Get Smarter

Image: Anastasia Vasilakis

Seventy-four thousand years ago, humanity nearly went extinct. A super-volcano at what’s now Lake Toba, in Sumatra, erupted with a strength more than a thousand times that of Mount St. Helens in 1980. Some 800 cubic kilometers of ash filled the skies of the Northern Hemisphere, lowering global temperatures and pushing a climate already on the verge of an ice age over the edge. Some scientists speculate that as the Earth went into a deep freeze, the population of Homo sapiens may have dropped to as low as a few thousand families.

The Mount Toba incident, although unprecedented in magnitude, was part of a broad pattern. For a period of 2 million years, ending with the last ice age around 10,000 B.C., the Earth experienced a series of convulsive glacial events. This rapid-fire climate change meant that humans couldn’t rely on consistent patterns to know which animals to hunt, which plants to gather, or even which predators might be waiting around the corner.

How did we cope? By getting smarter. The neuro­physi­ol­ogist William Calvin argues persuasively that modern human cognition—including sophisticated language and the capacity to plan ahead—evolved in response to the demands of this long age of turbulence. According to Calvin, the reason we survived is that our brains changed to meet the challenge: we transformed the ability to target a moving animal with a thrown rock into a capability for foresight and long-term planning. In the process, we may have developed syntax and formal structure from our simple language.

Our present century may not be quite as perilous for the human race as an ice age in the aftermath of a super-volcano eruption, but the next few decades will pose enormous hurdles that go beyond the climate crisis. The end of the fossil-fuel era, the fragility of the global food web, growing population density, and the spread of pandemics, as well as the emergence of radically transformative bio- and nano­technologies—each of these threatens us with broad disruption or even devastation. And as good as our brains have become at planning ahead, we’re still biased toward looking for near-term, simple threats. Subtle, long-term risks, particularly those involving complex, global processes, remain devilishly hard for us to manage.

But here’s an optimistic scenario for you: if the next several decades are as bad as some of us fear they could be, we can respond, and survive, the way our species has done time and again: by getting smarter. But this time, we don’t have to rely solely on natural evolutionary processes to boost our intelligence. We can do it ourselves.

Most people don’t realize that this process is already under way. In fact, it’s happening all around us, across the full spectrum of how we understand intelligence. It’s visible in the hive mind of the Internet, in the powerful tools for simulation and visualization that are jump-starting new scientific disciplines, and in the development of drugs that some people (myself included) have discovered let them study harder, focus better, and stay awake longer with full clarity. So far, these augmentations have largely been outside of our bodies, but they’re very much part of who we are today: they’re physically separate from us, but we and they are becoming cognitively inseparable. And advances over the next few decades, driven by breakthroughs in genetic engineering and artificial intelligence, will make today’s technologies seem primitive. The nascent jargon of the field describes this as “ intelligence augmentation.” I prefer to think of it as “You+.”

Scientists refer to the 12,000 years or so since the last ice age as the Holocene epoch. It encompasses the rise of human civilization and our co-evolution with tools and technologies that allow us to grapple with our physical environment. But if intelligence augmentation has the kind of impact I expect, we may soon have to start thinking of ourselves as living in an entirely new era. The focus of our technological evolution would be less on how we manage and adapt to our physical world, and more on how we manage and adapt to the immense amount of knowledge we’ve created. We can call it the Nöocene epoch, from Pierre Teilhard de Chardin’s concept of the Nöosphere, a collective consciousness created by the deepening interaction of human minds. As that epoch draws closer, the world is becoming a very different place.

Of course, we’ve been augmenting our ability to think for millennia. When we developed written language, we significantly increased our functional memory and our ability to share insights and knowledge across time and space. The same thing happened with the invention of the printing press, the telegraph, and the radio. The rise of urbanization allowed a fraction of the populace to focus on more-cerebral tasks—a fraction that grew inexorably as more-complex economic and social practices demanded more knowledge work, and industrial technology reduced the demand for manual labor. And caffeine and nicotine, of course, are both classic cognitive-enhancement drugs, primitive though they may be.

