AI for Pragmatists

The question you might ask as you approach the end of this book is: Which camp is right—utopian or dystopian?

The short answer? Neither.

The future won't be one extreme or the other; it won't be a utopia or a dystopia. We firmly believe, as we have argued throughout this book, that intelligent machines will increase living standards; create better, more satisfying jobs; allow us to solve big problems; and invent entirely new products, services, and experiences. But we also fully acknowledge the truth that intelligent machines will replace some occupations, put pressure on wages for many jobs, make some people's skills and capabilities irrelevant, and leave behind those unable to keep up and compete.

Between the extremes of the debate is the reality of what is going to happen in the next few years. Machines will learn to do more and more things; narrow AI will seep into every type of software, as well as an increasing range of physical products; systems of intelligence will expose the systems (and products, and processes, and organizations) that aren't intelligent; and customers will gravitate to the Google or Amazon price.

These things will happen—there is no doubt—while the AI debates continue to rage.

The debate has, so far, been in the hands of theoreticians. It's now time for pragmatists to take over, pragmatists who realize that the past has never been singularly utopian or dystopian. After all, the best-selling record in England in 1967, the year many musicologists believe was the greatest ever with the Beatles at the zenith of their fame, was Engelbert Humperdinck's “Release Me.” The past has always contained both; therefore, pragmatists logically believe the future will contain both, as well.

Pragmatists know that the debates will never be settled and fully agreed upon; but they know that arguing over possible futures ahead is less meaningful than making a probable future AHEAD. Pragmatists will be responsible for navigating their companies through the coming years, which all of us—utopians and dystopians alike—can agree will be full of change, disruption, opportunity, and risk.

The Digital Build-Out Is Here

In this book, we have argued that the information-technology innovations and investments of the past 70 years are merely a precursor to the next waves of digitization, which will have truly revolutionary impacts on every aspect of work, society, and life. Just as the world of 1840s England was not unlike that of 1770s England but was utterly different from 1870s England (at the end of the Second Industrial Revolution), the compounding and exponential nature of digital progress is set to make the next 15 years a period of fundamental metamorphosis.

If you sometimes think the way you file an insurance claim today is pretty much the same as when you first did so back in 1973, or that a visit to the division of motor vehicles seems unchanged from when you first got your driver's license, you're right; technology has only brushed the edges of how these institutions work. But in 15 years' time, these experiences, along with a raft of others, will be entirely unrecognizable.

What will your company's products and services look like in 2030? Will they be smart, personalized, full of intelligence, and offered at price points that unlock huge new addressable markets? Or will they be only marginally better than they are today, run on systems built in the 20th century, with processes full of paper and duplication and work-arounds? Will they still stink?

The great digital build-out that is in front of us is going to see us double down on work that matters. The winning companies (and the executives who lead them) are going to improve and upgrade how we manage our money, our health, the physical infrastructure of our cities and towns, as well as how we equip our kids with what they need to succeed, how we conduct government, and how we secure ourselves against those who would do us harm. Systems of intelligence will be at the heart of all these efforts to make our society better.

Align the Three M's

As the last S-curve's growth rate continues its inexorable journey south (and our politicians argue over how its spoils are distributed), the new S-curve is gathering momentum, and so are the companies poised to lead this new charge. These are the companies that have learned how to master the Three M's: how to align the new raw materials of the digital age (data), the new machines (systems of intelligence), and the new models (business models that optimize the monetization of data-based personalization). These are the companies that understand how to build and operate a Know-It-All business, that understand that intelligent machines aren't to be feared but embraced and harnessed, and that are energized by the unwritten future rather than just trying to hang onto the glories of the past.

Even when machines can do everything, it will still be people who are the ultimate X factor. And certainly for the foreseeable future, it will be people like you who need to decide to instrument everything; to harvest all of the resulting data; to ask questions of the data; and to teach the learning algorithms what to look for, what is meaningful, and what is immaterial. It is people who need to make the decisions about investing in Hadoop, in BigML or Hive, in AWS or Oracle's cloud. It is people who need to do the hard work of deciding that a once-successful product is no longer worth keeping alive.

These difficult questions along with a million others are the ones you need to answer today while debates about what “intelligence” is stretch out into an infinite horizon. (As Wikipedia dryly notes, “the definition of intelligence is controversial.”⁴)

It is leaders like you who need to know what to do when machines do everything. It is for leaders like you that we have written this book.

Move AHEAD

Our AHEAD model is our recommendation for what you should do:

• Automate everything you can.
• Instrument everything you can.
• Enhance every person you can.
• Drive the price point of your products and services down as low as you can.
• Discover and invent all of the possible futures you can.

