Smart Machines Will Eat Jobs (Except Where Smart People Create Them)


Automation will eat employment. That warning has been issued at every turn in history, with the printing press, the advent of electricity and the rise of robotics. Phases of automation, and the new trade patterns and agreements that accompany them, destroy jobs that involve repetitive tasks while creating new jobs.
“No office job is safe,” said Sebastian Thrun, Stanford CS professor and MOOC pioneer. “Lots of lawyers, accountants, even surgeons will be automated away. Having spent my career watching the long, slow carnage of my own industry, I have some insight into how that will feel, and how to cope.”
It’s easier to spot the jobs that will be destroyed than it is to predict the jobs that will be created. As a result, predictions associated with waves of automation are usually dire. That’s the case with the rise of artificial intelligence (AI)–observers suggest something between five and fifty percent are at risk. They are less specific about the number and type of jobs that will be created.
Some advocates (particularly those associated with new AI services) suggest “AI will help humans with their jobs, not replace them.” Mustafa Suleyman, co-founder of AI startup DeepMind acquired by Google, said that he’s seen no evidence that advances in AI are impacting the workforce but that it’s something that people “should definitely pay attention to” as the technologies continue to mature.
Suleyman predicts that humanity is still “many decades away from encountering that sort of labor replacement at scale.” Instead, the technology is best used to help humans with work-related tasks rather than replace them outright.

Machine learning (self-driving cars), neural networks (speech recognition) and natural language processing (essay scoring) are subsets of artificial intelligence—tools programmed to draw inferences from big data sets yielding what is sometimes referred to as machine intelligence, and which when used by humans to attack complex problems may also be called augmented intelligence.

Other vendors tout the benefits of augmented intelligence suggesting that AI isn’t going to replace the amazing, intuitive, creative human brain. In his new book, The Economist columnist Ryan Avent predicts in the next few years machine learning will complement many workers in the office—it will augment rather than replace.
However, Avent notes, “Machine intelligence, [is] a general-purpose technology that can be used anywhere, from driving cars to customer service, and it’s getting better very, very quickly.” He predicts a glut of labor where “the machines may render many humans as redundant as so many vintage washing machines.” He thinks the digital revolution will be as important and transformative as the industrial revolution.
“While AI technologies are likely to have a profound future impact on employment and workplace trends in a typical North American city, it is difficult to accurately assess current impacts, positive or negative.” That was the conclusion of a Stanford study, Artificial Intelligence and Life in 2030.
After issuing a report on likely AI impacts, President Obama said he tends towards optimism. “Historically we’ve absorbed new technologies, and people find that new jobs are created, they migrate, and our standards of living generally go up.” But, he added, “I do think that we may be in a slightly different period now, simply because of the pervasive applicability of AI and other technologies.”
“To date, digital technologies have been affecting workers more in the skilled middle, such as travel agents, rather than the very lowest-skilled or highest-skilled work,” added the Stanford study. “On the other hand, the spectrum of tasks that digital systems can do is evolving as AI systems improve, which is likely to gradually increase the scope of what is considered routine.”
“As AI substitutes for human roles, some jobs will be eliminated and new jobs will be created. The net effect on jobs is ambiguous, but labor markets are unlikely to benefit everyone evenly. The demand for some types of skills or abilities will likely drop significantly, negatively affecting the employment levels and wages of people with those skills,” noted the Stanford study.
The Stanford study panel identified domains where AI is already having or is projected to have the greatest impact, including transportation, healthcare, education, public safety and security, home/service robots and entertainment (these links are to prior posts in this #AskAboutAI series).
How to synthesize these conflicting views? It depends on your time frame and perspective—economists that look at long trend data are the most conservative while some technologists are ringing the alarm bell. After studying this issue, I think we can conclude five things about the next decade:

  • New work: The automation economy will change the nature of work for several billion people—enabling (and requiring) them to work with smart machines while increasing skill requirements and extending individual contributions.
  • Job loss: Hundreds of millions of jobs based on repetitive rules application are likely to be phased out over the next ten years as new applications deploy more sophisticated machine intelligence.
  • Job gains with skills: Tens of millions of new high-wage jobs will be created in Smart Cities that skill up and provide inspiration, incubation and intermediation around emerging opportunities.
  • New contributions: Machine intelligence makes predictions cheap but human judgment valuable. Empathy and social interaction, creativity and design thinking, and an innovation mindset will be increasingly in demand.
  • Big divide. Smart machines will eventually eat the middle of the job market—in some places as soon as ten years while in others it may be 20 years—eliminating most jobs that involve repetitive rule application. It’s hard to imagine that this won’t create an even bigger income gap between those that can code and leverage smart tools and those performing nonrepetitive service jobs.

