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- Herausgeber: John Wiley & Sons
- Kategorie: Fachliteratur
- Sprache: Englisch
- Veröffentlichungsjahr: 2017
"Refreshingly thought-provoking..." - The Financial Times The essential playbook for the future of your business What To Do When Machines Do Everything is a guidebook to succeeding in the next generation of the digital economy. When systems running on Artificial Intelligence can drive our cars, diagnose medical patients, and manage our finances more effectively than humans it raises profound questions on the future of work and how companies compete. Illustrated with real-world cases, data, and insight, the authors provide clear strategic guidance and actionable steps to help you and your organization move ahead in a world where exponentially developing new technologies are changing how value is created. Written by a team of business and technology expert practitioners--who also authored Code Halos: How the Digital Lives of People, Things, and Organizations are Changing the Rules of Business--this book provides a clear path to the future of your work. The first part of the book examines the once in a generation upheaval most every organization will soon face as systems of intelligence go mainstream. The authors argue that contrary to the doom and gloom that surrounds much of IT and business at the moment, we are in fact on the cusp of the biggest wave of opportunity creation since the Industrial Revolution. Next, the authors detail a clear-cut business model to help leaders take part in this coming boom; the AHEAD model outlines five strategic initiatives--Automate, Halos, Enhance, Abundance, and Discovery--that are central to competing in the next phase of global business by driving new levels of efficiency, customer intimacy and innovation. Business leaders today have two options: be swallowed up by the ongoing technological evolution, or ride the crest of the wave to new profits and better business. This book shows you how to avoid your own extinction event, and will help you; * Understand the untold full extent of technology's impact on the way we work and live. * Find out where we're headed, and how soon the future will arrive * Leverage the new emerging paradigm into a sustainable business advantage * Adopt a strategic model for winning in the new economy The digital world is already transforming how we work, live, and shop, how we are governed and entertained, and how we manage our money, health, security, and relationships. Don't let your business--or your career--get left behind. What To Do When Machines Do Everything is your strategic roadmap to a future full of possibility and success. Or peril.
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Contents
Cover
Title Page
Copyright
Preface
Chapter 1: When Machines Do Everything
Like It or Not, This Is Happening
Digital That Matters
Playing the New Game
But Will I Be Automated Away?
Getting AHEAD in the Age of the New Machine
Chapter 2: From Stall to Boom: We've Been Here Before
When Machines Do Everything, What Happens to Us?
But Haven't Our Computers Made Us More Productive?
Carlota's Way
Riding the Waves
Three Big Reasons Why a Boom Is About to Occur
From Stall to Boom, a Time of Optimism
Chapter 3: There Will Be Blood
Predictions of Massive Job Losses via AI
Manual vs. Knowledge Labor: As Goes the Factory, So Goes the Office?
Don't Confuse Jobs with Tasks
Don't Overlook the Job-Growth Story
The Pace of This Transition
Getting AHEAD in a Time of Churn
Chapter 4: The New Machine: Systems of Intelligence
Defining the New Machine
Meet the Machine: Anatomy of a System of Intelligence
Systems of Intelligence in Action
What Does “Good” Look Like? Attributes of a Successful System of Intelligence
From Vapor to Value
Chapter 5: Your New Raw Materials: Data Is Better than Oil
Turning Data from a Liability into an Asset
Managing the Data Supply Chain
Business Analytics: Turning Data into Meaning
If It Costs More than $5, and You Can't Eat It, Instrument It!
