Do Robots Dream of Electronic Paychecks?

This week, I’m going to continue my year-end tradition of looking back at the tweets I’ve issued on Twitter in order to follow up on some and comment on the significance of others. (If you’re not already following me, my handle is @LaurenceShatkin.) But this week, I’m going to focus on a single trend that I’ve tweeted about numerous times: the growing use of robots.

In fact, if it were up to me to choose Time’s Person of the Year, I’d choose the robot. For example, this year I learned about a new trend in warehouses: using robots to pull merchandise off the shelves and bring it to the loading dock. Human forklift operators need not apply for these jobs. Robots are also threatening some jobs in the green career field of solar panel installation. Part of the reason this trend is accelerating is that technology is creating a generation of robots that are more deft and therefore more capable of doing work that until now has been done by hand. (“Fine motor control” takes on a different meaning when it refers to actual motors.) For example, a Philips Electronics factory in Holland is using robots to do the same delicate work—assembling electric shavers—that humans are doing in a Philips factory located in the Chinese city of Zhuhai. One of the biggest manufacturers in China, Foxconn (which assembles iPhones, among many other products), has announced plans to add up to one million industrial robots to its assembly lines inside of three years.

But despite these improvements, robots still can’t think as well as human workers do, and it seems unlikely that they will soon be able to make complex decisions or recognize nonroutine visual patterns as well as the human brain can. Job erosion in the United States has been slowed partly by this limitation on robots, combined with a limitation on foreign workers: much work in America needs to be done by on-site workers. But perhaps a perfect storm is coming that will overcome both of these obstacles: what one writer calls “the Avatar economy.”

If you’ve seen that movie, you saw how one of the characters remotely controlled a physical body, his avatar, to accomplish work that his disabled body could not do. In a way, we already have workers doing this when they control aerial drones for surveillance and for making kill shots in foreign countries. Why can’t that be done in reverse—by foreign workers—for civilian work tasks here? For example, some delicate surgery is now performed by robotic hands under the control of a physician who watches the progress of the operation through stereoscopic video cameras. I’ve seen this being done from across a room. Couldn’t this be done from across an ocean? In surgery, the major remaining barrier may be the few seconds of delay in response time, which could be critical in some situations. But for less life-and-death work tasks, it may become less expensive to hire a foreign worker to control an on-site robot.

It’s important to understand that not all robots are engaged in physical manipulation of objects. Robots are also making inroads into some American jobs that are concerned mainly with manipulating data. For example, “e-discovery” software is replacing lawyers and legal assistants by rapidly reading through reams of documents to find material that is relevant to a lawsuit or other trial. One California firm analyzed 1.5 million documents for the bargain-basement cost of less than $100,000. The software is sophisticated enough to go beyond keyword recognition and actually identify key concepts. You saw something similar happening if you watched the computer that bested the human opponent on “Jeopardy!” Less clever computers are working with numbers to make decisions that used to require human loan officers and tax accountants.

Machine translation has reached the point where you can easily ask Facebook to translate a posting made in a foreign language. One indication of where this is going was a demonstration this year by Microsoft researchers in which a computer translated someone’s spoken English into Mandarin with only a very short delay and, most remarkable of all, spoke the translation in a voice that sounded like that of the original speaker.

Fears about the Mayan apocalypse now seem rather quaint, and I’m not going to predict an imminent robotic apocalypse for American workers. But if you’re planning for a career with any longevity, you need to think about developing skills that robots will find difficult to master.

Researching an Occupation Before an Interview

In September, I blogged about the importance of researching the employer before you walk into an interview. This week’s blog is about researching the occupation for which you’ll be interviewed.

If you work with job-seekers who are still in school or recent graduates, you may have to impress on them the importance of researching the occupation that is their career goal. Here are some reasons to mention:

Question the interviewer might ask: “The most important work tasks are x, y, and z. Do you think you can do these tasks? Do you have a problem with any of these tasks?”
What you need to research about the employer: The most important work tasks
Advantage you gain: You can be ready with examples of your work or schooling that show you can do the work tasks. You’ll know whether the work tasks at this particular job are easier or harder than what’s typical.

