Future of Work @future-of-work - Tumblr Blog

(An earlier version of this story ran online.)

Max Nanis’s website prominently features about two dozen head shots of the skinny, scruffy 22-year-old Southern Californian with his shirt off. At the top of his “About” page, there’s a personalized contact number (936-CALL-MAX) and a link to 10X Management, his professional representation. It looks like the résumé of an actor, seemingly pitched for casting directors and producers—but Nanis’s background is in computational biology. He’s a coder, part of a generation of programming hotshots starting to view themselves more like Hollywood talent than bit jockeys.

Nanis has his agent at 10X Management working to find him the best freelance programming gigs. Launched about a year ago as a dedicated agency for software developers, 10X now represents more than 30 people, taking a 15 percent cut of its clients’ earnings from each assignment. In exchange for that fee, 10X promises to help guide a programmer’s career development, negotiate with employers for better compensation, and handle the mountain of associated paperwork. “We deal with the necessary evils of being a freelance coder so they don’t have to,” says Altay Guvench, one of the management firm’s founders.

After graduating from Harvard in 2003, Guvench went to Silicon Valley and started a user-generated trivia website. When the site fizzled out a couple years later—“It was a side project that got out of hand,” he says—Guvench became a freelance coder. The flexible lifestyle left him with time to pursue his other love, music. While he was hopping in and out of bands, Guvench ran into Rishon Blumberg and Michael Solomon, a pair of musician managers best known for guiding John Mayer from playing bars to packing stadiums. “Their job is to do the business bulls- - - for these artists,” says Guvench. “So, in this weird experiment, I hired them to act as my agent for freelance programming.”

The experiment worked: Blumberg and Solomon got Guvench consistent work that paid well. “Friends of mine started seeing I was happier,” Guvench says. “They started asking how they could get in on it.” With Blumberg and Solomon, Guvench—who gave up coding full time—started an agency in January 2012 dedicated to representing software engineers. While his two partners lead the negotiations with companies, Guvench looks for talented coders. He reviews code samples submitted by would-be 10X clients before they get a face-to-face interview with him or another partner. If they pass muster, the agency tries to match their skills to a particular company’s needs. 10X wants to build a reputation for having A-list coders on speed dial so startups turn to the company for pickup programming whenever they need it. “We want to be the Rolls-Royce or Apple,” says Guvench.

At first blush, 10X Management sounds a lot like a temp agency or a headhunting service. Both partners and clients say 10X representation is more than that. San Diego-based coder Nanis recalls Solomon spending a week negotiating with one company to secure top rates and more detailed terms about what he’d be expected to produce within a certain time. The process saved Nanis from having uncomfortable conversations. “I don’t want to talk to a business manager, I want to talk to the technology team,” he says. It’s common for freelance coders in big cities to earn $75 to $125 per hour these days; 10X clients’ hourly rates have been pushing as high as $300, enough that they’re not looking for permanent jobs, Guvench says. “They have doubled and even tripled my rate sometimes,” says Nanis.

10X also spreads work among its clients to ease the feast-or-famine side of freelancing. Clients credit it with building a host of tools that help them pick jobs. One program tracks payment rates for jobs and cross-references that data with the time taken to complete the assignments; another app fills in contracts and provides time sheets. And then there’s coaching, as 10X tries to find what people like to do and where they want to take their careers. “They advise us on how to present ourselves online and just get really involved in the relationship,” says Sam Kaufman, a freelance iOS developer.

While some hiring managers have been taken aback by the idea of dealing with an agent, there’s a big need for strong programmers, and companies want people who can get things done. “It takes months to find a good, full-time hire,” says Richard Price, chief executive officer at Academia.edu, which provides a marketplace for academic papers. “The 10X guys are like premium talent that you bring in in the meantime who are maniacally focused and bash things out.”

Some people see coders with agents as another sign that Silicon Valley is overheated. Bert Nieves, a freelance coder for much of the last 15 years, remembers a few agents popping up in the 1990s. During the dot-com boom years, he says, “I would go to trade shows with my own rate negotiator,” but that practice sputtered out during the subsequent collapse. Still, Nieves says the core idea has staying power. “My friends just want to code and hate all the negotiations,” he says. “The need is there.”

The bottom line: A former freelance programmer has teamed with entertainment-industry agents to help other coders navigate the business world.

Vance is a technology writer for Bloomberg Businessweek in Palo Alto, Calif. Follow him on Twitter @valleyhack.

In this week’s New Yorker, James Surowiecki considers one theory for the recent and drastic decline in the U.S. labor force. More and more Americans mightbe working off the books, in informal jobs that aren’t counted by statistical agencies:

Psst, want a job?

Bernard Baumohl, an economist at the Economic Outlook Group, estimates that, based on historical patterns, current retail sales are actually what you’d expect if the unemployment rate were around five or six per cent, rather than the 7.6 per cent we’re stuck with. The difference, he argues, probably reflects workers migrating into the shadow economy.

“It’s typical that during recessions people work on the side while collecting unemployment,” Baumohl told me. “But the severity of the recession and the profound weakness of this recovery may mean that a lot more people have entered the underground economy, and have had to stay there longer.”