The Home-Field Advantage of Big Companies
Data Is Job One
Chapter 6: Digital Business Models: Your Five Ways to Beat Silicon Valley
Hybrid Is the New Black
Avoiding the Four Traps
Five Ways to Mine Gold from the New Machines
The Management Opportunity of a Generation
Chapter 7: Automate: The Robots Aren't Coming; They're Here
Automation Is Not Optional
Software Should Be Eating Your Core Operations
What to Do on Monday? Flick Your Automation-On Switch
Automation Is a Means, Not an End
Chapter 8: Halo: Instrument Everything, Change the Game
Every “Thing” Is Now a Code Generator
Become a “Know-It-All”
What to Do on Monday? Capitalize on Code
Digits over Widgets: The Next Age of Business and Technology
Chapter 9: Enhance: Amplify Human Performance with the New Machine
Stone Age, Bronze Age, Iron Age…Digital Age
Enhanced Jobs Will Be Protected Jobs
Smart Robots Make Smarter Hands
What to Do on Monday? Partner with Systems of Intelligence
You + New Tools = Enhancement
Chapter 10: Abundance: Finding Your 10X Opportunities with the New Machine
What to Do on Monday? Find Abundance in Your Organization
Increasing Prosperity by Lowering Prices
Chapter 11: Discovery: Manage Innovation for the Digital Economy
R&D Without AI Is No R&D at All
Discovery Is Hard, but Not as Hard as Being Irrelevant
What to Do on Monday? Don't Short Human Imagination
Create Your Own Budding Effect
Chapter 12: Competing on Code: A Call to Action from the Future
AI for Pragmatists
The Digital Build-Out Is Here
Align the Three M's
Move AHEAD
Courage and Faith in the Future
Acknowledgments
Photo Credits
Disclaimers
Index
End User License Agreement
List of Illustrations
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Guide
Cover
Table of Contents
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What to Do When Machines Do Everything
How to Get Ahead in a World of AI, Algorithms, Bots, and Big Data
Malcolm Frank, Paul Roehrig, and Ben Pring
Cover image: Kirill_makarov/Shutterstock.comCover design: theBookDesigners
Copyright © 2017 by Cognizant Technology Solutions U.S. Corporation. All rights reserved
Published by John Wiley & Sons, Inc., Hoboken, New JerseyPublished simultaneously in Canada
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Library of Congress Cataloging-in-Publication Data:
Names: Frank, Malcolm, author. | Roehrig, Paul, author. | Pring, Benjamin, 1962- author.
Title: What to do when machines do everything : how to get ahead in a world of AI, algorithms, bots, and big data / Malcolm Frank, Paul Roehrig, and Ben Pring.
Description: Hoboken, New Jersey : John Wiley & Sons, Inc., [2017] | Includes index.
Identifiers: LCCN 2016049472 (print) | LCCN 2017004469 (ebook) | ISBN 9781119278665 (cloth) | ISBN 9781119278672 (pdf) | ISBN 9781119278689 (epub)
Subjects: LCSH: Automation. | Information technology—Economic aspects. | Technological innovations—Economic aspects.
Classification: LCC HD6331 .F664 2017 (print) | LCC HD6331 (ebook) | DDC 658/.05—dc23
LC record available at https://lccn.loc.gov/2016049472
Preface
We know what you might be thinking: When machines do everything, what am I going to do? It's a good question.
If machines can do everything, then how are humans going to make a living? How are we going to pay the rent or mortgage or put food on the table? How are we going to survive when software eats all the knowledge work?
Even if you have reached a stage in your career in which you feel safe from the rise of the new machines, how will your children thrive when computers can out-think, out-work, and out-manage them? What do they study? Where do they focus? And will they have any chance of living a life as good as yours?
At work, how should your company be structured when so much can now be automated? What will happen to all those middle-class, middle-management knowledge jobs that currently stand as the economic bedrock of our society?
These are all good questions—the right questions—for indeed, something very big is going on.
The rise of artificial intelligence is the great story of our time. Decades in the making, the smart machine is leaving the laboratory and, with increasing speed, is infusing itself into many aspects of our lives: our phones, our cars, the planes we fly in, the way we bank, and the way we choose what music to listen to.
Within the next few years, AI will be all around us, embedded in many higher-order pursuits. It will educate our children, heal our sick, and lower our energy bills. It will catch criminals, increase crop yields, and help us uncover new worlds of augmented and virtual reality.
Machines are getting smarter every day and doing more and more; they will soon change our lives and our work in ways that are easy to imagine but hard to predict. So what does one do?
These are the questions that have been going through our minds for a while, too. Anyone with a casual interest in the future can see these issues swirling through the zeitgeist at the moment: in movies (Ex Machina and Her), on TV (Black Mirror, Humans, and Battlestar Galactica), in books (Superintelligence and Rise of the Robots), and in countless articles in the press. But we have more than a casual interest in the future.