With every technological step forward, though, has come anxiety about the possibility that technology harms our natural ability to think. These anxieties were given eloquent expression in these pages by Nicholas Carr, whose essay “Is Google Making Us Stupid?” (July/August 2008 Atlantic) argued that the information-dense, hyperlink-rich, spastically churning Internet medium is effectively rewiring our brains, making it harder for us to engage in deep, relaxed contemplation.

Carr’s fears about the impact of wall-to-wall connectivity on the human intellect echo cyber-theorist Linda Stone’s description of “continuous partial attention,” the modern phenomenon of having multiple activities and connections under way simultaneously. We’re becoming so accustomed to interruption that we’re starting to find focusing difficult, even when we’ve achieved a bit of quiet. It’s an induced form of ADD—a “continuous partial attention-deficit disorder,” if you will.

There’s also just more information out there—because unlike with previous information media, with the Internet, creating material is nearly as easy as consuming it. And it’s easy to mistake more voices for more noise. In reality, though, the proliferation of diverse voices may actually improve our overall ability to think. In Everything Bad Is Good for You, Steven Johnson argues that the increasing complexity and range of media we engage with have, over the past century, made us smarter, rather than dumber, by providing a form of cognitive calisthenics. Even pulp-television shows and video games have become extraordinarily dense with detail, filled with subtle references to broader subjects, and more open to interactive engagement. They reward the capacity to make connections and to see patterns—precisely the kinds of skills we need for managing an information glut.

Scientists describe these skills as our “fluid intelligence”—the ability to find meaning in confusion and to solve new problems, independent of acquired knowledge. Fluid intelligence doesn’t look much like the capacity to memorize and recite facts, the skills that people have traditionally associated with brainpower. But building it up may improve the capacity to think deeply that Carr and others fear we’re losing for good. And we shouldn’t let the stresses associated with a transition to a new era blind us to that era’s astonishing potential. We swim in an ocean of data, accessible from nearly anywhere, generated by billions of devices. We’re only beginning to explore what we can do with this knowledge-at-a-touch.

Moreover, the technology-induced ADD that’s associated with this new world may be a short-term problem. The trouble isn’t that we have too much information at our fingertips, but that our tools for managing it are still in their infancy. Worries about “information overload” predate the rise of the Web (Alvin Toffler coined the phrase in 1970), and many of the technologies that Carr worries about were developed precisely to help us get some control over a flood of data and ideas. Google isn’t the problem; it’s the beginning of a solution.

In any case, there’s no going back. The information sea isn’t going to dry up, and relying on cognitive habits evolved and perfected in an era of limited information flow—and limited information access—is futile. Strengthening our fluid intelligence is the only viable approach to navigating the age of constant connectivity.

When people hear the phrase intelligence augmentation, they tend to envision people with computer chips plugged into their brains, or a genetically engineered race of post-human super-geniuses. Neither of these visions is likely to be realized, for reasons familiar to any Best Buy shopper. In a world of on­going technological acceleration, today’s cutting-edge brain implant would be tomorrow’s obsolete junk—and good luck if the protocols change or you’re on the wrong side of a “format war” (anyone want a Betamax implant?). And then there’s the question of stability: Would you want a chip in your head made by the same folks that made your cell phone, or your PC?

Likewise, the safe modification of human genetics is still years away. And even after genetic modification of adult neurobiology becomes possible, the science will remain in flux; our understanding of how augmentation works, and what kinds of genetic modifications are possible, would still change rapidly. As with digital implants, the brain modification you might undergo one week could become obsolete the next. Who would want a 2025-vintage brain when you’re competing against hotshots with Model 2026?

Yet in one sense, the age of the cyborg and the super-genius has already arrived. It just involves external information and communication devices instead of implants and genetic modification. The bioethicist James Hughes of Trinity College refers to all of this as “exo­cortical technology,” but you can just think of it as “stuff you already own.” Increasingly, we buttress our cognitive functions with our computing systems, no matter that the connections are mediated by simple typing and pointing. These tools enable our brains to do things that would once have been almost unimaginable:

• powerful simulations and massive data sets allow physicists to visualize, understand, and debate models of an 11‑dimension universe;

• real-time data from satellites, global environmental databases, and high-resolution models allow geophysicists to recognize the subtle signs of long-term changes to the planet;

• cross-connected scheduling systems allow anyone to assemble, with a few clicks, a complex, multimodal travel itinerary that would have taken a human travel agent days to create.

