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Work in Transition

Digital technologies are changing the nature of the jobs we do. What does that mean for the future of work?
September 28, 2015

About five years ago, machine learning reached a point where software could, with guidance from senior lawyers, effectively take over the time–intensive task of legal discovery, in which one party in a lawsuit combs through its documents to determine what it must show to the other side before trial.

This is a job that junior lawyers, paralegals, or—increasingly—less expensive contract lawyers had traditionally done, and some fretted that the change might be just the first step in the computerization of the law. But while machine learning does well with structured tasks like searching for relevant words, handling documents similar to others already identified, and even reconstructing simple summaries of a baseball game, it is far less adept at constructing something like a legal memo, where persuasiveness can rely on developing novel arguments, explains economist Frank Levy, an MIT professor emeritus who, with Dana Remus, a professor at the University of North Carolina School of Law, is researching computers’ impact on the practice of law.

“There’s much less structure in a legal memo, which is trying to figure out a strategic approach to an argument,” says Levy, who coauthored (with Harvard professor Richard Murnane) an influential book, The New Division of Labor, about how computers are changing employment and the job market. Adds Levy: “You are putting a premium on innovation.”

It’s likely that work done by humans will increasingly involve innovative thinking, flexibility, creativity, and social skills, the things machines don’t do well. In a recent study on automation from the University of Oxford, researchers tried to quantify how likely jobs are to be computerized by evaluating how much creativity, social intelligence, and dexterity they involve. Choreographers, elementary school teachers, and psychiatric social workers are probably safe, according to that analysis, while telemarketers and tax preparers are more likely to be replaced.

Most professions won’t go the way of the telemarketer, but the work involved is likely to migrate toward the tasks humans are uniquely skilled at, with automation taking over tasks that are rules-based and predictable.

How jobs are evolving in this new model of work is the big question this report seeks to examine.

In addition to affecting the type of work we do, digital and mobile technologies are changing how we do it, where we do it (at home or remotely), and who our competition is. At Upwork, a platform that connects freelancers with jobs, 50 percent of corporate customers are based in the United States, but only 20 percent of the workers are. Opening up a global talent competition could make it harder to earn high wages.

A growing number of platforms like Upwork, TaskRabbit, Uber, Airbnb, and others that connect freelancers to clients are creating a new type of labor market, something consultant Sangeet Paul Choudary calls “networked work.” In this world, workers are responsible for their own development and assume many of the risks employers once bore. They depend on the platform for business, but they also have the ability to develop a reputation based on client satisfaction.

This networked model is disruptive enough to have led to riots in Tianjin, China, where taxi drivers are fighting the arrival of Uber and the bite it has taken out of their income. The people who drive for Uber are largely part-timers looking to make a little extra money. Uber customers in China take nearly one million rides a day, the company says, and management is investing more than $1.1 billion to expand into 100 more cities this year. The job of driving cars has not gone away, but the way that work is done is changing, and the transition is not painless.

Tim O’Reilly, CEO of O’Reilly Media, has recently been writing about how technology can both create new types of jobs and improve the quality of work. Mobile and sensor technologies could support health workers and help elderly people stay in their homes, for example, while machine learning could help doctors make decisions.

Some jobs will surely be automated out of existence, but technology has the potential to create new jobs as well.

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