Developing and recognising talent in a fast-changing world

A year or so ago, while driving through upper New York State back to Canada, I heard on the radio that the local newspaper had laid off its part-time sports reporter – but had not stopped running stories about high school’s (American) football games. They were now being written by a computer programme that had been fed the game’s statistics, nor had the paper received complaints about the style of the new ‘author’.

And, a few weeks ago, after copy-pasting text I wrote in Word into an e-mail, I noticed that G-Mail’s spell and grammar checker had flagged a number of stylistic faux pas, showing me how quickly artificial intelligence (AI) has gone from taking over repetitive tasks, such as welding car frames to changing, even threatening, my line of work.

While many looking at the changing landscape of work emphasise the need for students to learn to code – some in Canada calling for coding to be taught in grade school – Jamie Merisotis, head of the Lumina Foundation, argues in the other direction in his new book Human Work in the Age of Smart Machines.


He marshals strong support from, among others, a senior analyst of The Motley Fool, a private financial and investing advice firm based in Virginia, US. “Big companies in the US are actually looking for liberal arts-type graduates because they want people who have a broader background than just a narrow set of skills that you might get out of finance or something.” The speaker, Seth Jenson, not so incidentally, then said: “Look at me. I was an art history major.”

To understand what’s going on in the fast-changing world of work, Merisotis takes us into a photography shop. Just 20 years ago, much of a photographer’s job was repetitive dark-room work. Today, because of digital photography, 80% of the job is what Merisotis calls “human work”, work only humans can do. Partly, this includes getting to know his or her clients so that the photographer can think of creative solutions to their desires.

The change in the photographer’s remit is only one example of what is occurring across the economy when computers alter the very mechanics of a job or profession. In the future, Merisotis believes, it’s likely there will be no such dichotomy as blue-collar and white-collar jobs. Practical skills matter in all jobs, and so do other human traits such as teamwork, communication and abstract reasoning.

“What will matter more is how these abilities are acquired and developed, and how they’re synthesised through work into something meaningful,” Says Merisotis.

As do many such books, Human Work, provides eye-popping numbers, some of which portend how wrenching this COVID-19-caused recession will actually be. In the US, of the 5.6 million jobs held by those with high school education or less in the recession that began in 2007, only 80,000 had been revived by early 2020, while the economy had added eight million jobs.

Many of these positions required advanced technical knowledge and were well paid. Yet that did not prevent the doleful statistic that 10% of the highest-income earners in the United States owned 70% of the nation’s wealth while “the bottom 50% of American households” in which African-American and Latino families predominate, “had virtually no net worth at all”.

That these last words register the author’s rage are a clear indication of what the organisation he heads, the Indianapolis, Indiana-based Lumina Foundation, which is committed to support learning beyond high school, especially for those traditionally excluded from such education, is up against.

Across the economy, fewer of today’s workers hold the blue-collar work that involved heavy labour that their parents might have done. The Subaru plant in Indiana that in 1989 employed dozens of welders to turn out 88 cars a day is now robotised and turns out 1,350 cars every 24 hours.

Robots introduced

Among the workers there are employees like Joel Lewis. Before the robots were introduced at his Columbus, Indiana, company, he spent his days “stuffing pistons into diesel engines”. Now he supervises the robots, which he calls ‘co-bots’.

Lewis’s story shows, not just the march of technology but, importantly, that the march ends up requiring workers who have high-level skills such as communication, critical thinking and teamwork; this last might surprise, but Lewis underscores that, in order to get the most out of his co-bots, he has worked closely with “workers who offer suggestions for how manufacturing processes can be improved” and, even, made safer.

While Lewis’ career did not involve his going to college to become a trainer, for many that is still the route to a better, indeed, more human, job, though not in the traditional high school-to-college route.

Marcus Dodson saw the writing on the wall when, one after another, the companies he worked for in Kentucky outsourced production. After taking a $10,000 pay cut to work for the Tennessee state government installing and maintaining computers, he found himself energised by the desire to deliver better products and services to his government clients.

What he needed, he realised, was training, the first part of which he received in two government programmes.

Soon he was supervising 12 employees and availed himself of a state programme that subsidised his tuition at Tennessee State University, where he earned a masters.

Dodson’s technical knowledge may have secured him entrée into the Tennessee government, but it was his drive and, especially, his realisation that he needed a certain kind of education, that led him to his present position.

In it, he is less concerned with bits and bytes, monitors and keyboards than with ‘human work’, engaging with the users of technology with understanding and empathy. This is the story of work that should be told more often.