Skilling Up: The Smart Cities Agenda

“AI could widen existing inequalities of opportunity if access to AI technologies—along with the high-powered computation and large-scale data that fuel many of them—is unfairly distributed across society. These technologies will improve the abilities and efficiency of people who have access to them,” noted the authors of AI in 2030.
In Smart Cities that Work for Everyone, we argue that cities that organized to skill up fast would win in the new economy. The rapid rise of machine intelligence makes this an imperative.
MIT economist David Autor said AI will not cause mass unemployment, but it will speed up the existing trend of computer-related automation, disrupting labor markets just as technological change has done before and requiring workers to learn new skills more quickly than in the past.
“While the ultimate effects on income levels and distribution are not inevitable, they depend substantially on government policies, on the way companies choose to organize work, and on decisions by individuals to invest in learning new skills and seeking new types of work and income opportunities,” noted the Stanford study.
The obvious opportunities for individuals and educational systems to focus on include:

  • Design thinking: Empathy research, prototyping and iterative development of new solutions to big problems.
  • Computer and data science: Computational thinking, productive strategies for attacking large messy datasets, and creative coding.
  • Project management: Bringing together subject matter experts and tool builders in short sprints to important deliverables (we think Cause + Code is the new impact formula).
  • Marketing: Brand advancement and sales management using new tools will continue to be in demand.
  • Technical education: Beginning in secondary education (tenth or eleventh grade), access to a variety of technical pathways that combine learning and employment can help young people quickly and affordably achieve postsecondary credentials with money in their pocket rather than debt hanging over their heads.

Here’s an example of how a couple of these will play out: chatbots are replacing call centers. Instead of a big team in Bangalore, brands will employ small teams of marketing managers, data scientists, chatbot managers, and creative writers. U.S. cities with transportation advantages and skilled labor have the opportunity to attract small, clean, high-tech manufacturing facilities employing a few coders, a few technicians and a brand manager.
Less obvious opportunities include:

  • Caring: Health care, senior care and other caring economy roles will continue to grow steadily.
  • Learning: Postsecondary education (formal and informal) aimed at new economy jobs will remain in demand; learning guides, advocates, and tutors will be increasingly important.
  • Creative: Harnessing smart tools to create beautiful things is a new opportunity; some low tech artistic niches will survive for decades.

There will be pervasive questions of how these important roles are compensated in the automation economy.

Crafting the New Social Compact

There are no simple answers to the challenge of technology disruption across a global economy. This election cycle surfaced the pain and frustration of groups that feel excluded. “Even if Donald Trump loses the coming election, millions of Americans have a gut feeling that the system no longer works for them, and they are probably correct,” said Yuval Noah Harari, Hebrew University of Jerusalem.
“We are going to have to have a societal conversation about how we manage this,” said President Obama to Wired last week. He added, “The social compact has to accommodate these new technologies.” He provided three examples of economic and political issues that will need to be addressed:

  • How are we training and ensuring the economy is inclusive?
  • How do we make sure that folks have a living income?
  • What does this mean in terms of us supporting things like the arts or culture?

AI innovations will pressure local and national civic capacity to quickly and efficiently consider regulatory changes. In some places, sharp displacement or legal battles (e.g., Uber in Austin) will bring these issues into focus, but in most places there will be a gradual creep into the automation economy—Siri will get better, a retailer will leave the mall and more self-driving cars will appear.
Cities and schools need leaders willing to #AskAboutAI in order to launch local conversations that result in proactive plans to build infrastructure and skills that result in employment gains, privacy protection and social benefit.
For more see:

Feature photo courtesy of Lowe’s Innovation Labs

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Tom Vander Ark

Tom Vander Ark is the CEO of Getting Smart. He has written or co-authored more than 50 books and papers including Getting Smart, Smart Cities, Smart Parents, Better Together, The Power of Place and Difference Making. He served as a public school superintendent and the first Executive Director of Education for the Bill & Melinda Gates Foundation.

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