As the leaders of Cognizant's Center for the Future of Work, it is our job to figure out how the future of work works. We engage with many of the world's leading companies, universities, analysts, technologists, and economists to make sense of the great change we are all experiencing as well as to fathom how work will be reimagined, reconfigured, and restructured in the years to come. We do this to understand how new technology will shape the opportunities we have and the threats we face and to foresee how man and machine will relate and coexist.
So we've spent the last three years thinking about what to do when machines do everything, separating the hype from the reality on the front lines of global business.
The book you're holding contains our answers to these questions.
The bottom line? It's going to be all right. In fact, better than all right, because AI is about to usher in a new industrial revolution that, for those who manage it properly, will generate significant economic growth.
Will the new machines displace many current workers? Yes. However, on a larger scale, new machines will also create work that is better, more productive, more satisfying than ever before. The new machines will raise living standards and usher in a period of widely distributed economic growth that will be far stronger than any we've seen in the Western world during the past 50 years.
But there's a catch, which is expressed in the “what to do” part of the title of this book.
You and the company you work for and represent must accept, embrace, and leverage the fact that, minute by minute, machines are doing more and more of the work we perform today. That is the underlying assumption at the heart of this book.
This is where many people get stuck. They start tumbling down existential wormholes: Will machines need us? Who will control the machines? Will machines act in the best interests of humanity? Again, these are great questions that prompt fascinating discussions, all of which we like having as much as the next person, particularly with a glass of red wine on hand. But these discussions don't help you know what to do.
If you want to read about the big philosophical debates about what AI might do in the next 25 years, this is not the book for you. But if you want pragmatic advice on what AI will do in the next five years, then this is definitely the book for you.
While some have their heads in the sky, others have their noses to the grindstone. While some will ponder, winners will act.
This book aims to answer questions about the future of your business and your work in an era of intelligent machines. It explains how you as an individual and as a leader in your organization can survive and thrive in a world where machines do everything. This book explains what you should do, why, and what will happen if you don't.
We wrote this book because we are in an amazing time. Though we are professional students of the future, the three of us are students of history as well. Understanding the great shifts of the past provides a framework for understanding how change happens in the here and now. The rise of machine intelligence is such a moment of great change. Our children and grandchildren will study these times just as we study James Watt, Andrew Carnegie, and Thomas Edison.
It's time to build our own future, complete with a sense of optimism and confidence. When machines do everything, there will still be a lot for you to do. Let's get on with it.
1When Machines Do Everything
Artificial intelligence has left the laboratory (and the movie lot) and is in your building. It's in your home. It's in your office. It's pervading all the institutions that drive our global economy. From Alexa to Nest to Siri to Uber to Waze, we are surrounded by smart machines running on incredibly powerful and self-learning software platforms. And this is just the beginning.
To date, we've been enjoying—without even really noticing—various forms of “weak” artificial intelligence (AI). It's how Amazon recommends just the right gift. How Netflix suggests the perfect film for your Sunday evening. Or how Facebook fills your newsfeed. These forms of AI have been welcome little helpers, making our days just a bit easier and more fun. Once we start using them we stop thinking about them. In just a few short years, these machines have become almost invisible to us in our personal lives.
Now AI is transitioning from being our little daily helper to something much more powerful—and disruptive—as the new machines are rapidly outperforming the most talented of us in many endeavors. For example:
Games of intellect:
AI platforms can now out-compete us at some of our most challenging games—Jeopardy!, Chess, and Go. Google's AlphaGo beat world champion Go player Lee Sedol by a score of 4–1 in March 2016.
1
This was a convincing win, but not a rout. Yet with the current rate of technological advancement, in just a few years it will be inconceivable for a human to beat the new machines in such games of the mind.
Driving:
The driverless car, while still relatively nascent, is already a better driver than the average person. According to a Virginia Tech study, human-driven vehicles are involved in 4.2 crashes per million miles vs. 3.2 crashes per million miles for the automated car.
2
This disparity in safety will undoubtedly grow considerably in the next few years, and driverless cars, which never text behind the wheel or drive drunk, may soon become mainstream.
Trading:
In 2015, six of the top eight hedge funds in the United States earned around $8 billion based largely—or exclusively—on AI algorithms.
3
The machine has already won in stock picking.
Health care:
In medicine, the new machine is quickly surpassing the capabilities of human radiologists. Researchers at Houston Methodist Hospital utilize AI software, which interprets results of breast X-rays 30 times faster than doctors and with 99% accuracy. By contrast, mammograms reviewed by humans result in unnecessary biopsies nearly 20% of the time.
