Chapter Thirteen

Missions Require Capital

In which I argue that a mission chosen before you have relevant career capital is not likely to be sustainable.

Mission Failure

When Sarah wrote me, she was stuck. She had recently quit her job as a newspaper editor to attend graduate school to study cognitive science. Sarah had considered grad school right out of college, but at the time, she worried that she didn’t have the right skills. With age, however, came more confidence, and after she signed up for and then aced an artificial-intelligence course that would have “scared a younger version of myself,” Sarah decided to take the plunge and become a full-time doctoral candidate.

Then the trouble started. Not long into her new student career Sarah became paralyzed by her work’s lack of an organizing mission. “I feel I have too many interests,” she told me. “I can’t decide if I want to do theoretical work or something more applied, or which would be more useful. Even more threatening, I believe all the other researchers to be geniuses…. What would you do if you were in my shoes?”

Sarah’s story reminded me of Jane, whom I introduced in Rule #3. As you might recall, Jane dropped out of college to “[start] a non-profit to develop my vision of health, human potential, and a life well-lived.” This mission, unfortunately, ran into a harsh financial reality when Jane failed to raise money to support her vague vision. When I met her, she was soliciting advice about finding a normal job, a task that was proving difficult because she lacked a degree.

Both Sarah and Jane recognized the power of mission, but struggled to deploy the trait in their own working lives. Sarah desperately wanted a Pardis Sabeti style of life-transforming research focus, yet her failure to immediately identify such a focus led her to rethink graduate school. Jane, on the other hand, slapped together something vague (a non-profit that would “develop my vision of… a life well-lived”) and then hoped the details would work themselves out once she got started. Jane fared no better than Sarah: The details, it turned out, did not work themselves out, leaving Jane penniless and still without a college degree.

I tell these stories because they emphasize an important point: Missions are tricky. As Sarah and Jane learned, just because you really want to organize your work around a mission doesn’t mean that you can easily make it happen. After my visit to Harvard, I realized that if I was going to deploy this trait in my own career, I needed to better understand this trickiness. That is, I needed to figure out what Pardis did differently than Sarah and Jane. The answer I eventually found came from an unexpected place: the attempts to explain a puzzling phenomenon.

The Baffling Popularity of Randomized Linear Network Coding

As I write this chapter, I’m attending a computer science conference in San Jose, California. Earlier today, something interesting happened. I attended a session in which four different professors from four different universities presented their latest research. Surprisingly, all four presentations tackled the same narrow problem—information dissemination in networks—using the same narrow technique—randomized linear network coding. It was as if my research community woke up one morning and collectively and spontaneously decided to tackle the same esoteric problem.

This example of joint discovery surprised me, but it would not have surprised the science writer Steven Johnson. In his engaging 2010 book, Where Good Ideas Come From, Johnson explains that such “multiples” are frequent in the history of science.1 Consider the discovery of sunspots in 1611: As Johnson notes, four scientists, from four different countries, all identified the phenomenon during that same year. The first electrical battery? Invented twice in the mid-eighteenth century. Oxygen? Isolated independently in 1772 and 1774. In one study cited by Johnson, researchers from Columbia University found just shy of 150 different examples of prominent scientific breakthroughs made by multiple researchers at near the same time.

These examples of simultaneous discovery, though interesting, might seem tangential to our interest in career mission. I ask, however, that you stick with me, as the explanation for this phenomenon is the first link in a chain of logic that helped me decode what Pardis did differently than Sarah and Jane.

Big ideas, Johnson explained, are almost always discovered in the “adjacent possible,” a term borrowed from the complex-system biologist Stuart Kauffman, who used it to describe the spontaneous formation of complex chemical structures from simpler structures. Given a soup of chemical components sloshing and mixing together, noted Kauffman, lots of new chemicals will form. Not every new chemical, however, is equally likely. The new chemicals you’ll find are those that can be made by combining the structures already in the soup. That is, the new chemicals are in the space of the adjacent possible defined by the current structures.

When Johnson adopted the term, he shifted it from complex chemicals to cultural and scientific innovations. “We take the ideas we’ve inherited or that we’ve stumbled across, and we jigger them together into some new shape,” he explained. The next big ideas in any field are found right beyond the current cutting edge, in the adjacent space that contains the possible new combinations of existing ideas. The reason important discoveries often happen multiple times, therefore, is that they only become possible once they enter the adjacent possible, at which point anyone surveying this space—that is, those who are the current cutting edge—will notice the same innovations waiting to happen.