This “underground economy” could include anything from illicit activities — selling drugs, say — to off-the-books jobs in things like construction. There are plenty of examples of the latter: Bloomberg recently interviewed an unemployed woman who walks neighborhood children to their bus for $2 per kid. Surowiecki cites a study finding that “between eighty and ninety-seven per cent of nannies were paid under the table.” And so on.

But those are anecdotes. Is there any hard data on the underground economy? Some. A 2011 paper (pdf) Richard Cebula and Edgar Feige estimated that as much as “18-19 percent of total reportable income is not properly reported to the IRS.” That’s as much as $2 trillion in underground economic activity, with about $500 billion in taxes that aren’t being paid to the government.

And here’s another suggestive piece of evidence that the shadow economy has been growing. The amount of U.S. currency in circulation has been soaring in the last six years, from $803 billion in 2007 to $1.18 trillion in March. Some of that reflects growing overseas demand for dollars. But some of it could reflect growth in unreported economic activity in the United States — people getting paid under the table in cash, say.

If the shadow economy is in fact growing, that has upsides and downsides. It’s certainly a good thing that people are finding ways to survive during a brutal downturn. But it’s yet another sign that the formal economy is utterly failing to create enough jobs for everyone.

SUMMARY:

One of the biggest drivers for LinkedIn’s business isn’t the consumer-facing side that you see — it’s the set of tools the company provides professional recruiters to match people with jobs. And the company is using data and technology to improve those tools.

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If LinkedIn has become the quiet success of the major social web companies, LinkedIn’s Recruiter page is the quiet success — and cash machine – within the company. And a brand new feature shows how the company is turning your professional data into a gold mine for recruiters.

LinkedIn’s “talent solutions” service, which gives recruiters and hiring managers the ability to post job ads and hunt for candidates, is the fastest-growing and most profitable portion of LinkedIn’s business. The talent solutions homepage saw an update last week that involved several design changes, but it was the addition of the “People You Might Want to Hire” tool that’s sheds the most light on how LinkedIn makes money.

At this point, most professional people are at least aware of LinkedIn, and with the company boasting 200 million registered users, a good number of people now have profile pages listing their work experience and other relevant information on the social networking site. But the consumer-facing side of LinkedIn that you might see is not the portion of the company that brings in the most revenue — or, at least not directly.

The talent solutions portion of LinkedIn brought in 53 percent of the company’s revenue last quarter. The basic service allows corporate recruiters and human resources employeees to post job ads for the company, search for relevant candidates, track responses, and monitor people they might like to hire (yes, a recruiter can put an alert on your profile and know when you make updates or switch jobs.) Companies pay for access to those recruiting features, and the more accurate the data LinkedIn can provide, the more value the companies will derive from the service.

The new feature on the Recruiter page is an intelligent recommendation engine that suggests to recruiters people they might want to hire. It sounds simple enough, and with similar features all over sites like Facebook and Twitter, maybe not so novel. But the feature is huge for LinkedIn on the consumer side already, where the company reports that 50 percent of job seeker engagement comes from the recommended jobs tool, with the other 50 percent coming from people typing into the search bar. Users who are actively looking for jobs might be willing to put in search terms. But people who aren’t actively looking to switch jobs — which LinkedIn estimates is about 80 percent of the current workforce — are far less likely to search.

“Recommendations have fundamentally changed the trajectory of Linkedin.com,” said Parker Barrile, head of product for talent solutions, in an interview this week. “The recommendations technology that suggests things for members totally change the game. Because we’ve realized how important it is not to expect consumers to actively search for things.”

My colleague Derrick Harris recently wrote about the engineering shift at LinkedIn over the past five years that now allows the company to put significant resources behind engineering projects like recommendations, and Barrile said that refining and perfecting the suggestions has become critically important.

“We’ve invested a lot into the technology that works on those recommendations,” he said. “All of these recommendation technologies learn from the way users interact with them. And LinkedIn’s recommendation technologies have become especiallly responsive because they’re so important to the business.”

The “People You Might Want To Hire” tool takes into account past behavior on the part of the recruiter, as well as data signals from within the job ad, to put together a list of candidates who might be a fit based on a variety of signals. For instance, let’s say you’re an tech company looking to hire for a PR position. The tool won’t just surface people working in technology PR. Instead, it might surface people working in technology who list writing and editing as their skills, or have a number of endorsements for communication or working with a team. Or, let’s say you’re hiring for a venture capital position in San Francisco — the system might also suggest relevant candidates from New York, since it knows people in venture capital are likely to move between the two cities.

Potentially creepy if you start getting a lot of messages from recruiters asking you to move to New York? Maybe. But for people who end up with job offers out of the process, there’s a strong upside to that technology.

Here’s one big reason why America’s unemployment crisis may be here to stay. Thanks to the lasting effects of the recession, there are currently 4.7 million workers who have been out of work for at least 27 weeks. And new research suggests that employers will almost never consider hiring them.