4
Law:
In the legal profession, AI-enhanced computer systems are conducting discovery and due diligence far better, faster, and cheaper than the most talented team of paralegals in a white-shoe law firm. Multiple studies predict that the vast majority of paralegal work can soon be automated. We may reach a point in the not-too-distant future when relying only on humans for discovery might be grounds for malpractice.
We could go on and on with many more examples, but the point is clear; the new machines have already surpassed human capability in many ways. Moreover, with the geometric growth in the power and sophistication of these platforms, this is only a preview of coming attractions.
Thus, this rapid expansion of AI leads us to ask some big questions:
Will a robot take my job away?
Will my company be “Ubered”?
What will my industry look like in 10 years?
Will my children be better off than I am?
In the coming pages, we will answer these questions in a structured and practical manner. Based on our cumulative 100 years of experience analyzing and charting shifts in business and technology, we are fully convinced that we're now moving into a new economic era, one that will change the nature of work and the basis of competition in every industry. In this new economy, we will witness an expansion of what is possible and move from machines that do to machines that appear to learn and think.
Like It or Not, This Is Happening
What the World Economic Forum hailed in 2016 as the Fourth Industrial Revolution is now upon us: a time of economic dislocation, when old ways of production give way to new ones, and when those who can harness the power of the new machine will harvest the bounty of economic expansion.5 In the same manner that the First Industrial Revolution was powered by the invention of the loom, the second by the steam engine, and the third by the assembly line, the fourth will be powered by machines that seem to think—what we refer to in these pages as “systems of intelligence.”
This is leading to what we call the “know-it-all” business, in which leaders and managers can and should have a continuous awareness of all that is occurring in their company's operations. Where we used to guess, now we can know. These new machines—always “on,” always “learning,” and constantly “thinking”—will soon challenge and enhance the intellect and experience of even the savviest professionals in every sector. There's no way to escape the gravitational pull of these new machines and the business models that enable and leverage them.
As such, whether you are managing a large enterprise or just starting your first job, deciding what to do about the new machine—this new cocktail of AI, algorithms, bots, and big data—will be the single biggest determinant of your future success.
Digital That Matters
For the past decade, we've collectively enjoyed “digital that's fun.” We've seen the incorporation of Twitter (2006), the introduction of Apple's iPhone (2007), and Facebook's IPO (2012). These companies, along with others, such as Google, Netflix, and Amazon, have been able to generate unprecedented commercial success in terms of customer adoption, daily usage, and value creation by changing how we communicate and socialize. Yet, history will note that we started the digital revolution with the amusing and the frivolous: Facebook posts, Twitter feeds, and Instagram photos. We are using the most powerful innovations since the introduction of alternating current to share cat videos, chat with Aunt Alice, and hashtag political rants. However, that's just the warm-up act, for we haven't yet begun to fully realize the potential of the new machines.
Technology writer Kara Swisher summed it up best when she said, “In Silicon Valley, there's lots of big minds chasing small ideas.”6 Well, we're entering an era of big brains focused on big ideas—digital that matters—using these technologies to transform how we are educated, fed, transported, insured, medicated, and governed.
While companies such as Facebook, Amazon, Netflix, and Google (sometimes known as the FANG vendors) seem to have established themselves as the presumptive and eternal winners in this space, history will likely remember them as the precursors to a much more momentous and democratic economic shift. The next wave of digital titans probably won't be characterized by start-ups from Silicon Valley; instead, it will be made up of established companies in more “traditional” industries—in places like Baltimore, Birmingham, Berlin, and Brisbane—that figure out how to leverage their longstanding industry knowledge with the power of new machines.
We're starting to see this play out as we collectively work to apply systems of intelligence to help address some of our most vexing societal ills in areas where digital technology is not just entertaining or convenient but also life-altering. Certainly, many of our institutions—the pillars of our society and our everyday lives—are ripe for improvement.
For example, worldwide we lose 1.2 million lives to car accidents annually, with more than 94% of these accidents a result of human error.7 In the United States alone, these wrecks cost society over $1 trillion. This is nearly one-third the amount the U.S. federal government collects in individual income taxes.8 Driverless cars promise to save countless lives and heartache.
