Digitalization and the American workforce In recent decades, the diffusion of digital technology into nearly every business and workplace, also known as “digitalization,” has been remaking the U.S. economy and the world of work. The “digitalization of everything” has at once increased the potential of individuals, firms, and society while also contributing to a series of troublesome impacts and inequalities, such as worker pay disparities across many demographics, and the divergence of metropolitan economic outcomes. In light of that, this report presents a detailed analysis of changes in the digital content of 545 occupations covering 90 percent of the U.S. workforce in all industries since 2001. The analysis categorizes U.S. occupations into jobs that require high, medium or low digital skills and tracks the impacts of rapid change. The U.S. economy is digitalizing at an extremely rapid pace. Select occupations and digital skill level, 2016 Source: Brookings analysis of O*Net, OES, and Moody's data. 2002 and 2016 United States
What the future of work will mean for jobs, skills, and wages In an era marked by rapid advances in automation and artificial intelligence, new research assesses the jobs lost and jobs gained under different scenarios through 2030. The technology-driven world in which we live is a world filled with promise but also challenges. Cars that drive themselves, machines that read X-rays, and algorithms that respond to customer-service inquiries are all manifestations of powerful new forms of automation. Yet even as these technologies increase productivity and improve our lives, their use will substitute for some work activities humans currently perform—a development that has sparked much public concern. Video Powerful new technologies are increasing productivity, improving lives, and reshaping our world. The results reveal a rich mosaic of potential shifts in occupations in the years ahead, with important implications for workforce skills and wages. 1. 2. Rising incomes and consumption, especially in emerging economies Aging populations 3. Wage level 4. 5.
Beneath the U.S. job numbers: Tech’s influence on the workforce continues to hollow out the labor market Like clockwork, the start of each month brings the latest update on U.S. job numbers from the U.S. Bureau of Labor Statistics (BLS). Vital to assembling a momentary look at the job market’s latest trends, the report will support a pulse of urgent and useful news stories with its mixed and sometimes blurry data points on such topics as job growth and unemployment. And yet, for all that, the jobs report remains in many ways a distraction from the most important longer-term trend lines and macro forces. For example, don’t bet on the new numbers shedding much light on one of the most profound labor-market trends of all—one highlighted by our brand-new report on the “digitalization” of the U.S. economy. This trend is the extraordinary “hollowing out” of the job market that finds the nation’s high-skill and low-skill occupational groups growing even as middle-skill job categories sag. What’s going on with this “U-shaped” picture of the nation’s job problems? Why is this happening?
A New Year’s resolution to address wage inequality in firms As I was making my New Year’s resolutions a few days ago, I found myself distracted by an old item of news. It said that the civil servant in the United Kingdom who was responsible for increasing the pension age to 67 was to retire at the age of 61 with a pension pot of 1.8 million pounds—another example, the article suggested, of the establishment helping themselves while applying a different set of rules to the rest of us. Regardless of the rights and wrongs of that particular case, it set me thinking about inequality—not just in the U.K., but more generally for developed countries. Which begs the question “why not?” What else might work? If a cap is a bad idea, what about a ratio? Fortunately, there is a simple solution to this problem and astonishingly, to my knowledge, it has never been attempted. Table 1 provides a simple example for three firms with different wage distributions (for simplicity, we have shown firms with 10 employees, but it works for any number).
10 Dumb Mistakes Smart People Make When It Comes To Finding Their Purpose You would think a world filled with options and opportunity would excite you. But sometimes having too many options can paralyze you. You might think to yourself: What if I make the wrong choices and waste a bunch of time? You want a better life, but fear and uncertainty keep holding you back. I came up with a list of 10 mistakes you might be making which are steering you in the wrong direction, but learning about those won’t do you any good unless you start with a clean slate. Brainwashing 101 — How Society Has Ruined Your Life You’ve been brainwashed. Keeping people in line fuels corporate America. Sit still. Before we continue with this list, I want you to rid your mind of everything you’ve been told and start from scratch. Here are the mistakes you might be making when trying to find your purpose in life. You Focus On Passion “Find something you love and you’ll never work a day in your life.” *Barf* The focus on passion permeates our society. You want to know how to find passion? Sort of.
Students don't pursue STEM because it's too hard, say 52% of Americans When Americans are asked why more students don’t pursue a degree in science, technology, engineering or math (STEM), they are most likely to point to the difficulty of these subjects, according to a new Pew Research Center survey. About half of adults (52%) say the main reason young people don’t pursue STEM degrees is they think these subjects are too hard. Policymakers and educators have long puzzled over why more students do not pursue STEM majors in college, even though those who have an undergraduate degree in a STEM field of study earn more than those with other college majors – regardless of whether they work in a STEM job or a different occupation. Yet only a third of workers (33%) ages 25 and older with at least a bachelor’s degree have an undergraduate degree in a STEM field, according to a new Pew Research Center analysis. Only 13% of the U.S. workforce was employed in STEM occupations as of 2016, while the vast majority (87%) was employed in other occupations.
Labor 2030: The Collision of Demographics, Automation and Inequality The analysis and business insights in this report can help leaders put these changes in context and consider the effects they will have on their companies, their industries and the global economy. Chapter 1 explores the impact of aging populations and the end of plentiful labor. The baby boomer generation powered a long but temporary surge in labor force growth. Chapter 2 examines how automation may solve one problem by increasing productivity and powering growth but creates another by potentially eliminating millions of jobs and suppressing wages for many workers. Chapter 3 looks at how rising inequality could threaten growth. Chapter 4 traces how developments are likely to unfold in the turbulent 2020s. Chapter 5 considers the outlook if governments intervene more actively in the marketplace to address economic imbalances. Introduction By 2030—little more than a decade from now—the global economy will likely be in the midst of a major transformation. Some key implications follow.
