FOREWORD
From Flat to Fast to Smart to Deep

—Thomas L. Friedman
Foreign affairs columnist, the New York Times

There are a lot of snappy, shorthand ways I could summarize Heather and Chris’s book, but my favorite is this phrase that they use to encapsulate the essence of what they are saying: the abiding cliché and dominant news headline in the workplace these days is that the robots are going to take your job. What you learn from this book, though, is that, yes, indeed, robots can take your job. But if we’re smart, they can also guide you to and define your next job. Because whether it’s robots or automation or digitization, two things are true and always will be: there will always be another technological advance that will devour existing jobs—and, yes, those advances will be coming faster and faster. But we will always need humans to translate and augment the latest technology and we will always need humans to make meaning, joy, and connections that entertain us, inspire us, and connect us the moment we put our technology down. Microchips cannot and will not replace relationships. Your next job starts where the robots stop. Learn to embrace that handoff.

The best way to do that, Heather and Chris argue, for both individuals and organizations, is through rapid learning, unlearning, and adaptation. These skills are the new normal. Rapid learning, by the way, is not just about how to augment machines as they spin off new jobs, but how to augment humans as they stay the same, always craving meaning, joy, and new forms of entertainment and connections in every new epoch.

Rapid unlearning and adaptation are both about how we embrace and absorb new skills and how we let go of old ones. To be able to do both effectively and constantly, they argue, requires a mind shift and an identity shift—a letting go of “who we think we are” and a regular reinventing of yourself. I find this the most original aspect of their book—the important role that identity plays in how and how much we can learn and adapt at the steady pace demanded by this age of acceleration.

Heather and Chris argue that those who do it best will be those who allow themselves to be vulnerable, forcing themselves to be more open to the new and to the other. And that is not always easy under any conditions, but it is especially challenging when social norms are rapidly changing, or new immigrants are arriving with greater speed and numbers, and your identity—your sense of home, work, and norms—feels like it is under assault. That people today all over the world are reaching for walls to slow down the pace of change and protect their identities is not an accident.

I will let them tell you the rest …

If there is anything I can contribute from my own research and writing, it’s the conviction that the technological forces that are requiring such rapid learning, unlearning, and adaptation—this new normal—are not going away. Indeed, they just keep getting faster and touching deeper into more areas of daily life, commerce, governance, and science. Why?

The short answer is that technology moves up in steps, and each step tends to be biased toward a certain set of capabilities. Around the year 2000, for instance, a group of technologies came together that were biased toward “connectivity.” Because of the dramatic fall in the price of fiber-optic cable, thanks to the dot-com boom, bubble, and bust, we were suddenly able to wire much of the world and, as a result, connectivity became fast, virtually free, easy for you, and ubiquitous. Suddenly I could touch people I could never touch before and I could be touched by people who could never touch me before. I gave that moment a name. I said it felt like “the world is flat.”

Around 2007, another set of technologies came together that had the effect of making the world “fast.” This was also driven by a price collapse—a collapse in the price of computers, storage, software broadband, and smartphones. This enabled us to do a huge number of complex tasks on the cloud with just one touch on a mobile device. We took friction and complexity out of so many things. Suddenly, with just one touch, on an Uber or Didi app, I could page a taxi, direct a taxi, pay a taxi, rate a taxi, and be rated by a taxi. With just one touch! Complexity became fast, virtually free, easy for you, and invisible.

