This chapter appears concurrently in Age of Robots and includes content and quotes garnered from interviews with James J. Hughes, Jerome Glenn, Ian Pearson, Richard Yonck, John C. Havens and Alexandra Whittington on the Seeking Delphi™ podcast between April of 2017 and November of 2018. **
“There are no right answers to wrong questions.”—Ursula K. LeGuin
Will automation kill jobs? That’s not exactly the wrong question, but it is an incomplete one. Which automation—robots, computers, A.I.? Which industries? And most important, in what time frame? The next five years are particularly fuzzy; things are simply changing too fast to tell.
Some History
On the eve of the iconic year of 1984, Isaac Asimov published an article envisioning the society of 2019.1 He foresaw a world where computerization and robots would change the world of work, and computer literacy would be vital for the jobs of the future. He was right.
On the other hand, he conjectured that the transition to a more automated workplace would be largely complete by 2019. He was clearly wrong. The extent of the uncertainty and the varied nature of the many feasible scenarios indicate that the transition, if anything, is far from over. We still don’t know the outcome; but the next five years may bring us closer to knowing some answers. Even then, though, we still might find much uncertainty. Rapid change and disruption could become a permanent state.
Technological change has become so rapid—and to some extent chaotic–that even futurists feel challenged in ways they never have before. Consider these words from James J. Hughes, executive director and co-founder of The Institute for Ethics in Emerging Technology:
“We’ve had the general experience over the past ten years that It’s hard to be a futurist nowadays. You think up something that you think is going to be, for five or ten years, an issue that you’ll be able to be the only person talking about it. Two weeks later it’s in the White House or in the European parliament being debated.” **
If futurists can’t keep up with it, how can the rest of us?
The Hype
The popular media, in its never-ending quest for click bait, greatly oversimplifies the questions. This is particularly true of artificial intelligence and job loss.
“What we hear about [it] is mainly hype,” says Alexandra Whittington, Foresight Director of Fast Future Publishing. **
Jerome Glenn, chair of The Millennium Project and lead author on their State of The Future publications, points out that it is important to distinguish between types of A.I. The narrow A.I. we currently have generally is focused on a single task, like playing chess or arranging airline schedules. Human-like artificial general intelligence could be a much broader threat, but we have no idea when, or even if it will ever be achieved. So, near term, he sees the less disruptive narrow A.I. as all that is on the table. **
The current flap over automation job reduction probably started with a 2013 report by the Oxford Martin School at Oxford University, entitled The Future of Employment: How Susceptible are Jobs to Computerization.2 Supported by mountains of statistics and advanced mathematical formulas, they came up with the assertion that 47% of all U.S. jobs are highly susceptible to being automated, and therefore eliminated. That was only the beginning.
Following a 2017 report by McKinsey that 800 million jobs globally could be affected by automation by 2030, a torrent of gloom and doom articles appeared in the mass media. Just consider some of these:
- Automation could destroy millions of jobs—The Guardian, August 2018
- America is unprepared for the job apocalypse automation will bring—CBS News, June 2018
- Will robots take your job? Humans ignore the coming A.I. revolution at their peril—NBC News, February 2018
- One million jobs will disappear by 2026. How to prepare for an automation future—CNBC, February 2018.
Emotional, knee-jerk reaction to the headlines has led to what could be characterized as a kind of neo-Luddism.
Like the early 18th century efforts by weavers to destroy automated weaving looms and by horse breeders to block the proliferation of steam powered “horseless carriages,” there have sprung up various efforts to block technology today. Consider, then, these headlines:
- Professional Taxi Drivers In New York Want Self-Driving Cars Banned for 50 Years—Yahoo.com, January 2017
- The Beef Industry is Desperately Fighting Lab-Grown Meats Over Labeling—Uproxx.com, February 2018
But there have also appeared many rebuttals to the doom and gloom scenarios, and one does have to drill down in these reports to fully in understand what might be going on. The devil is most certainly in the details.
