The Coming of the Second Machine Age

If the first machine age was about the automation of manual labor and horsepower, the second machine age is about the automation of knowledge work.
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Andrew McAfee and Erik Brynjolfsson, from MIT's Center for Digital Business, have a new book out this week called, The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies.

McAfee and Brynjolfsson came to our attention in October 2011 with their thoughtful piece on data driven decision-making that ran in the Harvard Business Review. At the time, the two of them struck many of us as ahead of the curve on the phenomenon of big data and its impact on business. Since then, my colleagues and I have only become more impressed by what they've written.

That's why we invited McAfee to join EMC's leadership team in Boston a couple of weeks ago to talk with us about how every business model in every industry is going to be redefined in some form by software. If the first machine age was about the automation of manual labor and horsepower, the second machine age is about the automation of knowledge work, thanks to the proliferation of real time, predictive data analytics, machine learning and the Internet of Things -- an estimated 200 billion devices connected to the Internet by 2020, all of them generating unimaginable quantities of data.

McAfee and Brynjolfsson's favorite example of automated work is Google's self-driving car, a marvel of ingenuity enabled by technology's ability to capture the data of so many moving variables and act on them instantly, free of human error. If a self-driving car seems far-fetched, how about software that grades students' essays more objectively, consistently and quickly than humans? Or news articles on Forbes.com about corporate earnings previews -- "all generated by algorithms without human involvement."

We used to speak about how organizations had access to databases. Now, leading organizations are building "data lakes" -- giant reservoirs of information in heterogeneous formats, to aid decision-making and to offer new services to customers. Mobile apps collect intelligence from vast networks of drivers on highways to direct us to the least congested routes between points A and B. "Massive online open courses" offer thousands of college level students access to the best lecturers halfway around the world -- at a fraction of the cost.

But progress always has a flip side -- and its critics. Sweeping technology-driven transformations are as much about disruption and dislocation as opportunity. To explore this trade-off, we at EMC are hosting a breakfast conversation in Davos on Thursday with McAfee, Brynjolfsson and New York Times columnist Tom Friedman, who has written about these topics in previous books and columns. No conversation about the future can ignore the human costs of progress or the discomforting question of whether everyone is adequately prepared.

On this question, McAfee and Brynjolfsson are generally optimistic about the future of technology and the opportunities for humanity. The good news is, living standards increase with gains in productivity. But why are so many innovative large companies awash in cash while unemployment rates have hardly budged?

Harvard Business School's Clayton Christensen, who has devoted a career to studying disruptive innovation, spoke with us about this recently. The challenge, he notes, is that so much of the innovation we see in the world today is efficiency-based in nature: it's about doing familiar things in cheaper, more efficient ways.

In The Second Machine Age, the great software-defined businesses of tomorrow will be the ones that usher in breakthrough innovations that do new things entirely -- the kind of innovation that generates new value by opening up unforeseen market opportunities: new products, new services, new ways of servicing customers, and new jobs. That's what the first machine age was all about. Ready or not, the second machine age is already underway. And the value and disruption it will generate will stagger us all.

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