(Justin Sullivan – GETTY IMAGES)

Matthew O’Brien reports on a striking recent experiment by Rand Ghayad of Northeastern University. He sent out 4,800 fake resumes at random for 600 job openings. And what he found is that employers would rather call back someone with no relevant experience who’s only been out of work for a few months than someone with more relevant experience who’s been out of work for longer than six months.

In other words, it doesn’t matter how much experience you have. It doesn’t matter why you lost your previous job — it could have been bad luck. If you’ve been out of work for more than six months, you’re essentially unemployable. Many companies won’t even consider you for a job. Here’s what this looks like in chart form:

This jibes with earlier research (pdf) by Ghayad and William Dickens showing that the long-term unemployed are struggling to find work no matter how many job openings pop up. And it dovetails with anecdotes that workers and human resource managers have been recounting for years now. Many firms often post job notices that explicitly exclude the unemployed.

Now, it’s unclear whether companies are irrationally discriminating against the long-term unemployed or whether they have good reason for screening out these applicants. Privately, many employers worry that someone who’s been out of work for six months “may have outdated skills, or may be a short-timer who is desperate enough to take any work now but will leave when something better comes along.”

Either way, the broader trend is having disastrous effects. As my colleague Ylan Mui reported earlier, this is partly why Boston Fed President Eric Rosengren worries that our cyclical unemployment problems could become structural and long-lasting. The recession threw many people out of work. Those who stayed unemployed for six months or more can’t even get a callback for jobs. Their skills erode further. Eventually they drop out of the labor force. That all weighs down on America’s long-term growth prospects.

So is there a remedy? Dozens of states have been considering legislation that would make it illegal to discriminate against the long-term unemployed. Some proposals would even allow unsuccessful applicants to sue under the same discrimination laws that apply to race or gender bias. These proposals have plenty of critics. But it’s also unclear whether they would have much impact. New Jersey has had a law of this sort in place since 2011, and only one company has been cited for violating it to date.

The Obama administration, for its part, has proposed a few other ideas, including training programs and tax credits for businesses that hire the long-term unemployed. (The latter were even included in the American Jobs Act that Republicans blocked in Congress.) Yet economists have argued that while these programs might help at the margins, they won’t necessarily bring down the overall unemployment rate. For instance, a company might just hire a subsidized worker over someone else.

It’s worth noting, as Matt Yglesias points out here, that long-term unemployment was a major structural problem after the Great Depression too. But as this old essay by Richard Jensen suggests, it took World War II to finally solve the problem: “The war, by removing millions of prime men from the labor market, by restructuring the work process, by subsidizing wages, and by massive retraining, finally gave the private sector the methods and the incentives to rehire the hard-core.”

That’s not really an option today, but it underscores a bleak fact about the recession. When the labor market stays weak for years on end, the damage becomes long-lasting — and extremely difficult to reverse.

US legislators are expected to release a draft of a comprehensive immigration-reform bill this week. But right from the start, one of its core provisions—a compromise agreement between labor and business on guest workers—is inherently flawed, according to two labor economists.

The bill also includes provisions that provide a path to citizenship for 11 million undocumented immigrants and improve border security. But the most important economic test is whether it will allow the US to meet its labor needs without forcing workers into the underground economy. The last big immigration reform in 1986 failed that test—and Congress seems ready to repeat its mistakes.

Politicians outsourced negotiations over guest workers to the business lobby, which advocates for large numbers of guest workers and little regulation for the businesses that need them, and trade unions, which want to protect American workers from cut-rate competition. They came up with a deal for a “W Visa” that would allow 20,000 temporary workers per year to come to the US for the first four years, then increase the cap to 75,000 per year and eventually as many as 200,000 per year.

The problem is that the US economy will require many more workers than that, even if high unemployment might mask this reality today.

In a forthcoming policy brief, economists Michael Clemens and Lant Pritchett argue that more low-skilled jobs will be created in the US between 2010 and 2020 than there will be workers to fill them. Using a Bureau of Labor Statisticsforecast of occupational demand, they broke down jobs by skill level and whether workers could easily be replaced by automation or offshoring:

The bottom line: About 1.7 million new American workers between ages 25-54 will begin looking for jobs in the decade. But there will be demand for 1.6 million high-skilled workers—jobs like nursing, teaching and other professional work done face-to-face—and 3.6 million new low-skilled workers in sectors such as health care, food service, construction and janitorial services.

But wait, won’t people who are currently unemployed pick up the slack? That simply hasn’t happened during the recession, and there’s no reason to think it will change. For example, some skilled workers whose jobs have been outsourced don’t want to take low-skill jobs, and some older unemployed workers have opted for Social Security’s disability pensions.

So, filling all of the new jobs that will be created this decade will be a challenge. Ideally, Clemens says that lawmakers would simply increase the number of green cards issued. But since that’s politically unfeasible, the remaining options are to fill the gap with undocumented immigrants, create a sufficiently large guest worker program, or simply leave the jobs unfilled.

Critics of guest worker programs worry that they will drive down overall wages, but the research by and large suggests that any job displacement or lowering in wages is outweighed by the benefits that the immigrants bring, including this report from Alan Krueger, now the White House’s top economist.