So, what exactly did McKinsey say? It’s less stark than immediately meets the eye. While over half of all existing workers could have up to a third of their functions automated, they also said only 5% of current jobs are fully replaceable by automation. At least for now. They further made projections of millions of jobs created by A.I. and robotics and suggested that only between 3 and 14% of all workers will need to find new occupations by 2030.3
Clearly, it is only certain jobs in certain industries that are likely to disappear in the near term. And while cattle breeder and taxi driver are two occupations eventually in peril, it may already be too late to save the latter. Uber and Lyft are seeing to that.
Historically, the ultimate technological demise of many industries has simply resulted in job creation in new industries; often many more jobs then were lost. The loss of most jobs for horse breeding in the early 20th century led to creation of many more in automotive manufacturing, maintenance, professional driving, and the petroleum industry.
But people have short memeories, and the speed and pervasiveness threatened currently by multiple disruptive technologies will likely dwarf anything seen in the past.
Hughes sees the push back against technology in these terms:
“Trump says he is going to bring back all these jobs, but he has never dealt with the impact of automation in the erosion of industrial jobs. Luddism makes sense if there is no vision of how everyone gets fed and how we can have a good society without traditional jobs”. **
The Optimist
One optimist is noted British futurist and author Ian Pearson. Writing in his Futurizen blog in March of 2017, Pearson states:
AI has been getting a lot of bad press the last few months from doom-mongers predicting mass unemployment. Together with robotics, AI will certainly help automate a lot of jobs, but it will also create many more and will greatly increase quality of life for most people.4
How can he be so sanguine in opposition to the torrent of doom and gloom saying in the popular press? He asserts that there is a lot of counterbalance that is being ignored in the press and sees three main areas of robotic and A.I. job creation.
These include, first, the need to program and maintain robots and A.I “Even with industrial robots you need a skilled workman on the factory floor showing them what to do,” he says. But industrial robots are a lot easier to program than more general-purpose artificial intelligence, which he compares to the complexities of teaching children. He believes that, though this won’t last forever, it will get us quite a few decades of extra jobs.
A second area is in jobs where what he terms “emotional repertoire” is required. In things like interacting with patients and maintaining customer relationships, A.I. can only do so much. “It can’t pick up body language or facial expressions and can’t tell whether you’re lying or exaggerating. Having a nurse or a technician between you and the AI can allow you to give far more detail to that program.” He also suggests that people won’t open up to a computer program or robot in the same manner that they might to another human being. “The human forces you to be more open and honest about whatever it is you are doing.
Third, he believes A.I. and other forms of automation will aide entrepreneurship.
“I think a lot of us would be an entrepreneur if it wasn’t so difficult,” he says. He sees setting up a small company as a daunting task with tons of red tape, which can easily be farmed out to A.I., as long with handling logistics of manufacturing and shipping. Adding artificial intelligence to a green employee, and you “upskill” them as he says, and makes them a more useful employee.**
The fly in all this ointment is the emergence of emotional A.I., or affective computing. Richard Yonck is a futurist author who has written on the subject, and to some extent warns that A.I. that can read, and react appropriately, to human emotion, might threaten even the jobs that Pearson described.
Pearson does not entirely disagree with him. He thinks that Yonck is talking about a different time horizen than he is. He sees A.I. able to do just about everything humans can do, and then some, by around 2050. But in the near term of just a few years, he still sees it as a more stimulative technology.
The Skeptic—
Richard Yonck (author, Heart of the Machine) puts himself somewhere in between Pearson and the more pessimistic doomsayers in the foresight and economics communities.
In a 2017 interview he stated:
I think it will have a strong impact but probably not as severe as some of the prognostications. Automation, computerization A.I. and so forth. But we saw from the great recession we don’t need to have 46 per cent of jobs to go away to have an enormous impact. It’s true there are going to be new jobs and new value, and additional value placed on human emotional capabilities. I half agree there will be a number of new jobs that arise out of qualities that are distinctly human in whatever role. Nursing, teaching, psychotherapy, roles where we have a level of emotional connection that machines simply cannot or will not have for a good few decades. But I question whether that could offset all of the losses. **
Conclusions
So where do we go from here? It’s complicated.