One-third of all food produced in the world goes to waste. The food wasted in rich countries alone is almost enough to feed all of sub-Saharan Africa.9 By instrumenting the supply chain and applying AI, we could literally feed the world.
Medical misdiagnoses could also plummet. Right now, 5% to 10% of trips to the ER results in a misdiagnosis.10 More than 12 million diagnostic mistakes contribute to 400,000 deaths caused by preventable errors each year, and that's just in the United States.11 Applying data to the diagnostic process could dramatically improve patient outcomes.
The United States spends more per student on secondary education than most other countries in the world but generates mediocre results. In a recent international study, American students achieved scores far below those in many other advanced industrial nations in science, reading, and math.12 By tailoring lessons to the individual learning style of each student through technology, we could make the education process radically more productive and effective for both students and teachers.
These are the sorts of big things that we can address with the new machine. It's digital with purpose and digital that matters, and the big brains bringing these innovations forward will not necessarily reside in Silicon Valley or an MIT dorm room. They may well be sitting in an office down the hall at your company.
For example, McGraw-Hill Education is applying new technology to help teachers and kids improve learning with a system called ALEKS. The artificially intelligent Assessment and LEarning in Knowledge Spaces system uses adaptive questioning to quickly and accurately determine exactly what a student knows and doesn't know in a course. ALEKS then instructs the student on the topics he or she is most ready to learn. As the student works through a course, ALEKS periodically reassesses the student to ensure retention. All of this results in more flexible, one-on-one instruction for students, which boosts student success. And for teachers, ALEKS helps take over some of the more routine—and, let's say it, boring—work to allow them to focus more intently on working with students. Discovery, one of South Africa's leading insurers, uses its Vitality platform to provide economic incentives—discounts on travel, entertainment, healthy food, gym memberships, sports equipment, health products, and the like—to its members based on whether they participate in healthy behaviors. Members earn points by logging workouts with connected fitness devices and purchasing healthy food (also logged by swiping their Vitality card). The insurance sector may not be known as a hotbed of innovation, but Discovery has built a thriving business based on the value derived from the new machine.
Playing the New Game
Another area ripe for reinvention is managing our money. Jon Stein doesn't look like a Wall Street Master of the Universe—just the opposite, in fact. In his mid-30s, dressed in blue jeans and a mildly tattered shirt, he works not in a financial citadel but in a relaxed loft-like space. His language is not full of bravado and bombast but is casual, considered, and humble.
Figure 1.1 Jon Stein, CEO and founder of Betterment
Yet Stein is turning his corner of the banking world, personal wealth management, on its head. His company, Betterment, has rapidly become one of the world's leading “robo-advisors,” leveraging AI platforms to rewrite the rules of the financial advisory business. Betterment provides highly personalized, curated wealth management services 24x7. His system of intelligence is doing the work of hundreds of people and is doing it better, at a fraction of the cost.
Millions of investors—millennials, Gen-Xers, and baby boomers alike—are flocking to the platform. From the beginning of 2015 to mid-2016, Betterment's assets under management grew from $1.1 billion to $5.0 billion13,14 and for good reason. Betterment has created a bigger pie for wealth management services because it can attract new customers that traditional banks wouldn't touch. Traditional “bulge-bracket” investment banks (e.g., Goldman Sachs, Morgan Stanley, Credit Suisse, etc.) often do not offer personalized wealth management services to anyone with less than $1 million in assets; the margin isn't there, given their one-to-one advisory business model. So where does that leave the other 99.9% of the population that is interested in having their money professionally managed?
Betterment started by focusing on HENRY (high earners, not rich yet). These are young professionals in their 20s and early 30s: lawyers, doctors, and managers starting their careers armed with great educations…and the associated student debt.
Traditional wealth managers won't touch HENRY, but Betterment welcomes anyone with money to invest. And as each new customer comes on the platform, the system gets smarter, providing better value to each individual participant: on the spot, empirically based, unspun counsel on investment strategy, portfolio allocation, and tax management.