What these critics really miss, Clemens and Pritchett write, is that new low-skilled workers help create new jobs—not only by spending the wages they earn but also by creating demand for more managers, and by protecting industries (particularly tough to harvest crops like apples, cucumbers, lettuce, and melons) that couldn’t exist without cheap labor.

What worries Clemens most of all is that the guest worker compromise doesn’t appear to be looking closely at the United States’ labor needs in the future.

“It was not from a detailed economic analysis of the needs of the country,” he says. “To enshrine in law that the economy in no circumstance will ever need more than 200,000 a year is a strategy for guaranteeing that there will be large numbers of irregular workers in the future again.”

from the I-for-one-welcome-our-new-fedora-clad-robotic-overlords dept

This may seem like the sort of statement usually delivered by an overblown narrator as rockets and lasers go zooming* by, but here goes: In the world of journalism, the future is now! Granted, it's the kind of future that often makes waves in the present and raises at least as many questions as it answers, but if you wanted a bright, problem-free future, you'd have to travel back to the divergence point somewhere between Philip K. Dick and The Jetsons... and then eliminate the dystopians. *Yes, I realize lasers don't make noise or "zoom" by, but that hasn't prevented George Lucas from becoming insanely rich, has it? But you can't, so here we are, discussing journalism... by robots! [INS FANFARE/LASER NOISES]

Journalist Ken Schwencke has occasionally awakened in the morning to find his byline atop a news story he didn’t write. No, it’s not that his employer, The Los Angeles Times, is accidentally putting his name atop other writers’ articles. Instead, it’s a reflection that Schwencke, digital editor at the respected U.S. newspaper, wrote an algorithm — that then wrote the story for him. Instead of personally composing the pieces, Schwencke developed a set of step-by-step instructions that can take a stream of data — this particular algorithm works with earthquake statistics, since he lives in California — compile the data into a pre-determined structure, then format it for publication. His fingers never have to touch a keyboard; he doesn’t have to look at a computer screen. He can be sleeping soundly when the story writes itself.

This isn't exactly new news. (Then again, neither is the morning paper, but that's a discussion for another time...) Algorithmic story generation has been around for a few years now, with Narrative Science leading the field. A couple of years ago, Narrative Science was the story, rather than just the automated recap. George Washington University's website had covered a GWU baseball game with a longish recap that only got around to mentioning the opposing pitcher's perfect game in theseventh (out of eight) paragraph. Speculators wondered if a bot was behind this "ignoring the forest for the trees" recap. Narrative Science's techies were highly offended and responded by producing two algorithmically-generated recaps -- one from the home team POV and a more neutral piece. The first concern with robo-journalism is often expressed by the journalists themselves: are we getting pushed out? Kristian Hammond, co-founder of Narrative Science, doesn't see it that way.

This robonews tsunami, he insists, will not wash away the remaining human reporters who still collect paychecks. Instead the universe of newswriting will expand dramatically, as computers mine vast troves of data to produce ultracheap, totally readable accounts of events, trends, and developments that no journalist is currently covering.

This is somewhat echoed by L.A. Times reporter Schwencke, who sees the algorithmic output as a boon for busy journalists.

Schwencke says the use of algorithms on routine news tasks frees up professional reporters to make phone calls, do actual interviews, or dig through sophisticated reports and complex data, instead of compiling basic information such as dates, times and locations. “It lightens the load for everybody involved,” he said.

Schwenke's "bot" is rather simple, functioning best with a limited dataset and a minimum of formatting. Narrative Science's output is a bit more complex, allowing customers to adjust the "slant" of the generated stories. Not only that, but the software can cop an attitude, if requested.

The Narrative Science team also lets clients customize the tone of the stories. “You can get anything, from something that sounds like a breathless financial reporter screaming from a trading floor to a dry sell-side researcher pedantically walking you through it,” says Jonathan Morris, COO of a financial analysis firm called Data Explorers, which set up a securities newswire using Narrative Science technology. (Morris ordered up the tone of a well-educated, straightforward financial newswire journalist.) Other clients favor bloggy snarkiness. “It’s no more difficult to write an irreverent story than it is to write a straightforward, AP-style story,” says Larry Adams, Narrative Science’s VP of product. “We could cover the stock market in the style of Mike Royko.”

This leads to the ethical quandary presented by the use of bots. Is robo-generated journalism really journalism, and is the use of algorithms a betrayal of readers' trust, especially when a familiar name is on the byline? If factual errors are discovered, does the blame lie with the software, or with the journalist who agreed to let the article "write itself?" The answer here isn't simple (and the question likely isn't even fully formed yet), but the key is transparency.

“People are already reading automated data reports that come to them, and they don’t think anything of it,” said Ben Welsh, a colleague of Schwencke’s at the Times. Welsh says that responsibility for accuracy falls where it always has: with publications, and with individual journalists. “The key thing is just to be honest and transparent with your readers, like always,” he said. “I think that whether you write the code that writes the news or you write it yourself, the rules are still the same.” “You need to respect your reader. You need to be transparent with them, you need to be as truthful as you can… all the fundamentals of journalism just remain the same.”