Question the interviewer might ask: “On this job, the tools we use are x and y. Tell me about your experience using these.”
What you need to research about the employer: Typical tools and technologies
Advantage you gain: You can be ready with examples that show you are skilled with using these tools and technologies.

Question the interviewer might ask: “I’ve just described the work conditions here. Do you think you would be comfortable with them?”
What you need to research about the employer: Typical work conditions (indoor/outdoor, pressure, hours, travel, etc.)
Advantage you gain: You can decide whether the conditions at this particular job are better or worse than average.

Question the interviewer might ask: “Why do you want to work here? How do you see your future in this job?”
What you need to research about the employer: Future job trends
Advantage you gain: You understand what the future job opportunities will be with this type of employer. You can explain how you’ll serve future needs.

(What about how whether the employer pays a salary that’s appropriate for the occupation? You’ll need to know that eventually, when the interviewer offers you the job, but not for the initial interview.)

As you conduct research, for each question you investigate about the occupation, you’ll need to ask a corresponding question of yourself: specifically, “Am I ready for and comfortable with this aspect of the occupation?” Your answers to this question will help you be ready to decide whether or not the way the occupation is done at this employer suits you.

An exercise for conducting the research:
Start by looking at the work tasks. O*NET Online is an excellent resource for these inquiries. Search for the occupation and print out the Summary Report.

Make a Work Tasks Table. Divide a sheet of paper into three columns. In the first column, write each bulleted item on the Task list. In the middle column, make a mark to indicate whether you are ready for that task and comfortable with it. Use the right column for comments about the middle column:

• If you’re not comfortable with a task, explain how you think you might work around it.
• If you’re ready for a task, note how you learned it (training, work experience).
• If you’re not ready for a task, explain how you intend to learn it (on-the-job training, a future class, or maybe you consider it unimportant for the job opening you have in mind).

How to use the Work Tasks Table before a job interview:
Find out as much as you can about the work tasks for the particular job opening you will be interviewed for:

• If the job has been advertised, the advertisement probably mentions some tasks.
• If the job has not been advertised, you may be able to find out something about the tasks by word of mouth.
• In either case, you may be able to obtain a job description published by the employer. It will identify some tasks.

Compare the tasks of the particular job opening to the tasks listed in the table. On a paper pad, jot down some notes for the interview:

• Look at the tasks that you’re ready for and comfortable with.
  • If the particular job involves some of these tasks, be prepared to mention how you mastered these tasks (class, work experience).
  • If the particular job does not involve some of these tasks, be prepared to ask why not.
  • Look at the tasks that you’re not ready for.
    • If the particular job involves some of these tasks, be prepared to ask whether you can get help learning how to do them.
    • If the particular job does not involve some of these tasks, you may want to ask for confirmation that it doesn’t, although you should express your willingness to learn them eventually.
    • Look at the tasks that you’re not comfortable with.
      • If the particular job does not seem to involve some of these tasks, you may want to ask for confirmation that it doesn’t.
      • If you learn at the interview that the job does involve some of these tasks, be prepared to explain how you’ll deal with them.

The Hottest Specializations in Health Informatics

In my book The Sequel: How to Change Your Career Without Starting Over, I wrote about how it is often possible to move from one occupation to another that uses knowledge of the same field, but in a different way. For example, a teacher might move into educational sales. An entertainer might move into booking gigs for entertainers. A chemist might move into technical writing about chemistry-related topics. One kind of sequel career that I did not mention was managing information about the field with which you are familiar.

Every occupation generates information, and often it is possible to make a living by organizing that information and serving as a conduit for it. A stellar example is Michael Bloomberg, who earned his billions by realizing that the best business to be in was information about business. As his Wikipedia entry notes, “His business plan was based on the realization that Wall Street (and the financial community generally) was willing to pay for high quality business information delivered as quickly as possible and in as many usable forms as technically possible (such as graphs of highly specific trends).”