Indeed, the year 2007 was a remarkable year. In 2007, Steve Jobs introduced the iPhone. Facebook opened its platform to anyone with a registered email address and went global in 2007. Twitter split off onto its own platform and went global in 2007. Airbnb was born in 2007. In 2007, VMware—the technology that enabled any operating system to work on any computer, which enabled cloud computing—went public, which is why the cloud really only took off in 2007. Hadoop software—which enabled a million computers to work together as if they were one, giving us“Big Data”—was launched in 2007. Amazon launched the Kindle e-book reader in 2007. IBM launched Watson, the world’s first cognitive computer, in 2007. The essay launching Bitcoin was written in 2006. Netflix streamed its first video in 2007. IBM introduced nonsilicon materials into its microchips to extend Moore’s Law in 2007. The Internet crossed one billion users in late 2006, which seems to have been a tipping point. The price of sequencing a human genome collapsed in 2007. Solar energy took off in 2007, as did a process for extracting natural gas from tight shale, called fracking. Github, the world’s largest repository of open source software, was launched in 2007. Lyft, the first ride-sharing site, delivered its first passenger in 2007. Michael Dell, the founder of Dell, retired in 2005. In 2007, he decided he’d better come back to work—because in 2007, the world started to get really fast. It was a real turning point.

Today, we have taken another step up to another platform: now the world is getting “smart.” And it is being driven by still another price collapse—the collapse in the price and size of sensors. Now we can put sensors—“intelligence”—into anything and everything. We can put intelligence into your refrigerator, your car, your lightbulb, your toaster, your front door, your golf club, or your shirt. And with that intelligence, we can make your car drive itself, your refrigerator stock itself, and your shirt talk to your doctor and then tell your grocer which healthy foods to deliver to your home. And we can do all of that now with “no touch.” It all just happens by sensors talking to machines and vice versa. The other day I got a text message on my cellphone that said I had an appointment in my office in 30 minutes, but I was still 35 minutes away by car. It made me smart—or at least aware—with not even a touch, because it was sensing from my smartphone and GPS where I was, how far I was from my next meeting, and who that meeting was with when.

So what’s the next platform? I believe that when the world gets this flat, fast, and smart, what happens next is that it starts to get deep. How so? Well, when your shirt has sensors in it that can measure your body functions and then tell your e-commerce grocery store what foods are right for your particular body type and DNA and then order them for you at Walmart and have them delivered by an autonomous vehicle or drone to your refrigerator and restock them when the refrigerator announces that you are running low—that’s “deep.” And that’s where we’re going. Deep is the ability to hit that precise target you are looking for—no matter how small or hidden—in the precise context you are looking for it and then impact that target—heal it, fix it, track it, extract it, illuminate it, fake it, or destroy it—with an accuracy that a decade ago would have been dismissed as science fiction.

And that is why, in my opinion, deep is the word of the year. Have you noticed how many things we are now describing with the word deep?—deep mind, deep medicine, deep war, deep fake, deep surveillance, deep insights, deep climate, deep adaptation. We discovered that we needed a new word, a new adjective, to describe the fact that “deep technologies” have two qualities that we could tell were a difference in degree that was a difference in kind. One is physical. Deep technologies literally get imbedded deep inside your neighborhood, your home, or your bedroom. Having Siri or Amazon Alexa in your bedroom is deep. Having 5G wired into the streets of your neighborhood is deep. Having a shirt that monitors all your key bodily functions is deep.

The other quality is existential. Deep technologies can reach into places so deep and produce outcomes, insights, and impacts so profound and accurate that we also needed a new adjective to describe them. Deep technologies are almost God-like in their powers to hit precise targets in medicine or war; to find the right needles in the right haystacks of data; to manipulate the right atoms and cells in science; to create machines that can defeat any human in chess, Jeopardy, or Go; or to fake any face, voice, or image—always with an accuracy or at a depth that was considered science fiction just 15 years ago. And that is why deep technologies also need to be governed in new ways, because they can be used for so much more good or evil in so many new ways.

As the world has gone from flat to fast to smart to deep, it is overturning and melting traditions, foundations, and bonds in every realm of our lives—how we work, how we communicate, how we learn, how we educate, how we conduct business, how we conduct trade, how families communicate with each other, and how governments control their people—to name but a few. In my opinion, this inflection point may in time be understood as the single biggest and broadest inflection point since Guttenberg invented the printing press. And you just happened to be here. And it’s not over—in fact, it’s just getting started. Heather and Chris’s book is an indispensable guide to how navigate this new era in the workplace.