maslow’s hierarchy. However, he envisioned a protracted period of conflict, and even violence, between now and then. He pointed out that there will invariably be winners and losers as automation continues its impact. A driver losing his job is not going to be satisfied by the promise of humanity moving up the hierarchy of life, because he as an individual may not, in fact, be able to make that transition.

People also frequently envision unenhanced humans struggling to compete with machines, but this is a misconception. Imagining a world where humans are largely in competition with AI-powered machines is the wrong way of thinking about the future. To illustrate this, imagine a time traveler with a 2024 smartphone going back to 1924.[166] This person’s intelligence would seem truly superhuman to the people of Calvin Coolidge’s day. They could do advanced math effortlessly, translate any major language passably well, play chess better than any grandmaster, and command a whole Wikipedia’s worth of facts. To the people of 1924, it would seem obvious that the time traveler’s capabilities were radically enhanced by the phone. But to us in the 2020s it’s easy to lose this perspective. We don’t feel augmented. In a similar way, we will harness the advances of 2030 and 2040 to seamlessly augment our own capabilities—and this will feel even more natural as our brains interface directly with computers.

The first reference to nanotechnology was made by the physicist Richard Feynman (1918–1988) in his seminal 1959 lecture “There’s Plenty of Room at the Bottom,” in which he described the inevitability of creating machines at the scale of individual atoms, as well as the profound implications of doing so.[51] As Feynman said: “The principles of physics, as far as I can see, do not speak against the possibility of maneuvering things atom by atom…. It would be, in principle, possible…for a physicist to synthesize any chemical substance that the chemist writes down….

In order for nanotechnology to have an impact on large objects, it needs to have a self-replication system. The idea of how to create a self-replicating module was first formalized by legendary mathematician John von Neumann (1903–1957) in a series of lectures during the late 1940s and in a 1955 Scientific American article.[53] But the full range of his ideas was not collected and widely published until 1966, almost a decade after his death.

In the mid-1980s, engineer K. Eric Drexler founded the modern field of nanotechnology, building upon this concept from von Neumann.[55] Drexler designed an abstract machine that used atoms and molecular fragments found in ordinary substances to provide the materials for his von Neumann–style constructor, which would feature a computer able to direct the placement of atoms.[56] Drexler’s “assembler” could essentially make anything in the world, so long as its structure is atomically stable. It is this flexibility and generalizability that distinguishes the molecular mechanosynthesis approach Drexler pioneered from biology-based approaches, which would assemble objects at nanoscales but be much more limited in the designs and materials available.

In the context of self-replicating nanobots, this would enable the massive coordination required to achieve macroscopic results. The control system would be similar to the computer instruction architecture called SIMD (single instruction, multiple data), meaning that a single computational unit would read the program instructions and then transmit them to the trillions of molecular-size assemblers (each with its own simple computer) simultaneously.[63]

The nanotech revolution will bring this transformative shift into the physical world. In 2023 the value of physical products comes from many sources, especially raw materials, manufacturing labor, factory machine time, energy costs, and transportation. But convergent innovations will be dramatically reducing most of those costs in the coming decades. Raw materials will be cheaper to extract or synthesize with automation, robotics will replace expensive human labor, high-priced factory machines will themselves become cheaper, energy prices will fall due to better solar photovoltaics and energy storage (and eventually fusion), and autonomous electric vehicles will drive down transportation costs. As all these components of value become less expensive, the proportional value of the information contained in products will increase. Indeed, we are already going in that direction, as the “information content” of most products is rapidly increasing—and will ultimately get very close to 100 percent of their value.

The 2030s will usher in the third phase of life extension, which will be to use nanotechnology to overcome the limitations of our biological organs altogether. As we enter this phase, we’ll greatly extend our lives, allowing people to greatly transcend the normal human limit of 120 years.[94]

Over the past decade, scientists and investors have started giving much more serious attention to finding out why. One of the leading researchers in this field is biogerontologist Aubrey de Grey, founder of the LEV (Longevity Escape Velocity) foundation.[98] As de Grey explains, aging is like the wear on the engine of an automobile—it is damage that accumulates as a result of the system’s normal operation. In the human body’s case, that damage largely comes from a combination of cellular metabolism (using energy to stay alive) and cellular reproduction (mechanisms for self-replication). Metabolism creates waste in and around cells and damages structures through oxidation (much like the rusting of a car!). When we’re young, our bodies are able to remove this waste and repair the damage efficiently. But as we get older, most of our cells reproduce over and over, and errors accumulate. Eventually the damage starts piling up faster than the body can fix it.