Health care is our biggest and fastest-growing industry, and it generates terabytes of information daily. As a result, health informatics has become a fast-growing field. The data wizards at Burning Glass, whom I mentioned in last week’s blog (and who are another example of spinning data into gold), have measured a 36 percent increase in the number of job postings for health informatics careers in the period from 2007–2011. This dwarfs the 9 percent increase in health-care job listings, not to mention the 6 percent growth of all job listings. (See the PDF of their report, “A Growing Jobs Sector: Health Informatics.”)

The field is still small compared to the nursing occupations, but Burning Glass found that job postings for health informatics now represent the eighth-largest share of health-care occupation postings. The fastest-growing specializations in this field are the occupations that require high levels of skill. For example, the number of job postings for medical coders—who usually need the Certified Coding Specialist credential—increased by 31 percent over the time period Burning Glass studied. Demand for these workers is being pushed by the switch to electronic medical records and the increased complexity of turning doctor visits into bills submitted to insurers, including Medicare.

But health informatics is about much more than billing. The Affordable Care Act, otherwise known as Obamacare, has created incentives for hospitals and physicians to avoid the expense of follow-up treatments and readmissions. This, is turn, encourages health-care providers to coordinate treatment and monitor its quality. Other uses of clinical data will be for rating health-care providers and for determining which interventions are most effective. Taken together, these uses of data create a need for workers—clinical documentation and improvement analysts—who have experience with clinical care and who understand the data that clinical care generates. Burning Glass found a 124 percent increase in job posting for this specialization 2007–2011. This is career seems a natural doorway through which nurses can move from providing health care to manipulating data about health care. Their key to this door might be to get certified as a Registered Health Information Technician. In fact, 37 percent of RHITs surveyed by the American Health Information Management Association received their certification with less than 1 month of coding experience, 74 percent of them held an associate degree, 16 percent held a bachelor’s degree, and only 4 percent had no more education than a certificate in coding (PDF).

Burning Glass also found rapid growth in the job postings for supervisory positions in this field: 46 percent growth for medical records and coding department supervisors/managers, 53 percent for health information managers.

Contrast these high-skill specializations with medical records clerks, which had a decline of 46 percent in the job postings 2007–2011. Within this field, medical records clerks would be considered low-skilled, but consider that they are in the middle range of skills when viewed within the full range of health-care occupations. (Home health care aides, for example, would be found near the bottom.)

What these examples show about the health-care field is that it resembles so many others: The workforce is being hollowed out as high-skill and low-skill jobs grow, while middle-skill jobs shrink or, at best, stagnate. The low-skill jobs barely pay a living wage, if that. High skills now are necessarily to gain even a toehold in the middle class.

When Entry Requirements Are Raised, Is Pay?

One career trend that seems to be here to stay is the up-credentialing of occupations. By this I mean that occupational entry requirements keep going up, whether they are set by licensure requirements or by employers’ expectations. Compared to past job applicants, new candidates need more schooling, more training, perhaps having passed a new exam. One might expect that the boost in occupational credentials may give a boost to the occupation’s prestige, but does it result in increased earnings? I recently found a small data set to help answer this question.

First, let’s step back and look at the factors that contribute to the up-credentialing trend. In some occupations, workers may be raising credential requirements (for example, by forming an association that develops a certification exam) as a way of erecting barriers to the entry of new workers, with the goal of restraining competition. This is sometimes called “professionalizing,” and workers justify it on the grounds that they are safeguarding the public by ensuring that only highly skilled people are allowed to practice the occupation.

In other occupations, the set of skills required for mastery or even competency in the work may have ramped up, especially because of scientific and technological advances, and thus a longer period of study—in other words, a more advanced degree—is necessary. For example, when I prepared the third edition of the College Majors Handbook, I found that pharmacy could no longer be described as a four-year degree, as it had been in the previous edition. Audiology became a doctoral-level program a few years ago, and physical therapy is now following suit.

