Reflections on the eBook Race Against the Machine

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Reflections on the eBook

Race Against the Machine:

How the Digital Revolution is Accelerating Innovation,

Driving Productivity, and Irreversibly Transforming Employment and the Economy

By Erik Brynjolfsson and Andrew McAfee of MIT

Race Against the Machine was published as an eBook in 2011. The authors make some very intriguing points, especially if you are interested in innovation. From a business person’s perspective, the main point of the book is that in the coming years improvements in computer and communications technology will create many unanticipated disruptive changes in how work is done, how businesses succeed, and which careers are sustainable. Some of the changes are already here, and the authors demonstrate how innovation in combination with human skills and organization agility and modification will lead to success.
The authors are economists, and their recommendations focus on macro-economic and significant societal changes which are needed to address the consequences of their observations. I thought it might be useful for friends and colleagues to hear their core messages and my thoughts on the messages’ implications at the organizational and individual level. Your feedback on my analysis is welcomed.
Why You Might Be Interested
As a leader in your organization, whether you are in a technical or managerial role, you are interested in improving productivity of your unit and organization. In fact, while you know breakthroughs don’t occur daily, you are interested in potential breakthroughs that will impact your unit or organization.
Also, on a personal level, you are interested in how technology might impact your career and the careers of your loved ones.

For these reasons you might want to read the rest of this analysis.

What is the Main Thesis of Race Against the Machine?

The authors’ main thesis can be summed up with these quotes from the book:

We wrote this book because we believe that digital technologies are one of the most important driving forces in the economy today. They’re transforming the world of work and are key drivers of productivity and growth. Yet their impact on employment is not well understood, and definitely not fully appreciated. When people talk about jobs in America today, they talk about cyclicality, outsourcing and off-shoring, taxes and regulation, and the wisdom and efficacy of different kinds of stimulus. We don’t doubt the importance of all these factors. The economy is a complex, multifaceted entity. {They go on to say but there is another reason, see the two paragraphs below.}

The root of our problems is not that we’re in a Great Recession, or a Great Stagnation {another author’s analysis of our economic problems today}, but rather that we are in the early throes of a Great Restructuring. Our technologies are racing ahead but many of our skills and organizations are lagging behind. The pace and scale of this encroachment into human skills is relatively recent and has profound economic implications. Perhaps the most important of these is that while digital progress grows the overall economic pie, it can do so while leaving some people, or even a lot of them, worse off.

We used to be pretty confident that we knew the relative strengths and weaknesses of computers vis-à-vis humans. But computers have started making inroads in some unexpected areas. This fact helps us to better understand the past few turbulent years and the true impact of digital technologies on jobs.

We are on the Second Half of the Chessboard

To serve as a visual metaphor for their theses, the authors’ selected the story below from Kurzweil’s 2000 book, the Age of Spiritual Machines: When Computers Exceed Human Intelligence.

In one version of the story, the inventor of the game of chess shows his creation to his country’s ruler. The emperor is so delighted by the game that he allows the inventor to name his own reward. The clever man asks for a quantity of rice to be determined as follows: one grain of rice is placed on the first square of the chessboard, two grains on the second, four on the third, and so on, with each square receiving twice as many grains as the previous. The emperor agrees, thinking that this reward was too small. He eventually sees, however, that the constant doubling results in tremendously large numbers. The inventor winds up with 2 x 64 power grains of rice or a pile bigger than Mount Everest.

Kurzweil notes that the pile of rice is not that exceptional on the first half of the chessboard: After thirty-two squares, the emperor had given the inventor about 4 billion grains of rice. That’s a reasonable quantity—about one large field’s worth—and the emperor did start to take notice. But the emperor could still remain an emperor. And the inventor could still retain his head. It was as they headed into the second half of the chessboard that at least one of them got into trouble. Kurzweil’s point is that constant doubling, reflecting exponential growth, is deceptive because it is initially unremarkable. Exponential increases initially look a lot like standard linear ones, but they’re not. As time goes by—as we move into the second half of the chessboard—exponential growth confounds our intuition and expectations.

The authors tie this story to Moore’s Law regarding the doubling of computing power every 18 months and conclude {admittedly their educated guess} that as of 2006 we have moved into the second half of the chessboard. They then give some very interesting examples that illustrate how computers and computer networks are beginning to do things we had not expected and beginning to displace jobs we would not have anticipated. This is significantly disruptive to the economic status quo. A few examples are given below:

  • real-world driving went from being an example of a task that couldn’t be automated to an example of one that had. In October of 2010, Google announced on its official blog that it had modified a fleet of Toyota Priuses to the point that they were fully autonomous cars, ones that had driven more than 1,000 miles on American roads without any human involvement at all {though a driver legally had to be in the driver’s seat on the trip}. The Google vehicles’ only accident came when the driverless car was rear-ended by a car driven by a human driver as it stopped at a traffic light.