Robo-advisers, collectively, have more than $50 billion in assets under management today (and are estimated to have over $250 billion under management by 2020) and are taking aim at the $20 trillion worldwide that is currently being managed by 46,000 human financial advisors at traditional banks.15
Now, we don't know whether Betterment will ultimately emerge as the long-term winner in this new form of financial advisory services, but the company does demonstrate how new machines are disrupting traditional ways of work. Such widespread adoption is creating shock waves in both the financial services and technology industries.
Stein, and others who have figured out the new game, are nothing short of the Henry Fords of our time. They understand today's new raw materials (big data). They have built and now operate the new machines. And, most important, they have surrounded these new machines with business models that generate remarkable growth and profitability engines while expanding the overall market.
The story of robo-advisors in wealth management is about to be replayed a thousand-fold across all sectors of our economy. So the question becomes: Will you play, or stand on the sidelines?
But Will I Be Automated Away?
We have already proven that we love to consume AI-based products (with our rabid usage of the FANG vendors’ offers on our smartphones). And, through digital that matters, the new machine is poised to transform the primary institutions of our society for the better.
Yet once we get over our initial awe of the new machine, we start to wonder how it will impact jobs. What will happen to all those bankers, drivers, radiologists, lawyers, and journalists? What will happen to…me? Will a robot take my job?
Many of us don't know whether this Fourth Industrial Revolution is very good or very bad. It all starts to feel like a capitalist's dream…but a worker's nightmare. And the uncertainty is creating a palpable sense of anxiety, for at a personal level, many of us don't know what to do about it.
Some see only the dark side of this shift, and indeed, many of today's headlines forecast a grim future in a “jobless economy” as robots take over our livelihoods. But the coming digital boom and build-out we describe in the next chapter will be highly promising for those who are prepared. In fact, it will usher in once-in-a-century growth prospects as we reengineer our infrastructure, our industries, and our institutions. Similar to the prior three industrial revolutions, this one will steamroll those who wait and watch, and will unleash enormous prospects and prosperity for those who learn to harness the new machine.
All of this depends on what you do now to prepare for an era when machines can potentially do nearly everything related to knowledge work.
Will many jobs be “automated away” in the coming years? Yes. However, for the vast majority of professions, the new machine will actually enhance and protect employment. We don't think, for example, that a single teacher or nurse will lose their job due to artificial intelligence. Instead, these professions will become more productive, more effective…and more enjoyable. Workers in such professions will come to view the new machine as their trusted colleague. Just as one wouldn't think of driving across London today without an AI-based GPS, or researching a subject without referring to Google and Wikipedia, most workers in the coming years would not consider approaching their daily tasks without a “bot” at their side.
Additionally, entirely new professions will be created, driving employment in fields we can't currently envision (imagine trying to describe a “database administrator” to somebody in 1955). We have much to look forward to if we understand exactly what the new machine can and cannot do and how it will impact the future of work. Some very clear patterns for success have emerged, and we'll spend the rest of the book framing what's going on and providing tactical guidance on how to win in the new digital economy.
Getting AHEAD in the Age of the New Machine
We've written this book to provide you with a roadmap, a guide to success for this time of transition. First, we will outline what the machine actually is: how it's built, what it can do, and what it can't do. We will then look at where it can best be used today and tomorrow. What industry problems can it solve? What new customer value propositions can it create? Third, and most importantly, we will give you a structured approach for moving forward with our AHEAD model, which is based on our work with Global 2000 companies at the vanguard of the digital transition.
Briefly, AHEAD outlines the five distinct approaches for winning with systems of intelligence. The acronym stands for:
Automate:
Outsource rote, computational work to the new machine. This is how Netflix automated away the Blockbuster retail store and how Uber is automating away taxi dispatching.
Halo:
Instrument products and people and leverage the data exhaust they generate through their connected and online behaviors (what we call Code Halos) to create new customer experiences and business models.
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General Electric and Nike are changing the rules of the game in their industries by instrumenting their products, surrounding them with halos of data, and creating new value propositions and customer intimacy.
Enhance:
View the computer as a colleague that can increase your job productivity and satisfaction. The GPS in your car currently enhances your driving, keeping you on the fastest route, alerting you of road hazards, and ensuring that you never get lost. In the coming years, entire vocations, from sales to nursing to teaching, will be revolutionized with the power of computer-based enhancement.
Abundance:
Use the new machine to open up vast new markets by dropping the price point of existing offers, much as Henry Ford did with automobiles. In the way that Betterment is using AI to bring financial security to the masses, which market offers can be greatly democratized and expanded in your industry?