In still other occupations, employers may be trying to simplify hiring decisions by eliminating low-credentialed applicants. Perhaps certain academic or training programs have diminished in rigor and thus have lost their meaning as a signifier of skill mastery. Or perhaps a recession has made the ratio of resumes to job openings so great that recruiters feel it necessary to raise credential requirements to cope with the flood of applicants.

What might be the effect of up-credentialing on pay?

It seems reasonable to suppose that if up-credentialing happens because of increased skill requirements, workers should enjoy a commensurate increase in pay. This is not just a matter of fairness; in a field where the professionals are highly skilled, they often can enlist the help of less-skilled paraprofessionals and thus boost their productivity. For example, think of how physical therapists use assistants and aides to do much of the work of preparing patients and equipment so that a therapist can serve many more patients. Highly-skilled workers may also be more adept at using technology or outsourcing to be more productive and thus earn more.

It also seems likely that workers should reap higher salaries when they “professionalize” an occupation by creating credentialing barriers to competition from new entrants. I’ve blogged about one study that found that licensure provides a pay boost roughly equivalent to that of union membership: about 15 percent. Probably certification has a similar effect.

When employers require higher credentials simply to cut down the number of application letters that must be read and interviews that must be conducted, we should not expect them to increase higher-credentialed workers’ pay.

I decided to investigate the effect of raised employers’ demands by analyzing the results of a study by the labor-market researchers at Burning Glass. These researchers analyzed job ads from more than 20,000 online sources, including both job boards and employer sites. Catherine Rampell, a blogger on The New York Times Economix page, asked Burning Glass to compile a list of the occupations that have shown the most up-credentialing in the past five years—specifically, those that have seen the greatest percentage increase in percentage of advertisements specifying the bachelor’s degree compared to those not specifying this degree.

The list of 40 most-up-credentialed occupations ranges from Dental Laboratory Technicians, which experienced a 175% increase in the percentage of ads requiring the bachelor’s (from 12% to 33%), down to Sound Engineering Technicians, which experienced an 8% increase (from 60% to 65%). From this list, I was able to identify 33 occupations for which the Department of Labor publishes earnings figures. The figures for up-credentialing apply to the period from 2007 to November 2011, and for comparison I looked at the earnings figures from May 2007 and May 2011.

It turns out that, on average, a 1 percent increase in bachelor’s-requiring advertisements results in a $483 increase in average earnings. (This is a weighted average, in which the differences in the number of jobs advertised have been figured into the calculations to give greater weight to more-widely-advertised occupations.) Now, if $483 seems a small figure, consider that a 1 percent increase is also a very small amount of up-credentialing. Also consider that this earnings difference is averaged out across everyone in the occupation, not just the new, up-credentialed recruits.

On closer inspection, however, this apparent earnings effect proves illusory. I calculated the correlation between the percentage increase in bachelor’s-requiring advertisements and the percentage increase in earnings over the same period and got –0.15. This figure is too small to suggest the existence of a relationship. That negative finding, in turn, suggests that up-credentialing over the past five years was not caused primarily by the up-skilling of the occupations.

On the other hand, if recruiters were using up-credentialing mainly as a quick way of tossing out most of the resumes that crossed their desks, one would expect a decrease, or at best a below-average increase, in earnings within up-credentialed occupations. That is, if up-credentialing is the recruiters’ response to an oversupply of job applicants, then employers shouldn’t need to increase incentives for applicants to these occupations.

In fact, the (weighted) average pay increase for the most-up-credentialed occupations, about $6,000,  is almost exactly the same as the average increase in pay of all associate-degree-level occupations over the same time period, also about $6,000.