Dodson is one of millions who realised they were in a ‘skills gap’. Another whom Merisotis points to is Marica McCallum of Austin, Texas. For four decades, she waited tables, sometimes doing double shifts, to support her four children and put them through school. Eight years ago, she decided it was her turn and enrolled in the local community college.

The age difference between her and her classmates prompted a few to mistake her for the professor when the class first met. Elementary algebra was mastered with the help of flashcards her oldest daughter prepared. McCallum’s intention, to become a nurse, barely survived her first experience of laboratory work. Soon she changed her major to biotechnology.

Officials at her community college were so impressed with her passion and the series of As on her transcript, that they turned to her to help set up the school’s Bioscience Incubator Lab. From there, she went from strength to strength, taking a general degree in science and being hired by a biotech company, where she helps harvest therapeutic antibodies that are used to treat cancer, inflammatory conditions and other diseases.

Skills gap

The skills gap that Dodson and McCallum overcame is an equal problem for companies and, by extension, the economy as a whole. At the end of 2018, there were 700,000 advertised openings in the United States and 630,000 receiving unemployment benefits. The vast majority of these unemployed, Merisotis notes, lacked the necessary skills to fill the existing jobs.

Merisotis believes that the Fourth Industrial Revolution (AI) will produce the number of jobs needed to replace those being destroyed. At the book launch, he made this point by taking us back to 1970 when Detroit was the motor of the American economy and Silicon Valley had barely been named.

The essential difference between the two areas, he noted, was that the denizens of the valley had higher levels of education that allowed their careers to take off once the computer revolution began.

Not everyone agrees with him. In his magisterial The Rise and Fall of American Growth: The US Standard of Living Since the Civil War (2016, Princeton UP), Robert J Gordon shows conclusively that the First and Second Industrial Revolutions (steam, and electrification and internal combustion) quickly produced millions more jobs than were lost.

Ford’s Model T, as the legend goes, put buggy makers out of business, but making the Tin Lizzy employed thousands and then hundreds of thousands and then millions.

By contrast, the Third Industrial Revolution, with its miniaturised electronics and computers, has not produced anything like these numbers, partly because of manufacturing overseas and partly because so much of the production of, say, a smart phone, is performed by robots.

Defining ‘human work’

The strengths of Human Work in the Age of Smart Machines lie in Merisotis’ extended effort to define ‘human work’ as the “work only humans can do” and the book’s final chapter, “Human Work in a Democratic Society”. Defining the “work only humans can do” is not simply a matter of noting that robots do not have the dexterity needed to lay bricks, for example.

Merisotis divides ‘human work’ into four groupings. The first, ‘helpers’, includes the predictable occupational therapists and mental healthcare workers, as well as financial service personnel because they, too, have to be empathetic and communicate clearly.

The effect of including these is interesting. It elevates the other careers (which in the United States are generally devalued because they are seen as extensions of ‘women’s work’) in a way that would surprise practitioners of the ‘dismal science’ of economics.

Sales and repair managers, and computer specialists are ‘bridgers', so called because they must “create connections” between users and technology. They, too, must not only be able to communicate to individuals in need, of, say, a working car, but also anticipate uses of the technology.

‘Integrators’ included social workers and elementary school teachers, as well as “people who apply the lessons learned in one context . . . to a new or different field”; again, here, Merisotis’ language erases the devaluation of these professions all too common in America’s gendered language.

Finally,‘creators’ are those with “highly technical skills and pure creativity”.

Re-imagining education

Designing curricula to facilitate training for each of these groups, Merisotis argues, involves re-imagining education so that colleges and universities are no longer the main credentialling bodies.

Much can be learned by doing as the various training courses run by such companies as Microsoft and Google show; in a lighter moment, Merisotis tells of a training course qualification any techy might want on his/her business card: ‘Certified Ethical Hacker’.

When asked, university and college administrators talk glibly about preparing their students for the job market. But, says Merisotis, too often universities train their students to be academics and not, as the vast majority will be, workers in the general economy.

Part of the problem is that professors work in settings – classrooms on campuses – that are divorced from where their students will work, with the result that the professors cannot structure their courses to foster human work in situ.

Fostering breadth of talent

A good example of how education can foster the breadth of talent required by human work comes from a medical faculty, perhaps the faculty more like on-the-job training or the almost 740,000 credentialled programmes in the United States.

At the University of Virginia’s medical school, students take a six-week art course, during which they not only “hone their observational and diagnostic skills” but, importantly, develop “capacity for personal reflection, tolerance of ambiguity” and increase their awareness of personal biases.

When he discusses the vexed question of what colleges and universities, on the one hand, and employers, on the other, mean by credentials, Merisotis might well have quoted Winston Churchill on the Americans and British: “They are divided by a common language”.