Tech companies should stop pretending AI won’t destroy jobs I took an Uber to an artificial-intelligence conference at MIT one recent morning, and the driver asked me how long it would take for autonomous vehicles to take away his job. I told him it would happen in about 15 to 20 years. He breathed a sigh of relief. “Well, I’ll be retired by then,” he said. Good thing we weren’t in China. That might sound surprising, given that the US is, and has been, in the lead in AI research. China will have at least a 50/50 chance of winning the race, and there are several reasons for that. First, China has a huge army of young people coming into AI. Second, China has more data than the US—way more. Third, Chinese AI companies have passed the copycat phase. And fourth, government policies are accelerating AI in China. The rise of China as an AI superpower isn’t a big deal just for China. Not everyone agrees with my view. Then there are the symbiotic optimists, who think that AI combined with humans should be better than either one alone.
Deep Learning Is Going to Teach Us All the Lesson of Our Lives: Jobs Are for Machines (An alternate version of this article was originally published in the Boston Globe) On December 2nd, 1942, a team of scientists led by Enrico Fermi came back from lunch and watched as humanity created the first self-sustaining nuclear reaction inside a pile of bricks and wood underneath a football field at the University of Chicago. Known to history as Chicago Pile-1, it was celebrated in silence with a single bottle of Chianti, for those who were there understood exactly what it meant for humankind, without any need for words. Now, something new has occurred that, again, quietly changed the world forever. The language is a new class of machine learning known as deep learning, and the “whispered word” was a computer’s use of it to seemingly out of nowhere defeat three-time European Go champion Fan Hui, not once but five times in a row without defeat. What actually ended up happening when they faced off? So, what is Go? Let the above chart sink in. Routine Work Neural Networks Big Data
How AI could transform the way we measure kids' intelligence There is a saying in education that you treasure what you measure. Going by the standardized tests that dominate schools in many countries around the world, we’re teaching children that we value only a very narrow definition of intelligence—the ability to solve word problems about train times, or identify the purpose of a World War I treaty on a multiple-choice test. The truth is human intelligence is vast and complex. Yet it is measured—and valued—crassly. And in an age when artificial intelligence is capable of nailing IQ tests and mastering knowledge-based curricula, humans may be setting ourselves up to be outshone by technology. “I think we are in danger of dumbing ourselves down,” says Rose Luckin, a professor of learning-centered design at University College London who has been studying artificial intelligence and learning for more than 25 years. Redefining intelligence Luckin identifies seven kinds of intelligence that kids will need to thrive in the future. The future of testing
How to Program Your Job In 2016, an anonymous confession appeared on Reddit: “From around six years ago up until now, I have done nothing at work.” As far as office confessions go, that might seem pretty tepid. But this coder, posting as FiletOFish1066, said he worked for a well-known tech company, and he really meant nothing. He wrote that within eight months of arriving on the quality assurance job, he had fully automated his entire workload. “I am not joking. The tale quickly went viral in tech corners of the web, ultimately prompting its protagonist to delete not just the post, but his entire account. About a year later, someone calling himself or herself Etherable posted a query to Workplace on Stack Exchange, one of the web’s most important forums for programmers: “Is it unethical for me to not tell my employer I’ve automated my job?” The post proved unusually divisive, and comments flooded in. Call it self-automation, or auto-automation. “It felt weird to have free time during the day,” he told me.
“I Was Devastated”: Tim Berners-Lee, the Man Who Created the World Wide Web, Has Some Regrets “For people who want to make sure the Web serves humanity, we have to concern ourselves with what people are building on top of it,” Tim Berners-Lee told me one morning in downtown Washington, D.C., about a half-mile from the White House. Berners-Lee was speaking about the future of the Internet, as he does often and fervently and with great animation at a remarkable cadence. With an Oxonian wisp of hair framing his chiseled face, Berners-Lee appears the consummate academic—communicating rapidly, in a clipped London accent, occasionally skipping over words and eliding sentences as he stammers to convey a thought. His soliloquy was a mixture of excitement with traces of melancholy. At 63, Berners-Lee has thus far had a career more or less divided into two phases. Berners-Lee, who never directly profited off his invention, has also spent most of his life trying to guard it. For the man who set all this in motion, the mushroom cloud was unfolding before his very eyes.
IBM's HR Chief Shares Best Advice On The Future Of Work When it comes to the forefront of the global human resources landscape, Diane Gherson is someone you want to know. As Chief Human Resource Officer at IBM, Diane has helped to revolutionize IBM over the past 13 years. Under her leadership, she has transformed global workforce outcomes through talent analytics and data, with special emphasis on predictive analytics. I interviewed Diane to learn her thoughts on several topics, including the future of work, how technology is disrupting human resources, how to build a lasting culture, the best way to give feedback, her favorite interview question, her best career advice and where she eats breakfast. Zack Friedman: It’s no secret that technological innovation brings rapid disruption. Diane Gherson: I see three major disrupters that are upending HR: Consumer-grade expectations. At the same time, the half-life of skills is shrinking, and so employees need to continue to learn at an exponential rate. Diane Gherson: It’s a two-way conversation.