The isolation of oxygen as a component of air, to name one of Johnson’s examples of a multiple discovery, wasn’t possible until two things happened: First, scientists began to think about air as a substance containing elements, not just a void; and second, sensitive scales, a key tool in the needed experiments, became available. Once these two developments occurred, the isolation of oxygen became a big fat target in the newly defined adjacent possible—visible to anyone who happened to be looking in that direction. Two scientists—Carl Wilhelm Scheele and Joseph Priestley—were looking in this direction, and therefore both went on to conduct the necessary experiments independently but at nearly the same time.

The adjacent possible also explains my earlier example of four researchers tackling the same obscure problem with the same obscure technique at the conference I attended. The specific technique applied in this case—a technique called randomized linear network coding—came to the attention of the computer scientists I work with only over the last two years, as researchers who study a related topic began to apply it successfully to thorny problems. The scientists who ended up presenting papers on this technique at my conference had all noticed its potential around the same time. Put in Johnson’s terms, this technique redefined the cutting edge in my corner of the academic world, and therefore it also redefined the adjacent possible, and in this new configuration the information dissemination problem, like the discovery of oxygen many centuries earlier, suddenly loomed as a big target waiting to be tackled.

We like to think of innovation as striking us in a stunning eureka moment, where you all at once change the way people see the world, leaping far ahead of our current understanding. I’m arguing that in reality, innovation is more systematic. We grind away to expand the cutting edge, opening up new problems in the adjacent possible to tackle and therefore expand the cutting edge some more, opening up more new problems, and so on. “The truth,” Johnson explains, “is that technological (and scientific) advances rarely break out of the adjacent possible.”

As I mentioned, understanding the adjacent possible and its role in innovation is the first link in a chain of argument that explains how to identify a good career mission. In the next section, I’ll forge the second link, which connects the world of scientific breakthroughs to the world of work.

The Capital-Driven Mission

Scientific breakthroughs, as we just learned, require that you first get to the cutting edge of your field. Only then can you see the adjacent possible beyond, the space where innovative ideas are almost always discovered. Here’s the leap I made as I pondered Pardis Sabeti around the same time I was pondering Johnson’s theory of innovation: A good career mission is similar to a scientific breakthrough—it’s an innovation waiting to be discovered in the adjacent possible of your field. If you want to identify a mission for your working life, therefore, you must first get to the cutting edge—the only place where these missions become visible.

This insight explains Sarah’s struggles: She was trying to find a mission before she got to the cutting edge (she was still in her first two years as a graduate student when she began to panic about her lack of focus). From her vantage point as a new graduate student, she was much too far from the cutting edge to have any hope of surveying the adjacent possible, and if she can’t see the adjacent possible, she’s not likely to identify a compelling new direction for her work. According to Johnson’s theory, Sarah would have been better served by first mastering a promising niche—a task that may take years—and only then turning her attention to seeking a mission.

This distance from the adjacent possible also tripped up Jane. She wanted to start a transformative non-profit that changed the way people live their lives. A successful non-profit, however, needs a specific philosophy with strong evidence for its effectiveness. Jane didn’t have such a philosophy. To find one, she would have needed a nice view of the adjacent possible in her corner of the non-profit sector, and this would have required that she first get to the cutting edge of efforts to better people’s lives—a process that, as with Sarah, requires patience and perhaps years of work. Jane was trying to identify a mission before she got to the cutting edge and she predictably didn’t come up with anything that could turn people’s heads.

In hindsight, these observations are obvious. If life-transforming missions could be found with just a little navel-gazing and an optimistic attitude, changing the world would be commonplace. But it’s not commonplace; it’s instead quite rare. This rareness, we now understand, is because these breakthroughs require that you first get to the cutting edge, and this is hard—the type of hardness that most of us try to avoid in our working lives.

The alert reader will notice that this talk of “getting to the cutting edge” echoes the idea of career capital, which was introduced back in Rule #2. As you’ll recall, career capital is my term for rare and valuable skills. It is, I argued, your main bargaining chip in creating work you love: Most people who love their work got where they are by first building up career capital and then cashing it in for the types of traits that define great work. Getting to the cutting edge of a field can be understood in these terms: This process builds up rare and valuable skills and therefore builds up your store of career capital. Similarly, identifying a compelling mission once you get to the cutting edge can be seen as investing your career capital to acquire a desirable trait in your career. In other words, mission is yet another example of career capital theory in action. If you want a mission, you need to first acquire capital. If you skip this step, you might end up like Sarah and Jane: with lots of enthusiasm but very little to show for it.

Not surprisingly, when we return to the story of Pardis Sabeti, we find that her path to a mission provides a nice example of this career capital perspective translated into practice.