Instead, longevity researchers argue, the only solution is to cure aging itself. The SENS (Strategies for Engineered Negligible Senescence) Research Foundation has proposed a detailed research agenda for how to do this (even though it will certainly take decades to fully accomplish).[99]

And we don’t need to wait until these technologies are fully mature in order to benefit. If you can live long enough for anti-aging research to start adding at least one year to your remaining life expectancy annually, that will buy enough time for nanomedicine to cure any remaining facets of aging. This is longevity escape velocity.[100] This is why there is sound logic behind Aubrey de Grey’s sensational declaration that the first person to live to 1,000 years has likely already been born.

People become upset when they hear of an individual whose life has been cut short by a disease, yet when confronted with the possibility of generally extending all human life, they react negatively. “Life is too difficult to contemplate going on indefinitely” is a common response. But people generally do not want to end their lives at any point unless they are in enormous pain—physically, mentally, or spiritually.

That is, extending human life would also mean vastly improving it.

But nanobots won’t be limited to preserving the body’s normal function. They could also be used to adjust concentrations of various substances in our blood to levels more optimal than what would normally occur in the body. Hormones could be tweaked to give us more energy and focus, or speed up the body’s natural healing and repair.

Part of why cancer can be so hard to eliminate is because each cancer cell has the ability to self-replicate, so every single cell has to be removed.[113] Although the immune system is often able to control the very earliest phases of cancerous cell division, once a tumor does get established, it can develop resistance to the body’s immune cells. At that point, even if a treatment destroys most of the cancer cells, the survivors can start growing new tumors. A subpopulation known as cancer stem cells are especially likely to be these dangerous survivors.[114]

In the 2040s and 2050s, we will rebuild our bodies and brains to go vastly beyond what our biology is capable of, including their backup and survival. As nanotechnology takes off, we will be able to produce an optimized body at will: we’ll be able to run much faster and longer, swim and breathe under the ocean like fish, and even give ourselves working wings if we want them. We will think millions of times faster, but most importantly, we will not be dependent on the survival of any of our bodies for our selves to survive.

I do think we also need to take seriously the misguided and increasingly strident Luddite voices that advocate broad relinquishment of technological progress to avoid the genuine dangers of genetics, nanotechnology, and robotics (GNR).[80]

When people are presented with the prospect of radical life extension, two objections are quickly raised. The first is the probability of running out of material resources to support an expanding biological population. We frequently hear that we are running out of energy, clean water, housing, land, and the other resources we need to support a growing population, and that this problem will only be exacerbated when the death rate starts to plummet. But as I articulated in chapter 4, as we begin to optimize our use of the earth’s resources, we’ll find they are thousands of times greater than we require. For example, we have nearly ten thousand times the sunlight we need to theoretically meet all of our current energy needs.[83] The second objection to radical life extension is that we will become profoundly bored doing the same things over and over again for centuries. But in the 2020s we will have virtual and augmented reality delivered in very compact external devices, and in the 2030s we will have VR and AR connected directly to our nervous systems by nanobots feeding signals to our senses. We will thereby have radical life expansion in addition to radical life extension. We will inhabit vast virtual and augmented realities limited only by our imagination—which itself will be expanded. Even if we lived hundreds of years, we would not exhaust all the knowledge there is to gain, and all the culture there is to consume.

Cassandra: Right. And that is why I am still concerned at what could be a one-decade delay in getting a brain extender to work, given the extraordinary challenge of putting a device with millions of connections inside our skulls. I can accept the feasibility of all kinds of changes outside our bodies, including VR, but that is not the same as actually extending our neocortex. Ray: That was the concern that Daniel Kahneman expressed, and he was also concerned about the potential for violence between people who lost their jobs and others. Cassandra: By “others” do you mean the computers, since it will be the computers that are superior to humans in every skill? Ray: Not the computers, as we will be dependent on the computers for our well-being, but rather humans who may be perceived as using AI to expand their own wealth and power at the expense of displaced workers.