As I can attest from my 30-year career as a professor in a technical college in Ontario, defining what ‘problem solving’ or the ‘ability to work in a team’, let alone ‘critical thinking’, means is like trying to nail jelly to the wall.

Merisotis calls for common frameworks that clearly define knowledge and skills. Given that we have been able to develop standards with which to adjudge hotel rooms, he does not see any reason why it is not possible to define a skill, such as problem solving, and then “drill down to define the specific competencies people need to develop to master each skill”.

The gold standard would seem to be the European Qualification Framework, which allows comparison across the European Union, despite the different languages, educational systems and labour markets. In the United States, he points to Credential Engine as a way out of this impasse. Its forthcoming Credential Registry should allow educators and employers to determine the knowledge, skills and abilities that credentials are supposed to attest to. Both colleges and employers would then be able to give credit where credit is due, as it were.

Silos out of step

Another area where the traditional university is out of step with today’s job market is its organisation. Universities and colleges are organised by department: silos was the buzzword before I retired from teaching. Many people, Seth Jenson discussed above is one, do not end up working in the field in which they majored. Even for those who do move from university into the field in which they studied, which is the case for many STEM majors, focusing solely on STEM curriculum is short sighted.

Even in STEM fields, human work demands a broader, more integrated kind of learning, as the cliched story of the engineer who could not explain to a client how a proposed product worked has underscored for decades.

One of the most revealing statistics in Human Work testifies to the way colleges and universities have ignored the changing nature of the humans who come through their doors.

In 2010, only 9% of students at Amarillo College in Texas graduated. When he undertook a survey of the school’s students, its president, Russell Lowery-Hart expected the usual litany of academic reasons that any, “recovering faculty member”, as he mockingly called himself, could recite.

Instead of complaints about teachers, textbooks and assignments, he heard that student success in the classroom was undermined before they had even walked through the schoolhouse door.

Childcare expenses, access to affordable health care, housing, utility bills and even lack of food all prevented students from succeeding.

Since existing financial aid programmes were unable to raise these barriers, the college’s social service department helps students find ways to pay their bills, a food bank was established as were dental and car repair clinics. To help poor students dress for success when going to job interviews, the school set up closets in which students could find spiffy clothes. Graduation rate is now 53%.

Political act

Were he simply one more educrat anatomising what is wrong with today’s – and tomorrow’s – post-secondary systems, Merisotis’ insights would be useful. What makes them truly important, however, is where he leads us in the final chapter of his book. Human work is not a slogan. Rather, developing skills for human work is, ultimately, a political act, as Indira Samarasekera, who between 2005 and 2015 was president of the University of Alberta (Canada), told a conference Merisotis attended in London in 2019.

“Empathy, human emotion, social skills, and things like ethics and morality, character, and kindness are not simply traits you are born with,” she said. They have to be developed by the curriculum.

These skills are important for success at work. But they are also effective counterweights, Merisotis believes, to the coarsening of political discourse and the right-wing echo chambers formed on the internet, which fundamentally divide citizens and prepare the soil in which Donald Trump and other populists currently grow.

It is so much easier to blame immigrants, better educated ‘elites’ and/or women for, say, lack of jobs in the Upper Midwest if those who have lost their jobs see the path to the education they need as being blocked by Byzantian bureaucratic structures that tell many of those most in need of human education, “You don’t belong here”.

It is so much easier for the siren song of ‘fake news’ to be believed when large segments of the population have no training in determining fact from fiction. Antivaxxers, Merisotis notes, have gained the upper hand and measles makes a resurgence – because education systems have failed to provide scientific literacy and inculcate the human attributes of empathy and understanding.

The figures Merisotis adduces for America’s polity are frightening. One-quarter of those with high school or lower education say that “military rule would be a good way to govern our country”. Only 7% of university graduates agree. Presumably the millions who have taken credentials through professional organisations and companies fall somewhere in-between; at least we might hope so given that these credentials are designed to hone high-order reasoning skills and, in many cases, provide training in interpersonal relations that should break down barriers between people.

Faced with what, to borrow the poet Matthew Arnold’s words from Dover Beach, seems like the “melancholy, long, withdrawing roar” of democratic values that only 30 years ago when the Berlin Wall came down seemed triumphant, Merisotis gives post-secondary educators of all types something of a motto: “Education helps people to better understand abstract principles of democracy and equality and how to deal with complexity and differences in society.”

James Merisotis: Human Work in the Age of Smart Machines, Rosetta Books 2020, ISBN: 978-1-9481-2262-7

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