    • Let’s speculate on how this might impact businesses and individuals. Will the cars and trucks of the future be more like flying a plane equipped with an effective automatic pilot? If so, then driving might be a lot safer, and seniors might not drive 40 MPH on Interstate highways. Or will the cars and trucks of the future be more like riding in a train. If so, then we might think about reworking the interior of the car or truck so it is more like an office or entertainment center. If you are being driven to your destination by the vehicle why not work or be entertained. Then again, think about how this may impact the need for different skills. More jobs in car design and providing electronics for the interior of cars and trucks. How will it impact the work of truck or taxi cab drivers? Can you image riding in a New York City cab that didn’t cut other cars off every block and where the cab driver spend time trying to find the right entertainment pleasure for you while the cab delivered you to your destination?

  • Translating from one human language to another, for example, has long been a goal of computer science researchers, but progress has been slow because grammar and vocabulary are so complicated and ambiguous. In January of 2011, however, the translation services company Lionbridge announced pilot corporate customers for GeoFluent, a technology developed in partnership with IBM.

GeoFluent is based on statistical machine translation software developed at IBM’s Thomas J. Watson Research Center. This software is improved by Lionbridge’s digital libraries of previous translations. This “translation memory” makes GeoFluent more accurate, particularly for the kinds of conversations large high-tech companies are likely to have with customers and other parties. {The technology has tested out very well}

    • While this may impact the need for translators ten years from now, think about how once this becomes a fairly portable technology, it will impact travel to foreign countries or business meetings involving people who speak different languages. Right now, one inhibitor to the effective functioning of global teams, particularly those involving highly skilled professionals tackling complex tasks, is their ability to truly understand each other in real time. For example, companies that deployed such a technology effectively {with the proper processes and training} could significantly improve the productivity of their product development teams.

  • A March 2011 story by John Markoff in the New York Times highlighted how heavily computers’ pattern recognition abilities are already being exploited by the legal industry where, according to one estimate, moving from human to digital labor during the discovery process could let one lawyer do the work of 500. {One software user tasked his}… e-discovery software to reanalyze work his company’s lawyers did in the 1980s and ’90s. His human colleagues had been only 60 percent accurate, he found.

    • Think about how this may impact the need for lawyers right now. Recent studies have shown that we have twice as many people passing the bar in a year as there are job openings. More important, many jobs require discovery; and where discovery is time consuming making cost an issue, discovery may not get done at all. Last time I looked at my twenty-year-old health folder at my primary care physician’s office {PCP}, it was about four inches think, and I have been pretty healthy. What are the chances that my PCP appreciates the key facts in those four inches and is aware of key trends without my reminding him? How much better would my PCP be if the records were electronic and his nurse used some form of discovery software to search my record before my next visit? And, as I age, and become pretty incompetent at reminding the doctor of key facts in my medical history, how much better health care would I get if this discovery software was deployed?

The authors sum up this discussion regarding moving into the second half of the chessboard with these comments:

Advances like the Google car and GeoFluent translation, then, can be seen as the first examples of the kinds of digital innovations we’ll see as we move further into the second half—into the phase where exponential growth yields jaw-dropping results. These results will be felt across virtually every task, job, and industry. Such versatility is a key feature of general purpose technologies (GPTs), a term economists assign to a small group of technological innovations so powerful that they interrupt and accelerate the normal march of economic progress. Steam power, electricity, and the internal combustion engine are examples of previous GPTs.

As the economists Timothy Bresnahan and Manuel Trajtenberg note: Whole eras of technical progress and economic growth appear to be driven by … GPTs, [which are] characterized by pervasiveness.

Thus, as GPTs improve they spread throughout the economy, bringing about generalized productivity gains. GPTs, then, not only get better themselves over time (and as Moore’s Law shows, this is certainly true of computers), they also lead to complementary innovations in the processes, companies, and industries that make use of them. They lead, in short, to a cascade of benefits that is both broad and deep. Computers are the GPT of our era, especially when combined with networks and labeled “information and communications technology” (ICT).

Racing with Machines

While it is difficult to forecast which jobs, careers, industries, etc. will be significantly impacted as we move into the second half of the chessboard, it is clear that there is great economic incentive to develop these technologies. Consequently, many game changing technologies will be developed over time.

However, the authors think that in those areas where game changing technologies will be deployed the winners will be those that learn to race with machines, not against them. Below are a few select examples from the book to more fully describe the authors’ ideas.