If that last example sounds prosaic, it simply reflects how embedded these kinds of augmentation have become. Not much more than a decade ago, such a tool was outrageously impressive—and it destroyed the travel-agent industry.

That industry won’t be the last one to go. Any occupation requiring pattern-matching and the ability to find obscure connections will quickly morph from the domain of experts to that of ordinary people whose intelligence has been augmented by cheap digital tools. Humans won’t be taken out of the loop—in fact, many, many more humans will have the capacity to do something that was once limited to a hermetic priesthood. Intelligence augmentation decreases the need for specialization and increases participatory complexity.

As the digital systems we rely upon become faster, more sophisticated, and (with the usual hiccups) more capable, we’re becoming more sophisticated and capable too. It’s a form of co-evolution: we learn to adapt our thinking and expectations to these digital systems, even as the system designs become more complex and powerful to meet more of our needs—and eventually come to adapt to us.

Consider the Twitter phenomenon, which went from nearly invisible to nearly ubiquitous (at least among the online crowd) in early 2007. During busy periods, the user can easily be overwhelmed by the volume of incoming messages, most of which are of only passing interest. But there is a tiny minority of truly valuable posts. (Sometimes they have extreme value, as they did during the October 2007 wildfires in California and the November 2008 terrorist attacks in Mumbai.) At present, however, finding the most-useful bits requires wading through messages like “My kitty sneezed!” and “I hate this taco!”

But imagine if social tools like Twitter had a way to learn what kinds of messages you pay attention to, and which ones you discard. Over time, the messages that you don’t really care about might start to fade in the display, while the ones that you do want to see could get brighter. Such attention filters—or focus assistants—are likely to become important parts of how we handle our daily lives. We’ll move from a world of “continuous partial attention” to one we might call “continuous augmented awareness.”

As processor power increases, tools like Twitter may be able to draw on the complex simulations and massive data sets that have unleashed a revolution in science. They could become individualized systems that augment our capacity for planning and foresight, letting us play “what-if” with our life choices: where to live, what to study, maybe even where to go for dinner. Initially crude and clumsy, such a system would get better with more data and more experience; just as important, we’d get better at asking questions. These systems, perhaps linked to the cameras and microphones in our mobile devices, would eventually be able to pay attention to what we’re doing, and to our habits and language quirks, and learn to interpret our sometimes ambiguous desires. With enough time and complexity, they would be able to make useful suggestions without explicit prompting.

And such systems won’t be working for us alone. Intelligence has a strong social component; for example, we already provide crude cooperative information-filtering for each other. In time, our interactions through the use of such intimate technologies could dovetail with our use of collaborative knowledge systems (such as Wikipedia), to help us not just to build better data sets, but to filter them with greater precision. As our capacity to provide that filter gets faster and richer, it increasingly becomes something akin to collaborative intuition—in which everyone is effectively augmenting everyone else.

In pharmacology, too, the future is already here. One of the most prominent examples is a drug called modafinil. Developed in the 1970s, modafinil—sold in the U.S. under the brand name Provigil—appeared on the cultural radar in the late 1990s, when the American military began to test it for long-haul pilots. Extended use of modafinil can keep a person awake and alert for well over 32 hours on end, with only a full night’s sleep required to get back to a normal schedule.

While it is FDA-approved only for a few sleep disorders, like narcolepsy and sleep apnea, doctors increasingly prescribe it to those suffering from depression, to “shift workers” fighting fatigue, and to frequent business travelers dealing with time-zone shifts. I’m part of the latter group: like more and more professionals, I have a prescription for modafinil in order to help me overcome jet lag when I travel internationally. When I started taking the drug, I expected it to keep me awake; I didn’t expect it to make me feel smarter, but that’s exactly what happened. The change was subtle but clear, once I recognized it: within an hour of taking a standard 200-mg tablet, I was much more alert, and thinking with considerably more clarity and focus than usual. This isn’t just a subjective conclusion. A University of Cambridge study, published in 2003, concluded that modafinil confers a measurable cognitive-enhancement effect across a variety of mental tasks, including pattern recognition and spatial planning, and sharpens focus and alertness.