Questions involving intellectual property are also raised, although they aren't discussed in these articles. Who holds the copyright on the generated articles? In Schwencke's case, these rights are likely retained by the L.A. Times. In the case of Narrative Science, it's probably defined by contractual terms with the end user. Once the contract is up, the generated articles' copyright reverts to the end user. Schwencke's homebrewed algorithm is a different IP animal. If he switches papers, does he retain the right to the "bot?" Or is that algorithm, developed while employed with the L.A. Times, considered a "work for hire," and thus, the paper's property? Arguably, his algorithm is an extension of him, covering his area of expertise and designed to emulate his reporting. What if Schwencke generates a similar piece of software for his new employer? Would he be permitted to do this, or would this be prevented by additions to "non-compete" clauses? Is it patentable? The more ubiquitous "robo-journalism" becomes, the more issues like these will arise. Hopefully, IP turf wars will remain at a minimum, allowing for the expansion of this promising addition to the journalist's toolset. With bots handling basic reporting, journalists should be freed up to pursue the sort of journalism you can't expect an algorithm to handle -- longform, investigative, etc. This is good news for readers, even if they may find themselves a little unnerved (at first) by the journalistic uncanny valley.

Is Job Polarization Holding Back the Labor Market?

Stefania Albanesi, Victoria Gregory, Christina Patterson, and Ayşegül Şahin More than three years after the end of the Great Recession, the labor market still remains weak, with the unemployment rate at 7.7 percent and payroll employment 3 million less than its pre-recession level. One possibility is that this weakness is a reflection of ongoing trends in the labor market that were exacerbated during the recession. Since the 1980s, employment has become increasingly concentrated among the highest- and lowest-skilled jobs in the occupational distribution, due to the disappearance of jobs focused on routine tasks. This phenomenon is called job polarization (see Autor et al. [2003],Acemoglu and Autor [2010], Jaimovic and Siu [2011], and Abel and Deitz [2011]).

To study job polarization, it’s useful to put occupations into different task groups, with each occupation categorized as either routine or nonroutine. An occupation is routine if its main tasks require following explicit instructions and obeying well-defined rules. These tend to be middle-skilled jobs. If the job involves flexibility, problem solving, or creativity, it’s considered nonroutine. Job polarization occurs when employment moves to nonroutine occupations, a category that contains the highest- and lowest-skilled jobs. The chart below shows the employment share of routine and nonroutine jobs in the United States starting from 1976. The share of routine occupations declined from 60 percent in 1976 to 40 percent in 2012, resulting in job polarization. It’s useful to further classify occupations into cognitive and manual categories based on the amount of mental or physical activity required of the job: cognitive jobs require mostly mental activity; manual jobs, mostly physical. For instance, nonroutine cognitive jobs are generally high-skilled and include management, technical, and healthcare workers, such as doctors and engineers. Manual nonroutine occupations are generally low-skilled and include service and protection workers, such as waiters and security guards. Cognitive-routine jobs include sales and office workers, such as sales agents and office assistants. Manual routine occupations include construction workers, mechanics, and machine assemblers. As the chart below shows, the share of routine jobs has been steadily decreasing for the cognitive and manual categories since the 1980s, and the decline accelerated during the 1981-82 and 2007-09 recessions. Most of the rise in the employment share of nonroutine jobs reflects the increase in cognitive nonroutine occupations. The rise in job polarization during the most recent labor market slowdown can potentially account for why the labor market recovery has been sluggish. In particular, it can explain the persistently high unemployment rate and the rise in long-term unemployment. If this is the case, we should see weakness in the segments of the labor market that involve routine jobs. We examine this idea by looking at different labor market indicators for different occupation groups in the current labor market downturn. (See interactive charts for indicators for workers from different occupations at a more disaggregated level.) Foote and Ryan (2012) provide a detailed analysis of all recessions starting from 1976. Their results suggest that most of our findings for the recent downturn also apply to the earlier recessions. Unemployment The following chart displays the percentage change in the unemployment rate for routine and nonroutine occupations during the most recent slowdown. We start from the trough of the aggregate unemployment rate in May 2007, and examine a recession and a recovery window. Between May 2007 and May 2010, the unemployment rate for routine occupations rises by 130 percent, while it rises by 103 percent for nonroutine occupations. However, this behavior is matched by a more sizable and rapid decline in the unemployment rate for routine occupations relative to nonroutine in the recovery. This suggests that the larger increase in the unemployment rate for routine occupations during the recession reflects mostly cyclical factors. For example, construction and manufacturing sectors, which typically include routine jobs, had substantial employment declines during the recession. If job polarization were responsible for the sluggish recovery, we’d expect the unemployment rate among routine jobs to fall more slowly than the rate among nonroutine jobs. The chart shows that this isn’t the case. Long-term unemployment. If job polarization is causing long-term unemployment, we should expect long jobless spells to be more common among workers with routine occupations. We see from the next chart that this isn’t supported by the data—the duration of unemployment spells increased significantly during the recession for all occupation groups, and has remained high for all groups. This suggests that the job-finding prospects of the unemployed in routine occupations aren’t any worse than prospects for those in nonroutine occupations. Job-finding rates. The main reason why the unemployment rate has been persistently high is the slow recovery of the rate at which unemployed workers find jobs. Job polarization can potentially explain this phenomenon if workers displaced from routine jobs have more difficulty finding employment than those displaced from nonroutine jobs. However, the chart below shows that this isn’t the case, and that all job-finding rates are recovering similarly. Occupational Transitions If job polarization is depressing the prospects of the unemployed, we should see more occupational transitions from routine to nonroutine jobs after the recession. If people were unable to find routine jobs, they’d be incentivized to retrain and search for work in nonroutine occupations. The table below shows that this isn’t the case—in both the pre-recession and recession periods, only 22 percent and 23 percent, respectively, of unemployed workers moved from routine to nonroutine jobs. This means that three-quarters of unemployed workers in routine occupations who found jobs remained in routine occupations. Our findings show that while job polarization is an important ongoing trend in the labor market, it’s not a key contributor to the sluggish labor market recovery. Our analysis suggests that the weakness in the labor market is broad based and not limited to a certain segment of the market. The unemployment rates, average duration of unemployment, and the job-finding rates for workers from different occupations can be analyzed in theseinteractive charts.