So I conclude that up-credentialing probably occurred for a mixture of reasons: actual up-skilling of some occupations mixed with oversupply of applicants for other occupations. However, I should point out that the data set I’ve been working with is quite small. Burning Glass provided figures for only the 40 occupations with the largest increases in up-credentialing. I could calculate more confident correlations if I had access to credentialing shifts, both upward and downward, for the full range of occupations.

You, Too, Can Become a Superstar

I am not a fan of “American Idol” or “Dancing With the Stars,” but these shows are examples of one form of upward mobility that our economy still permits: Thanks to the reach of the mass media, talented people can become superstars. Over time, people in an expanding range of occupations—not just singers and dancers—will achieve superstardom.

This phenomenon was described as long ago as 1981, when the economist Sherwin Rosen published “The Economics of Superstars” in The  American Economic Review (PDF). As examples of fields ruled by superstars, Rosen cited comedy, classical music, and elementary economics textbooks. In all three cases, a large market existed for the service or good, but each market was (and still is) dominated by a small number of very-highly-paid providers.

Rosen noted, “Motion pictures, radio, television, phono reproduction equipment, and other changes in communication have decreased the real price of entertainment services, but  have also increased the scope of each performer’s audience.” Nor is there any reason this phenomenon must be limited to performers. “Undoubtedly, secular changes in communications and transportation have expanded the potential market for all kinds of professional and information services, and allowed many of the top practitioners to operate at a national or even international scale.”

It used to be that a chef could serve only a few dozen people per night and therefore could aspire to only a middle-class lifestyle at best. Ever since Julia Child, however, several chefs with the ability to communicate effectively through the mass media have grown rich from television appearances, cookbook sales, and ownership of restaurant chains. Some highly telegenic clergy have also achieved great wealth and touched many lives by using their media savvy to reach beyond church walls.

One newly emerging group of superstars is teachers. Surprised? You shouldn’t be. This is an occupation in which the work is essentially a performance. We all can remember teachers with outstanding performance styles, the teachers who kept us attentive and who succeeded in making the lessons memorable. Now the mass media are allowing teachers to take their skills to much bigger audiences than could fit into any classroom. In Germany, a self-taught Photoshop expert with a flamboyant teaching style has built an empire of DVDs, live online webinars, and downloadable courses for those who want to learn how to manipulate bitmapped images. This superstar instructor, who goes under the pseudonym Calvin Hollywood, says he earns as much as $16,000 per month.

Another superstar teacher is Salman Khan, a former hedge fund analyst who launched a teaching career by posting YouTube videos (such as this one) that explain how to do elementary math problems. Wealthy philanthropists noticed these videos and helped Khan establish the Khan Academy, an expanding collection of free online videos about math, several sciences, information technology, economics, and several humanities subjects.

One kind of teacher—fitness instructor—has a long history of media superstars, such as Jack LaLanne, Richard Simmons,  and Jane Fonda (not to mention the granddaddy of them all, Charles Atlas).

Television news and talk shows are routes to stardom for a few professions. For example, every TV news operation spotlights a physician, such as Dr. Sanjay Gupta, to explain medical developments and issues. Among lawyers, think of Nancy Grace. Talk shows have elevated the visibility of counselors of various sorts, turning them into self-help gurus who publish best-selling books.

But these media-leveraging workers, like the exercise workout leaders, are functioning essentially as teachers. The TV doctors, lawyers, and psychobabblers are not following the model of TV-chefs-turned-restaurateurs by opening HMOs, chains of legal practices, or storefront therapy centers—at least, not yet.

A Second Look at My Predictions

Now that the presidential votes have (almost) all been tallied, I’m sure that a lot of pundits are hoping you will not look at their pre-election predictions. (If you’re curious, you can see several of these on Ezra Klein’s blog. I’ve made some predictions of my own in print—not about the election, but about career prospects. I’m going to use this period of transition to a second Obama administration to look back at my prognostications in the book called Great Jobs in the President’s Stimulus Plan (2009). It turns out that my recommendations were, on balance, poor advice for the short term but good advice for the long term. And I’m okay with that. Occupational choice (as opposed to job choice) should be a long-term decision.