Discovery:
Leverage AI to conceive entirely new products, new services, and entirely new industries. As Edison's light bulb led to new discoveries in radio, television, and transistors, today's new machine will lead to a new generation of discovery and invention.
These are five specific approaches—plays, if you will—for winning with AI, each with its own set of approaches and tactics. In the coming pages, we will utilize this model to demystify the application of the new machine in your business.
The first play—to automate—is the one most prevalent in today's zeitgeist. Automation has been the initial step in each industrial revolution, as one loom replaced 40 textile workers or one steam engine had the power of 50 horses. Today, automation will be a similar necessary “evil,” because it's how you will deliver at the “Google price” in core portions of your company. However, what most market observers miss is that the next wave of automation will pave the way for invention and economic expansion through the four subsequent plays.
This one-two of efficiency plus invention will manifest itself across all industries. Banking will become more efficient and personalized. Health care will become more transparent and effective, generating much better outcomes. Manufactured goods will become more interactive, intuitive, and reliable. Our food system will be less wasteful and produce higher quality goods. Education will be enhanced and individualized, and government services will be upgraded and more cost-effective. And, as outlined previously, much of this shift will not be driven by companies that were started last year or even 10 years ago but by companies started by our grandparents. This is because those companies have access to the richest lodes of data, the “fuel” for the new machine.
Much has already been said and written about the potential impact of the new machine on society. We wrote this book not for policy wonks and academics but rather for people in organizations large and small that are trying to make the best decisions possible for their businesses and their own jobs. We aren't naïve to the fact that business happens in a wider context, but we can't all sit around waiting for politicians to improve education or to pass huge spending bills to enhance infrastructure or enact a universal basic income. We need to act today in the world as it is. You can rest assured that if you don't act now, others will.
The title of this book is What to Do When Machines Do Everything. This may sound a bit hyperbolic, and clearly machines will never do everything and nobody really wants them to. But in the next few years the new machines will continue to amaze, will be embedded most everywhere and in most everything, and will increasingly do more and more of the work people do today.
Technology is no longer the domain of the few but the province of the many. As such, those who win in the next phase of the digital economy are not those who can create the new machines, but those who figure out what to do with them. This book is your field guide.
Notes
1.
Christopher Moyer, “How Google's AlphaGo Beat a Go World Champion,”
The Atlantic
, March 28, 2016,
http://www.theatlantic.com/technology/archive/2016/03/the-invisible-opponent/475611/
.
2.
“Automated Vehicle Crash Rate Comparison Using Naturalistic Data,” January 8, 2016,
http://www.vtti.vt.edu/featured/?p=422
.
3.
Emel Akan, “World's Top Hedge Fund Managers Took Home $13 Billion in 2015,”
Epoch Times
, May 17, 2016,
http://www.theepochtimes.com/n3/2067771-worlds-top-hedge-fund-managers-took-home-13-billion-in-2015/
.
4.
Todd Ackerman, “Houston invention: Artificial Intelligence to read mammograms”
San Antonio Express-News
, Sept. 16, 2016,
http://www.expressnews.com/local/prognosis/article/Houston-researchers-develop-artificial-9226237.php
.
5.
Klaus Schwab,
The Fourth Industrial Revolution
, World Economic Forum, Jan. 11, 2016,
https://www.amazon.com/Fourth-Industrial-Revolution-Klaus-Schwab-ebook/dp/B01AIT6SZ8
.
6.
John Kennedy, “Kara Swisher: ‘In Silicon Valley, There Are a Lot of Big Minds Chasing Small Ideas,’” Silicon Republic, June 24, 2015,
https://www.siliconrepublic.com/start-ups/kara-swisher-in-silicon-valley-there-are-a-lot-of-big-minds-chasing-small-ideas
.
7.
“Human Error Accounts for 90% of Road Accidents
,” International News
, April 2011,
http://www.alertdriving.com/home/fleet-alert-magazine/international/human-error-accounts-90-road-accidents
.
8.
See
http://www.rmiia.org/auto/traffic_safety/Cost_of_crashes.asp
and
http://www.who.int/violence_injury_prevention/publications/road_traffic/world_report/en/
and
https://en.wikipedia.org/wiki/United_States_federal_budget
.