Google Engineer Says Vietnamese 11th Graders Know Enough Computer Science to Pass Their Interview Process

With 1 million more jobs than there are computer science students anticipated by 2020, learning computer programming is as essential for the 21st century workforce as learning to read or write. But here in the United States only 10 percent of K-12 schools even offer computer science classes, which means our kids aren't being set up for success.

That's a far cry from what's happening in Vietnam. Google engineer Neil Fraser, who works in the company's education department, recently headed there to check out how they're teaching computer science to students and the difference is pretty astounding. Fraser writes on his siteNeil's News that Vietnamese kids begin basic programming lessons in second grade and in third grade, they start learning how to use Microsoft Windows and how to type. Depending on an individual school's access to technology, students here in the United States might learn the same thing at that age. But by fourth grade it's clear that American and Vietnamese kids are being put on different paths.

"By grade 4," writes Fraser, Vietnamese students, "start programming in Logo. Starting with sequences of commands, then progressing to loops." And "By grade 5 they are writing procedures containing loops calling procedures containing loops," he says.

Fraser also says 5th graders in Vietnam are so skilled, they can do the same programming 11th graders in the U.S. can do, which means that the 11th graders in Vietnam significantly outpace their American peers. Indeed, they're skilled enough, says Fraser, to succeed in Google's interview process.

So what's the problem here in the U.S. with getting coding taught in schools? Fraser says:

"School boards fight to keep CS out of schools, since every minute spent on CS is one less minute spent on core subjects like English and math. The students' test scores in these core subjects determine next year's funding, so CS is a threat.

Teachers often refuse to teach real CS because more often than not they don't understand it. Instead, they end up teaching word processing and website construction, while calling it CS.

Parents often oppose CS classes since the grade has no direct benefit on their child's academic prospects. This is compounded by a lack of understanding of the difference between their child playing video games and their child writing video games.

Students intentionally tune out of CS class since there are few things worse in American high school than being labelled a nerd."

Fraser says what he sees "in America is a prefect storm of opposition from every level." As a result, Google's "been spending enormous resources with frankly minimal impact."

We should absolutely be lobbying for computer science's inclusion in the K-12 academic curriculum—last year parents involved in Coding for Kids in the U.K. did just that. But since bureaucratic wheels can turn slowly—and we don't even have enough educators who are trained to teach computer science in schools—using some of the free resources on the web is the way to go. Platforms like Code Year, which features short, game-based, interactive lessons are teaching novices enough coding to build a website or game in just four weeks.

Of course, teaching kids how to code doesn't mean that we have to expect that every child will grow up to be a programmer. But by not teaching the vast majority of students how to code, we're denying them the ability to make the choice to pursue working in computer science. What's clear is that if we don't step up and take action, American kids will be, for the most part, mere consumers of technology instead of innovators and creators who use it to solve the challenges facing their communities.

Click here to add learning to code to your GOOD "to-do" list.

Electronic circuit board image via Shutterstock

40% of America’s workforce will be freelancers by 2020

By Jeremy Neuner — March 20, 2013

Jeremy Neuner is the CEO and cofounder of NextSpace, a company that builds co-working communities. He is the co-author of the forthcoming book “The Rise of the Naked Economy” due out in July. Before starting NextSpace, Jeremy worked as a management and strategy consultant in Washington, DC.

Say so long to the rush hour commute. AP Photo/Reed Saxon

The debate over telecommuting that Yahoo has spurred raises an important issue, but it’s not simply about workplace flexibility or telecommuting, but rather the fundamental nature of work itself. By 2020, more than 40% of the US workforce will be so-called contingent workers, according to a study conducted by software company Intuit in 2010. That’s more than 60 million people.

We are quickly becoming a nation of permanent freelancers and temps. In 2006, the last time the federal government counted, the number of independent and contingent workers—contractors, temps, and the self-employed—stood at 42.6 million, or about 30% of the workforce. How many are there today? We have no idea since 2006 was the last year that the government bothered to count this huge and growing sector of the American workforce.