I’m not the only one who has taken advantage of this effect. The Silicon Valley insider webzine Tech Crunch reported in July 2008 that some entrepreneurs now see modafinil as an important competitive tool. The tone of the piece was judgmental, but the implication was clear: everybody’s doing it, and if you’re not, you’re probably falling behind.

This is one way a world of intelligence augmentation emerges. Little by little, people who don’t know about drugs like modafinil or don’t want to use them will face stiffer competition from the people who do. From the perspective of a culture immersed in athletic doping wars, the use of such drugs may seem like cheating. From the perspective of those who find that they’re much more productive using this form of enhancement, it’s no more cheating than getting a faster computer or a better education.

Modafinil isn’t the only example; on college campuses, the use of ADD drugs (such as Ritalin and Adderall) as study aids has become almost ubiquitous. But these enhancements are primitive. As the science improves, we could see other kinds of cognitive-modification drugs that boost recall, brain plasticity, even empathy and emotional intelligence. They would start as therapeutic treatments, but end up being used to make us “better than normal.” Eventually, some of these may become over-the-counter products at your local pharmacy, or in the juice and snack aisles at the supermarket. Spam e-mail would be full of offers to make your brain bigger, and your idea production more powerful.

Such a future would bear little resemblance to Brave New World or similar narcomantic nightmares; we may fear the idea of a population kept doped and placated, but we’re more likely to see a populace stuck in overdrive, searching out the last bits of competitive advantage, business insight, and radical innovation. No small amount of that innovation would be directed toward inventing the next, more powerful cognitive-enhancement technology.

This would be a different kind of nightmare, perhaps, and cause waves of moral panic and legislative restriction. Safety would be a huge issue. But as we’ve found with athletic doping, if there’s a technique for beating out rivals (no matter how risky), shutting it down is nearly impossible. This would be yet another pharmacological arms race—and in this case, the competitors on one side would just keep getting smarter.

The most radical form of superhuman intelligence, of course, wouldn’t be a mind augmented by drugs or exocortical technology; it would be a mind that isn’t human at all. Here we move from the realm of extrapolation to the realm of speculation, since solid predictions about artificial intelligence are notoriously hard: our understanding of how the brain creates the mind remains far from good enough to tell us how to construct a mind in a machine.

But while the concept remains controversial, I see no good argument for why a mind running on a machine platform instead of a biological platform will forever be impossible; whether one might appear in five years or 50 or 500, however, is uncertain. I lean toward 50, myself. That’s enough time to develop computing hardware able to run a high-speed neural network as sophisticated as that of a human brain, and enough time for the kids who will have grown up surrounded by virtual-world software and household robots—that is, the people who see this stuff not as “Technology,” but as everyday tools—to come to dominate the field.

Many proponents of developing an artificial mind are sure that such a breakthrough will be the biggest change in human history. They believe that a machine mind would soon modify itself to get smarter—and with its new intelligence, then figure out how to make itself smarter still. They refer to this intelligence explosion as “the Singularity,” a term applied by the computer scientist and science-fiction author Vernor Vinge. “Within thirty years, we will have the technological means to create superhuman intelligence,” Vinge wrote in 1993. “Shortly after, the human era will be ended.” The Singularity concept is a secular echo of Teilhard de Chardin’s “Omega Point,” the culmination of the Nöosphere at the end of history. Many believers in Singularity—which one wag has dubbed “the Rapture for nerds”—think that building the first real AI will be the last thing humans do. Some imagine this moment with terror, others with a bit of glee.

My own suspicion is that a stand-alone artificial mind will be more a tool of narrow utility than something especially apocalyptic. I don’t think the theory of an explosively self-improving AI is convincing—it’s based on too many assumptions about behavior and the nature of the mind. Moreover, AI researchers, after years of talking about this prospect, are already ultra-conscious of the risk of runaway systems.