9.
http://www.fao.org/save-food/resources/keyfindings/en
.
10.
“Surprising Number of Emergency Room Medical Errors,” July 15, 2016,
http://philadelphia.cbslocal.com/2016/07/15/surprising-number-of-emergency-room-medical-errors/
.
11.
http://www.cbsnews.com/news/12-million-americans-misdiagnosed-each-year-study-says/
and
http://www.healthcareitnews.com/news/deaths-by-medical-mistakes-hit-records
.
12.
http://www.cbsnews.com/news/us-education-spending-tops-global-list-study-shows/
and
http://www.pewresearch.org/fact-tank/2015/02/02/u-s-students-improving-slowly-in-math-and-science-but-still-lagging-internationally/
.
13.
“Millennials hire computers to invest their money,”
Denver Post
, March 4, 2016,
http://www.denverpost.com/2016/03/04/millennials-hire-computers-to-invest-their-money/
.
14.
Julie Verhage, “Robo-Adviser Betterment Hits the $5 Billion Mark,”
Bloomberg Markets
, July 14, 2016,
http://www.bloomberg.com/news/articles/2016-07-14/robo-adviser-betterment-hits-the-5-billion-mark
.
15.
Melody Hahm, “Robo-advisor Wealthfront is now using AI to manage over $3 billion in assets,”
Yahoo! Finance
, March 31, 2016,
https://beta.finance.yahoo.com/news/robo-advisor-wealthfront-artificial-intelligence-betterment-assets-venmo-205354921.html
and Michael P. Regan, “Robo Advisers to Run $2 Trillion by 2020 if This Model Is Right,” Bloomberg, June 18, 2015,
http://www.bloomberg.com/news/articles/2015-06-18/robo-advisers-to-run-2-trillion-by-2020-if-this-model-is-right
.
16.
For more information on Code Halos, see our white paper and book,
https://www.cognizant.com/code-halos
.
2From Stall to BoomWe've Been Here Before
Many of us feel stalled. Growth, both for our companies and for us individually, seems increasingly difficult to attain. There is plenty of evidence of the structural weakening of our economy: stagnant wages, rising debt levels, and anemic productivity growth. It seems the major trends are all working against us: increased global competition, a winner-take-all economy driving massive income inequality, the steady erosion of privacy and security, start-ups worth billions emerging while legacy firms crumble, and technology taking our jobs. It's clear that the old rules of work and business no longer apply.
We (the authors) work with a lot of people excited about the opportunities that lie ahead in the digital economy, but their optimism is often tempered by the news of the day. The headlines all too frequently seem to foretell a pending jobless nightmare of breadlines and robot overlords. And some feel as if there's a party being thrown—in Silicon Valley, New York, and London—that they're not invited to.
Yet within the malaise there is good news. We have weathered similar storms before, and the shape and pattern of our current situation is actually a harbinger for a period of technology-fueled growth. This seems counterintuitive; after all, how can economic stagnation signal future growth and opportunity?
It's because our current stall fits within a well-established pattern that shows up during every major shift in business and technology, when the economy moves from one industrial revolution to the next. In short, we are currently in an economic “stall zone” as the Third Industrial Revolution is (literally) running out of gas, while the Fourth Industrial Revolution—based on the new machine—has yet to grab hold at scale.
This situation creates a dissonance in which we marvel at the computers that surround us, and all they can do, while we search in vain for greater growth prospects for our companies and career security for ourselves.
The good news, which we will explore in this chapter, is that we are coming to the end of the stall zone and entering a time when the economy can break out for those who harness the power of the new machine. We refer to this as the coming “digital build-out,” in which the fruits of digital technology move from Silicon Valley to the entire economy. This value migration will be of a scale similar to the industrial build-out of the last century and will move much faster. To fully understand this transition, it helps to take a look back at the impact of new machines on work in previous periods of tumultuous disruption.
When Machines Do Everything, What Happens to Us?
People have been worried about “new machines” and their effect on the human condition for centuries. Only the machine has changed; the concerns remain the same.
Back in the early 1800s, during the First Industrial Revolution, the Luddites in northwestern England responded to the introduction of power looms by smashing them. They recognized that their textile jobs were at risk. It turned out that they were right; the machines