Following the recent economic downturn, the employment rate has recovered at a frustratingly slow pace, except in one area: temporary, contingent, and independent workers. Between 2009 and 2012, according the Bureau of Labor Statistics, the number of temporary employees rose by 29%. A survey of the 200 largest companies found that temporary workers represented, on average, 22% of their workforce, and that percentage is growing. Workers from all different industries (not just tech) are discovering that they’re able to be productive outside of the corporate office and without a long-term employer. At my company, NextSpace, we provide membership to contingent and independent workers from industries as varied as marketing, law, media, accounting, entertainment, construction, art, architecture, and healthcare, along with hundreds of programmers and developers.

The forces behind this sea-change are many: the rapid adoption of mobile technology, ubiquitous internet access, and a general sense of malaise powered by the vague yet nagging notion that we’re just not meant to work all day sitting in a cubicle. Add to that the waste of time, energy and brainpower that commuting engenders, and it becomes apparent that our definition of “workplace” will never be the same. It may seem like a tug of war between companies and workers, but in fact they share common goals: using technology and mobility to maximize productivity, innovation, and well-being.

Given these trends, companies need to proactively create what I call “approved workplace ecosystems” that will likely include the corporate campus, home office, co-working spaces, the corner coffee shop, client/vendor sites, or any place with a decent WiFi or 4G signal. But a real ecosystem is about more than just a collection of places. It’s about the norms, the culture, and the vibe that knit these places together.

At NextSpace, we foster a culture and community among these independent disaggregated workers by creating common ground. Brown bag lunches and informal lectures bring people together over ideas. Member happy hours bring people together over food and drink. And when all else fails, our community curators often literally drag people together based on common personal or professional bonds (the community March Madness pool works, too!).

Traditionally, being self-employed used to come with a social stigma; you were self-employed if you couldn’t get a “real job.” Work was inconsistent and so was the pay. Today, the opportunities for contingent, project-based work are exploding, as is the development of tools that allow people to work independently across industries like software, design, marketing, legal services, architecture, healthcare, and engineering.

As this trend accelerates, problems will arise since the current system is heavily geared toward people working in conventional ways. Those who have full- or part-time work with established companies receive a regular paycheck, employer-sponsored benefits (if they’re lucky), and get a tidy IRS W-2 form at the end of the year for taxes. What people find when they leave the system is a confusing, byzantine, and slightly scary world of health insurance, taxes, pensions, and regulations.

Like it or not, companies and the systems that serve them are going to have to change because the workforce evolution is already underway.

We welcome your comments at [email protected].

Want Productive Employees? Treat Them Like Adults

For more than a decade now, I've struggled to define what fuels the most sustainably productive work environment—not just on behalf of the large corporate clients we serve, but also for my own employees at The Energy Project. Perhaps nothing I've uncovered is as important as trust.

Much as employers understandably hunger for one-size-fits-all policies and practices, what motivates human beings remains stubbornly complex, opaque, and difficult to unravel. Perhaps that's why I felt so viscerally the shortsightedness and futility of Marissa Mayer's decision to order Yahoo employees who had been working from home to move back to the office, and Hubert Joly's to do the same at Best Buy.

Here's the problem: Employees who want to game the system are going to do so inside or outside the office. Supervising them more closely is costly, enervating, and it's ultimately a losing game. As for highly motivated employees who've been working from home, all they're likely to feel about being called back to the office is resentful—and more inclined to look for new jobs.

At its heart, the problem for Mayer and Joly is lack of trust. For whatever reasons, they've lost trust that their employees can make responsible adult decisions for themselves about how to best get their work done and add value to the company. Distrust begets distrust in return. It kills motivation rather than sparking it. Treat employees like children and you increase the odds they'll act like children. You reap what you sow—for better and for worse.

As an employer, I stay focused on one primary question about each employee: What is going to free, fuel, and inspire this person to bring the best of him or herself to work every day, most sustainably? My goal is to meet those needs in the best ways I can, without undue expense to others.

In the end, I'm much less concerned with where people do their work than with the value they're able to create wherever they happen to do it. The value exchange here is autonomy (grounded in trust) for accountability.

As CEO, I myself work from home for an hour or two in the mornings most days because it's quiet and free of distractions. I find it's the best way for me to get writing and other high-focus activities accomplished, and I know that's true for many other business leaders.

One of the senior members of our team is a 35-year-old woman with three children under the age of nine. She lives 90 minutes from work. I'd love to have her at our offices every day, because I enjoy being able to interact with her around issues as they arise. I also just like having her around as a colleague.

But to make that possible she'd have to invest three withering hours commuting each day—a huge cost, not just in time, but also in energy, for work and for her family. Demanding that she make that trip every day would only prompt progressive fatigue, resentment, and impaired performance.

Instead, we settled from the start on having her come to the office two days a week, which is when we schedule our key meetings. Those days also provide time for spontaneous brainstorming of ideas across the team.

Another one of our team members, a woman with two teenage kids, travels frequently in her role. When she gets back from trips, she typically works from home the next day—both to recover, and to have more time for her family.