Pardis’s Patience

“I think you do need passion to be happy,” Pardis Sabeti told me. At first this sounds like she’s supporting the passion hypothesis that I debunked in Rule #1. But then she elaborated: “It’s just that we don’t know what that passion is. If you ask someone, they’ll tell you what they think they’re passionate about, but they probably have it wrong.” In other words, she believes that having passion for your work is vital, but she also believes that it’s a fool’s errand to try to figure out in advance what work will lead to this passion.

When you hear Pardis’s story, the origin of this philosophy becomes clear. “In high school, I was obsessed with math,” she told me. Then she had a biology teacher whom she loved, which made her think that biology might be for her. When she arrived at MIT, she was forced to choose between math and bio. “It turns out that the MIT bio department has an unbelievable emphasis on teaching,” she explained. “So I majored in bio.” With a bio major came a new plan: She decided she was destined to become a doctor. “I perceived myself as someone who cared about people. I wanted to practice medicine.”

Pardis did very well at MIT, won a Rhodes Scholarship, and used it to go earn her PhD at Oxford. She focused on biological anthropology, a typically archaic Oxfordian name for a field most would simply call genetics.

It was at Oxford that Pardis decided that Africa and infectious diseases were also a potentially interesting topic to study. If you’re keeping count, this was the third field that at some point in her student career attracted her—the full list now contains math, medicine, and infectious disease. This is why she’s wary of the strategy of trying to identify your one true calling in advance—in her experience, lots of different things can, at different times, seem compelling.

Given her new interest in Africa, Pardis joined a research group using genetic analysis to help African-Americans trace their genealogy back to regions of Africa. After a year or so, Pardis decided to switch labs, and she moved into another, suggested by a friend. This lab was tackling the genetics of malaria.

After Oxford, Pardis returned to Harvard Medical School to earn her MD—amazingly, even as she was finishing up a PhD in genetics, she wasn’t ready yet to abandon her earlier premonition that she was somehow meant to be a doctor. The result was that she became a young med student finishing a PhD thesis during her spare time. “If you want to write a thing about having a quality enjoyable life, don’t ask me about my time at Harvard,” she warned. “Harvard was a tough time.”

Pardis finished her dissertation and became a postdoctoral fellow, continuing to juggle this work with the end of her MD program, taking the subway back and forth between Harvard and MIT, where she was now working at the Broad Institute with the famed geneticist Eric Lander. It was during this period that her ideas about using statistical analysis to find evidence of recent human evolution begin to yield results, culminating in the 2002 publication of a major paper in Nature with the innocuous title: “Detecting recent positive selection in the human genome from haplotype structure.”2

According to Google Scholar, the work has been cited over 720 times since its publication. “People started treating me differently after that paper,” Pardis says. “That’s when the faculty offers started coming in.” Though she finished her MD somewhere in this period, it was not until this point that her mission finally became clear: Becoming a clinical doctor didn’t make sense; she was going to build a research career focused on her use of computational genetics to combat ancient diseases. Pardis took a professorship at Harvard, finally ready to commit to a single focus in her working life.

What struck me about Pardis’s story is how remarkably late it was in her training before she identified the mission that now defines her career. This lateness is best represented by her decision to still attend—and finish!—medical school even though she was working on PhD research that was starting to attract notice. These are not the actions of someone who is certain of her destiny from day one. This certainty didn’t come until later, around the time of her Nature publication, when Pardis had finally developed her computational genetics ideas to the point where their usefulness and novelty were obvious.

To use my terminology, this long period of training, starting with her undergraduate biology classes and continuing through her PhD and then postdoctoral work at the Broad Institute, was when she was building up her stores of career capital. When she took a professorship at Harvard, she was finally ready to cash in this capital to obtain the mission-driven career she enjoys today.

Rule #4 is entitled “Think Small, Act Big.” It’s in this understanding of career capital and its role in mission that we get our explanation for this title. Advancing to the cutting edge in a field is an act of “small” thinking, requiring you to focus on a narrow collection of subjects for a potentially long time. Once you get to the cutting edge, however, and discover a mission in the adjacent possible, you must go after it with zeal: a “big” action.

Pardis Sabeti thought small by focusing patiently for years on a narrow niche (the genetics of diseases in Africa), but then acting big once she acquired enough capital to identify a mission (using computational genetics to help understand and fight ancient diseases). Sarah and Jane, by contrast, reversed this order. They started by thinking big, looking for a world-changing mission, but without capital they could only match this big thinking with small, ineffectual acts. The art of mission, we can conclude, asks us to suppress the most grandiose of our work instincts and instead adopt the patience—the style of patience observed with Pardis Sabeti—required to get this ordering correct.