First, let me give you a bit of context about why and how this book was written. In the weeks following the 2008 election, as the inauguration drew near, interest in and excitement about the president-elect was building, and many businesses were cashing in by offering products such as Obama commemorative crockery. At the same time, the Obama transition team was developing the outlines of an economic stimulus plan to try to lift the nation out of the terrible recession. My editor at the time, Susan Pines, suggested that there was a market for a book that would focus on occupations that were likely to get a boost from the stimulus plan. On January 9, 2009, she gave me 14 days to develop a manuscript. I worked day and night like a madman and sent in the manuscript on January 20, a few hours before the new president was sworn in. The editing and page-layout staff at JIST Publishing then turned around this manuscript in record time and shipped the printed book February 4.

Understand that at the time I wrote the book, I had only an incomplete picture of what would be in the stimulus plan that eventually became law as the American Recovery and Reinvestment Act. In the terms of the old metaphor, the horse that I found in the plans of the Obama transition team ended up looking more like a camel once it had achieved passage by Congress. Some provisions were modified to gain the support of senators and representatives with diverse ideological and regional interests. Much of the funding for the original plan was redirected into tax cuts. In the introduction to the book, I warned about the limitations of my predictions.

But I also noted that the stimulus plan was designed to do more than just reopen the jobs that had been lost.  One important goal was to create jobs in sectors of the economy that would anticipate the directions where the American economy needed to go to remain competitive in a global job market. Therefore, the promise of these “great jobs” was not just a matter of short-term employment but also the potential to be good long-term choices. And when measured for the long term, based on the most recent job-market projections, my recommendations still hold the promise of success.

Let’s look at the record in detail, measuring my predictions against actual changes in the workforce between May 2009 and May 2011. (The BLS issues estimates of workforce size for May of each year. May 2009 was the latest May before the stimulus could start to influence the economy; May 2011 is the latest May for which figures are available.)

In Great Jobs in the President’s Stimulus Plan, I selected eight industries that the ARRA was designed to promote: Construction; Education; Energy; Health Care; Management, Scientific, and Technical Consulting Services; Manufacturing; Scientific Research and Development Services; and Wholesale Trade. I identified 300 occupations that are important in these industries and that had reasonably good outlook projections. This set of 300 included some occupations (such as Technical Writers, Sales Engineers, and Industrial Truck and Tractor Operators) that are not closely linked to any of the eight industries but are important across industries. These 300 occupations, taken from the O*NET-SOC taxonomy, represent 267 unique SOC occupations for which it is possible to obtain workforce statistics.

Now let’s look at the scorecard. The baseline for comparison is –1.8 percent. The workforce of all occupations shrank by 1.8 percent between May 2009 and May 2011. My set of 267 SOC occupations, the “great jobs,” shrank by 2.3 percent—in other words, did worse than the workforce as a whole. The construction jobs in the book shrank by 4.0 percent. The education jobs shrank by 0.6 percent; the energy jobs by 0.7 percent; the management, scientific, and technical consulting services jobs by 4.0 percent; the manufacturing jobs by 2.2 percent; the scientific research and development services jobs by 0.1 percent; the wholesale trade jobs by 3.1 percent; and the cross-industry jobs by 1.0 percent. The one bright spot was the health care occupations, which grew by 2.0 percent.

But recall what I said earlier about how the stimulus plan was designed to boost the sectors of the economy with the best prospects for long-term growth, and about how occupational choice should be based on long-term prospects. For the long term, the baseline is 14.3 percent. That’s how much the workforce as a whole is projected to grow between 2010 and 2020, the latest forecast available from the BLS. Against this baseline, the occupations I chose for the book score much better. The 267 unique occupations in the book have average projected growth of 15.7 percent over this long term.