By automating, you strip the costs out of processes, speed processes up, improve process quality, and achieve “beyond-human” scale.

By instrumenting and creating a Code Halo, you turn everything into a “data generator,” allowing you to see facts that have never been visible before.

By enhancing people and systems and processes through new technologies, you improve human performance levels. Multiply that by 1,000 or 100,000 people (or however many are in your organization), and in sum, you improve your corporate performance level.

By lowering the price of what you sell, you increase the size of the market you are serving; at an appropriate price point your offering has the potential to become abundant.

By prioritizing innovation, you increase your chances of discovering the future of your work.

The companies that are getting ahead are the ones acting on these ideas. Some companies we work with emphasize one “play” over another, while others recognize the holistic connection between all of the plays: automation enables enhancement, discovery uncovers how to achieve abundance, and so on.

All of them, however, understand the need to act now, to not wait for more certain times ahead, more clarity over exactly what AI is, and what it will become. All of them recognize that the rise of machine intelligence is the ultimate game changer we face today. All of them know that inaction will result in irrelevance. All of them know that fortune favors the brave and punishes the timid.

Courage and Faith in the Future

This is no time to be timid; just look at these quotes from recent news articles:

• “In 2014, for the first time, an e-sport's streamed broadcast attracted more viewers than the NBA Finals. More than 27 million people around the world tuned in to the League of Legends World Championship.”⁵
• “General Motors is launching a car-sharing program. It's called Maven, it's available in exactly one city, and frankly, it's an unexciting riff on ZipCar. But GM isn't really competing with ZipCar. It's placing a bet on the future.”⁶
• “‘Speed is the new currency of business. The most dangerous place to make a decision is in the office,’ says Salesforce.com CEO Marc Benioff.”⁷
• “Digital Asset Holdings, the Blockchain start-up run by former JPMorgan Chase & Co. banker Blythe Masters, raised $52 million from investors and won a contract to radically speed up settlement in Australia's stock market.”⁸
• “The [Sony] team's Flow Machines project successfully created… Daddy's Car, an AI-composed song that's meant to follow the musical style of The Beatles.”⁹
• “What happened is the instantaneous and disembodied transfer of the photon's quantum state onto the remaining photon of the entangled pair, which is the one that remained six kilometres away at the university.”¹⁰

What do all these quotes have in common? They are all messages from the future, telling us the world is changing faster than ever. Some of these you may not appreciate today, but in 10 years they could be part of our daily lives.

Approaches, norms, models, and ways of life that have been the backdrop during our 50 years (give or take!) on planet Earth and that one might have assumed would long outlast us are seemingly crumbling before our very eyes. Watching sports on TV, owning a car, answering a message the next day, planning to hold the same job for years, using a bank; all are going the way of all flesh.

This incredible pace of change, and the substantive nature of this change, is, at its core, about one thing: what to do when machines do everything.

Innovation shows no signs of stopping (despite our elevated perch on Maslow's Hierarchy of Needs) and shows no sign of being any less powerful than it has been in the past; quite the opposite.¹¹ Remember, don't short human imagination. The future is racing toward big businesses through the apps and Web services they use to get to the airport, hire new recruits, segment audiences, collaborate, meet, book hotels, ship goods, and access bandwidth and CPUs. All this abundance—functionality delivered at price points that are blowing away incumbent competition—is the light of innovation, of new ideas and approaches, of the future, that is there for everyone to see and follow and use.

The new frontiers we have explored in this book aren't simply about substituting labor with software; they're about building the new machines that will allow us to achieve higher levels of human performance. As Narrative Science's Kris Hammond—a pragmatist at heart—put it to us, “AI is not a mythical unicorn. It's the next level of productivity tool.”

As we have seen throughout the preceding pages, innovation has propelled humans forward through the centuries; although the process of innovation is always messy and often uncomfortable (or worse), its power is entirely unstoppable.

Hammond, as one of the world's leading AI practitioners, sees the inevitability of widespread AI in the workplace: “I don't believe that work on AI can be inhibited. It's not like stem cells where there are physical things you can do to stop stem cell research. There is nothing physical you can do to stop AI research. The computational resources are out there.”

As we have repeatedly illustrated, AI isn't coming; it's here. What this book attempts to do is show you there are things—many, many things—that you can do—must do—when machines do everything. Those who win in the coming great digital build-out, who seize the incredible rewards, who make history, will be those who stop debating and start building—and, rather than predicting the future, go out and invent it, hand-in-hand with the new machines.