Two of our other staffers—one male and one female—work mostly at the office out of personal preference, but also have young kids and work from home on some days when their kids are on vacation, or get sick.

Two younger, married team members recently requested permission to move to Amsterdam for eight months—for no other reason than they wanted to experience another culture. For a moment, I bridled. But since technology makes it possible for them to do their jobs from anywhere, we were able to make it happen. They agreed to work during our regular office hours, and to visit our office for a week every two months. So far it seems to be working seamlessly.

Every one of these people is highly productive. I do have moments when I find myself wishing all of our team members were in the office more, and even wondering what they're doing when I haven't heard from them.

When those feelings arise, I take a deep breath and remind myself that my colleagues are adults, capable of making their own decisions about how best to get their work done, and that all good relationships involve some compromise.

It gets back to trust. Give it, and you get it back. In over a decade, no employee has ever chosen to leave our company. The better you meet people's needs, the better they'll meet yours.

The U.S. job market is slowly improving, and most economists expect that gradual recovery to continue this year. Yet one of the most disturbing trends of the recession is still very far from being reversed. America’s middle-class jobs have been decimated since 2007, replaced largely by low-wage jobs.

A recent presentation from the Federal Reserve Bank of San Francisco lays out the situation clearly. The vast majority of job losses during the recession were in middle-income occupations, and they’ve largely been replaced by low-wage jobs since 2010:

Mid-wage occupations, paying between $13.83 and $21.13 per hour, made up about 60 percent of the job losses during the recession. But those mid-wage jobs have made up just 27 percent of the jobs gained during the recovery.

By contrast, low-wage occupations paying less than $13.83 per hour have utterly dominated the recovery, with 58 percent of the job gains since 2010. (This data all comes from anearlier report (pdf) from the National Employment Law Project.)

That’s put downward pressure on wages: “[M]any middle-class workers have lost their jobs and, if they have been able to secure new employment at all, find themselves earning far lower wages post-recession,” the San Francisco Fed notes. ”[O]n average over the next 25 years, these workers will earn 11% less than similar workers who retained their jobs through the recession.”

The jobs of the future? (Washington Post)

So what types of low-wage jobs are we talking about? Nearly 40 percent of the jobs gained since the recovery began — about 1.7 million — have come from three low-wage sectors: food services, retail, and employment services (that last is a sweeping category encompassing jobs like office clerks and sales representatives).

As the San Francisco Fed presentation notes, just four low-wage sectors now make up nearly 12 percent of the workforce in 2011: retail sales, cashiers, office clerks, and food preparation and service workers. ”[T]hese occupations are crucial to the support and growth of major industries across the country, but many of these workers do not earn enough to adequately support their families, even at a subsistence level.”

By contrast, many mid-wage industries, such as construction, manufacturing, insurance, real estate and information technology, have either stagnated or grown too slowly to make up for their pre-recession losses.

What’s more, the NELP report notes, budget cuts to state and local governments have taken away a major source of mid- and higher-wage jobs. And a separate chunk of middle-wage jobs — including carpenters, painters, and electricians — are still waiting for the U.S. housing market to recover.

This isn’t a new phenomenon: Over the past decade high-wage and low-wage jobs have been growing at a decent clip. But that middle rung continues to get hollowed out. Mid-wage jobs endured a major drop after the 2001 recession, largely stagnated during the 2000s, and have now declined even further in the most recent downturn. (See this graph for a look at the historical trend.)

Are robots to blame? (Getty)

Economists have been debating the underlying causes of this growing divergence for years now. Some, such as Harvard’s Lawrence Katz and Claudia Goldin, argue that new technologies and machines are now displacing mid-wage jobs at the assembly line and elsewhere. Others, such as Larry Mishel of the Economic Policy Institute, point to explicitly political factors, from the decline of labor unions to trade liberalization to the dwindling minimum wage.

Yet whatever the cause, the hollowing-out of mid-wage jobs has been accelerating sharply during the recession. And if the trend continues, the NELP report notes, it’s very likely to exacerbate income inequality in the United States.

The San Francisco Fed presentation, for its part, spends some time discussing how to lift people out of that lower-middle-income rung — though it shies away from drastic ideas like raising the minimum wage or bolstering labor unions. Instead, there’s a lot of focus on vocational training for workers, which has had only mixed success of late:

[Business, banks, and nonprofit groups] noted that many unemployed [lower-middle-income] individuals, seeing few employment opportunities for which they are qualified on the job market, return to school to improve their qualifications. When students graduate from vocational training programs or community college coursework, however, they must compete with one another in a tight job market.

Respondents explained that some students do not graduate or complete their training programs before dropping out due to expenses, household demands, or other conflicts. Additionally, whether or not they have graduated, these students now have varying degrees of student debt, layered on top of existing debt accumulated while they were unemployed.

The presentation goes on to suggest a few other small-bore remedies, from affordable-housing programs to making job-training programs cheaper and easier. But there’s a larger trend taking place in the U.S. economy — in which low-wage jobs are displacing middle-wage jobs — that’s becoming increasingly difficult to fight against with small policy tweaks.

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