More important, though, is that the same advances in processor and process that would produce a machine mind would also increase the power of our own cognitive-enhancement technologies. As intelligence augmentation allows us to make ourselves smarter, and then smarter still, AI may turn out to be just a sideshow: we could always be a step ahead.

So what’s life like in a world of brain doping, intuition networks, and the occasional artificial mind?

Banal.

Not from our present perspective, of course. For us, now, looking a generation ahead might seem surreal and dizzying. But remember: people living in, say, 2030 will have lived every moment from now until then—we won’t jump into the future. For someone going from 2009 to 2030 day by day, most of these changes wouldn’t be jarring; instead, they’d be incremental, almost overdetermined, and the occasional surprises would quickly blend into the flow of inevitability.

By 2030, then, we’ll likely have grown accustomed to (and perhaps even complacent about) a world where sophisticated foresight, detailed analysis and insight, and augmented awareness are commonplace. We’ll have developed a better capacity to manage both partial attention and laser-like focus, and be able to slip between the two with ease—perhaps by popping the right pill, or eating the right snack. Sometimes, our augmentation assistants will handle basic interactions on our behalf; that’s okay, though, because we’ll increasingly see those assistants as extensions of ourselves.

The amount of data we’ll have at our fingertips will be staggering, but we’ll finally have gotten over the notion that accumulated information alone is a hallmark of intelligence. The power of all of this knowledge will come from its ability to inform difficult decisions, and to support complex analysis. Most professions will likely use simulation and modeling in their day-to-day work, from political decisions to hairstyle options. In a world of augmented intelligence, we will have a far greater appreciation of the consequences of our actions.

This doesn’t mean we’ll all come to the same conclusions. We’ll still clash with each other’s emotions, desires, and beliefs. If anything, our arguments will be more intense, buttressed not just by strongly held opinions but by intricate reasoning. People in 2030 will look back aghast at how ridiculously unsubtle the political and cultural disputes of our present were, just as we might today snicker at simplistic advertising from a generation ago.

Conversely, the debates of the 2030s would be remarkable for us to behold. Nuance and multiple layers will characterize even casual disputes; our digital assistants will be there to catch any references we might miss. And all of this will be everyday, banal reality. Today, it sounds mind-boggling; by then, it won’t even merit comment.

What happens if such a complex system collapses? Disaster, of course. But don’t forget that we already depend upon enormously complex systems that we no longer even think of as technological. Urbanization, agriculture, and trade were at one time huge innovations. Their collapse (and all of them are now at risk, in different ways, as we have seen in recent months) would be an even greater catastrophe than the collapse of our growing webs of interconnected intelligence.

A less apocalyptic but more likely danger derives from the observation made by the science-fiction author William Gibson: “The future is already here, it’s just unevenly distributed.” The rich, whether nations or individuals, will inevitably gain access to many augmentations before anyone else. We know from history, though, that a world of limited access wouldn’t last forever, even as the technology improved: those who sought to impose limits would eventually face angry opponents with newer, better systems.

Even as competition provides access to these kinds of technologies, though, development paths won’t be identical. Some societies may be especially welcoming to biotech boosts; others may prefer to use digital tools. Some may readily adopt collaborative approaches; others may focus on individual enhancement. And around the world, many societies will reject the use of intelligence-enhancement technology entirely, or adopt a cautious wait-and-see posture.

The bad news is that these divergent paths may exacerbate cultural divides created by already divergent languages and beliefs. National rivalries often emphasize cultural differences, but for now we’re all still standard human beings. What happens when different groups quite literally think in very, very different ways?

The good news, though, is that this diversity of thought can also be a strength. Coping with the various world-histori­cal dangers we face will require the greatest possible insight, creativity, and innovation. Our ability to build the future that we want—not just a future we can survive—depends on our capacity to understand the complex relationships of the world’s systems, to take advantage of the diversity of knowledge and experience our civilization embodies, and to fully appreciate the implications of our choices. Such an ability is increasingly within our grasp. The Nöocene awaits.

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