In 1997 Gary Kasparov, the top chess master at the time, was beaten by Deep Blue {IBM computer}. Today the best chess player in the world is not a person or a machine, but a team of humans using computers. A pair of amateur players using three computers is the current champ in open competition which allows any combination of humans and computers.

The authors drew these conclusions from examining instances where computers were deployed to compete against man.

  • Weak human + machine + better process was superior to a stronger computer alone and, more remarkably, superior to a strong human + machine + inferior process.”

  • The authors’ contend that this true in many parts of the economy.

  • Therefore, a key to competition is fostering organization innovation, which includes everything from improving processes, to adapting organizational structures, business models and cultures to leverage advancing technology and human skills.

The authors retell the famous legend of John Henry and the steam engine. Of course John Henry won the battle, beat the steam engine, but lost the war, died of a broken heart (over exertion). They think the more appropriate analogy for today is the Indy 500, humans racing with machines to beat the competition. They argue that machines that are forever evolving and improving but require human ingenuity to beat the competition.

Every generation underestimates the potential of finding new ideas that solve significant problems facing society and their business. Here are two that are interesting:

  1. The authors cite this example – “When Bill Clinton assembled the top minds in the Nation in 1992 to discuss the economy, no one mentioned the Internet.”

  2. My favorite example comes from Ernesto Sirolli’s September 2012 TED talk. The relevant quote is below:

There's a lovely story that I read in a futurist magazine many, many years ago. There was a group of experts who were invited to discuss the future of the city of New York in 1860. And in 1860, this group of people came together, and they all speculated about what would happen to the city of New York in 100 years, and the conclusion was unanimous: The city of New York would not exist in 100 years. Why? Because they looked at the curve and said, if the population keeps growing at this rate, to move the population of New York around, they would have needed six million horses, and the manure created by six million horses would be impossible to deal with. They were already drowning in manure.

So 1860, they are seeing this dirty technology that is going to choke the life out of New York.

So what happens? In 40 years' time, in the year 1900, in the United States of America, there were 1,001 car manufacturing companies -- 1,001. The idea of finding a different technology had absolutely taken over, and there were tiny, tiny little factories in backwaters, Dearborn, Michigan, Henry Ford.

Implications for You, Your Business and Your Loved Ones

I encourage everyone to read the entire book if interested in the details that lead to the authors’ conclusions and to see what they recommend be done at a societal level to cope with the changes they are predicting.

In this section I pose some questions and offer some comments for you to think about regarding the impact on you, your business and your loved ones as we move into the second half of the chessboard.

At the Business Level

Create a list of game changing possibilities for your business that could be brought about in the next 5-10 years by a combination of more powerful computers and communication networks in combination with smart organizational changes {to include process, structure, business model, etc. changes}. It is important to get the right people “in the room” to develop this list.

  • Estimate the potential impact on your business if such technologies were in fact developed.

  • Which technologies would it make sense to develop internally; which with partners to create competitive advantage? Why?

  • Which technologies would it makes sense to adapt from other industries where versions of the game changing technology might already be deployed?

  • Which of the technologies are being developed by technical service companies that you might be able to adopt once developed? Can you gain competitive advantage by working with the service company in some way as they are developing the technology?

  • For each technology you feel is worth either developing or scouting for in other industries or service companies, estimate the smart organization changes that will be needed to create competitive advantage when deploying the technology. This analysis may help you determine that some technologies would not be a good fit for your organization because they would be very difficult to deploy effectively.

  • Utilize the thinking generated by answering the above questions to create a technology innovation strategy for using computers and communications networks in your business over the next 5-10 years.

At the Career Level

As you make decisions that shape your career or give advice to loved ones, colleagues and subordinates regarding decisions that will shape their career keep these thoughts in mind:

  • Be constantly alert to the possibility of how a change in technology could help productivity, creativity, etc. in the profession in question.

  • Jobs that require a degree of physical coordination and sensory perception have proven to be the most difficult to automate. This covers activities from surgery to cutting hair.

  • Jobs that require problem solving when examining complex, unique systems will be difficult or expensive to automate. This covers activities from management consulting to fixing the plumbing in an existing building or house.

  • Jobs that require adjusting to complex and unique changing environments will be difficult or expensive to automate. This covers activities from business management to air traffic controller. Note driving fits into this category, so when there is a large enough audience and the prize is large enough, it is possible to automate, as the Google car has demonstrated.

In summary, the key take aways at a personal level from this book are:

  • We are in the second half of the chessboard and profound, unanticipated changes in how work gets accomplished can significantly impact your business or you.

  • Figure out for your business and your career how you can most effectively race with machines to achieve success.

Richard M. DiGeorgio © Richard M. DiGeorgio & Associates, LLC – 2013 – 215-369-0088 Page

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