Not all the industries into which I grouped the occupations fare better than the average for all occupations. For example, the manufacturing occupations I chose are projected to grow by an average of only 9.0 percent. However, what makes jobs “great” is not just the average growth of the industry. One of the slow-growing occupations is Secretaries, Except Legal, Medical, and Executive, a very large occupation (more than 2 million workers) with projected growth of only 5.8 percent. The large size of this occupation, while it drags down the average growth rate for this industry, also means that it will create a very large number of job openings because of turnover. And many of the slow-growing occupations, such as Industrial Engineers (projected at 6.4 percent) and Mechanical Engineers (8.8 percent), offer high salaries and many job opportunities. In fact, the manufacturing industry is now having great difficulty recruiting as many engineers as it needs.

The lesson to take away is that no one factor makes an occupation “great”—not any one economic factor, such as job growth, nor any other single factor, such as indoor versus outdoor work. It is likely to take many years before a career choice turns out to be a good one, and the same occupation can be a good goal for you but a bad one for someone else. Get a broad range of facts and impressions about a career—ideally, some firsthand experience observing it—before making a choice. And learn about the long-term trends for the occupation—not just the economic trends, but also the trends in work conditions.

The Divisive Election Reflects a Divided Economy

Last Sunday’s New York Times Magazine carried a story about how the Amtrak ride from New York City to Washington offers a microcosm of the new American economy: at either end of the trip, prosperous cities fueled by government and finance, and in between, struggling cities plagued by high unemployment. This portrait represents the challenge that confronts the second term of the Obama Administration.

The article correctly points out that the nostalgia for good-paying manufacturing jobs, expressed so often in campaign speeches during the previous months, overlooks the reality that “the dollar value of goods made in America is at an all-time high of $1.9 trillion, just about even with China. The catch is that the number of American workers needed to create all that value has dropped steadily. In the mid-1940s, more than half of the New Jersey work force was in factories; today around 7 percent [are].” Modern manufacturing facilities employ “a handful of highly trained workers guiding machines that return huge value to shareholders while all the time finding ways to produce more goods with fewer workers.”

The writer, Adam Davidson, notes that the train ride also offers views of shiny office buildings housing “law firms and engineering companies and I.T. firms.” He is mistaken when he identifies the workers in these buildings as having “nothing to do with manufacturing.” That is true for many of these office workers, certainly, but the nation’s high-dollar-value manufacturing industry depends on engineers and I.T. workers who apply new technologies, as well as lawyers who work out contracts and fight patent infringements, to keep their companies competitive.

It’s highly significant that General Motors has done a U-turn on its previous trend of outsourcing information technology jobs, according to an article in MIT’s Technology Review. When GM’s current chief information officer came on board in February, 90 percent of the company’s I.T. work was being done outside of GM. Now GM plans to open four software innovation centers around the United States and may hire as many as 10,000 workers to staff them. This shift recognizes the fact that as manufacturing—from the design process to the assembly floor—has become thoroughly computerized and automated, and as the automobiles themselves have integrated many computerized components, it is expertise in I.T. that gives American carmakers the competitive advantage over foreign firms.

Where Davidson is very much on point is his observation that these white-collar service jobs are not as easily obtained as the manufacturing jobs of the old economy: “For people with advanced training, the service sector means an above-average wage, a below-average risk of unemployment and days sitting at a desk. For those with only a high-school [diploma] or no degree at all, far fewer jobs are available, and the ones that are pay poorly and disappear quickly.”

During the presidential campaign that just ended, you probably heard a lot about policy differences between the two major parties. Many of these policies had implications for the new economy outlined in this article: for education that will equip workers with advanced skills, for innovations in technology that will keep us competitive, for health care that will keep us productive at costs that are not crippling, and for infrastructure that will allow industries to function efficiently. We voters have now chosen government leadership that is highly divided on which policies will achieve these ends. Let’s hope that our leaders can move past the gridlock of the past several years and find ways to keep our industries strong without leaving behind a large segment of the population.