Almost to a person, the pundits quoted above look at Universal Basic Income as a solution to mass technological unemployment.
Hughes puts it this way:
“We have been advocating for the importance of grappling with technological unemployment and advocating for universal basic income guarantee. That’s now become mainstream. We need to be able to make that deal with the public. Yes, lots of people are going to lose their jobs, but we’re going to get all this cool stuff and we’re going to make sure that everyone gets fed and everyone’s going to have an income. Folks don’t really believe it yet, they don’t see the politics. “**
Another possible solution—attitudinal, rather than socialistic—comes from Heartificial Intelligence author John C. Havens. He sees that the currently dominant economic model in the West as a roadblock to preventing automation job loss. He thinks that it makes no sense to have all these fantastic, disruptive technologies but still be living in an economic system based on GDP developed in 1944.
”It’s absurd not to bring societal infrastructure up to the level of technology.” He says and cites a possible solution in adopting what is called the triple bottom line, emphasizing not only growth and profitability, but also human and environmental well being. **
But again, one must ask oneself, is there any likelihood of the politics and economics being there for either of these solutions—at least in the short term?
The silver lining in the cloud, at least for the next few years, is that only a few select professions in a few industries are in danger of disappearing entirely. While taxi drivers are under assault from ride sharing, the autonomous-driving demise of all professional taxi and truck drivers appears much farther out.
The stark fact, as of this writing, is that much of the West is experiencing labor shortages. Even China is facing a shortfall of over 20 million skilled tech workers in the next few years.5 In the near term, labor shortages, rather than profits, may drive the proliferation of automation.
The verdict, then, is that we have not achieved the new equilibrium that Asimov envisioned by now. Change has accelerated but is nowhere near complete. We don’t now know for sure where it all will lead; we might have a better idea in five years.
Questions:
Which jobs in which industries and in what timeframe are most likely to be transformed or completely displaced by technology?
Will automation deployment be accelerated as a short-term solution to skilled labor shortages?
How should society deal with job loss due to automation?
**Sackler, M. (2017-2018). Seeking Delphi™. from https://seekingdelphi.com/podcasts/
- Asimov, I. (2019). 35 years ago, Isaac Asimov was asked by the Star to predict the world of 2019 Here is what he wrote. https://www.thestar.com/news/world/2018/12/27/35-years-ago-isaac-asimov-was-asked-by-the-star-to-predict-the-world-of-2019-here-is-what-he-wrote.html
- (2019). Oxacuk. https://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf
- Mckinsey, . (2017). Jobs lost, jobs gained: What the future of work will mean for jobs, skills, and wages. https://www.mckinsey.com/featured-insights/future-of-work/jobs-lost-jobs-gained-what-the-future-of-work-will-mean-for-jobs-skills-and-wages
- Pearson, I.D. (2017). The more accurate guide to the future. https://timeguide.wordpress.com/2017/03/26/ai-is-mainly-a-stimulative-technology-that-will-create-jobs/
- People’s daily. (2019). China to see shortage of 22 million high-end technical workers by 2020. http://en.people.cn/n3/2019/0115/c90000-9537759.html
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Alexandra Whittington is a futurist, writer, foresight director of Fast Future, and faculty member on the Futures program at the University of Houston. She has a particular expertise in future visioning and scenario planning. Alexandra is a contributor to The Future of Business, Beyond Genuine Stupidity—Ensuring AI Serves Humanity, and The Future Reinvented—Reimagining Life, Society, and Business, and a co-editor for forthcoming books Unleashing Human Potential—The Future of AI in Business and 50:50—Scenarios for the Next 50 Years.
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