According to a report by the World Economic Forum, emerging technologies (e.g., robotics and artificial intelligence) will result in a global loss of five million jobs by 2020. The report concludes that 7 million jobs will be actually be lost, but 2 million of those jobs will be offset by new jobs associated with the new technologies. “The report, based on a survey of chief human resources officers and top strategy executives,” writes Danny Palmer (@), “dubs the rise of AI and robotics as the ‘fourth industrial revolution’ and suggests that roles in every industry and in every geographical area will be affected.” He continues:
“White-collar office and administrative roles are expected to suffer the greatest losses, while the report suggests that there will be a rise in more specialised roles, such as computing, mathematics, architecture and engineering. ‘Without urgent and targeted action today to manage the near-term transition and build a workforce with future-proof skills, governments will have to cope with ever-growing unemployment and inequality, and businesses with a shrinking consumer base,’ said Klaus Schwab, founder and executive chairman of the World Economic Forum.”
I share Schwab’s concern that policymakers and business executives haven’t given enough thought to how we are going to assure jobs sustainability in a future increasingly characterized by automation. It’s a concern shared by Brookings Institution analysts Jack Karsten (@jtkarsten) and Darrell M. West (@DarrWest) who write, “Emerging technologies like industrial robots, artificial intelligence, and machine learning are advancing at a rapid pace, but there has been little attention to their impact on employment and public policy.” This concern, however, does not reflect an anti-technology bias. As President and CEO of a cognitive computing firm, I am a proponent of technology and the progress it can bring. I don’t believe progress can or should be stopped. I believe, however, that we owe generations to come the courtesy of trying to create a future that provides them ample opportunities to engage in meaningful work. We have the means to create that future; but, we also need the will to do so. Thomas H. Davenport (@), a Distinguished Professor at Babson College, and Julia Kirby (@) write, “Suddenly, it seems, people in all walks of life are becoming very concerned about advancing automation. And they should be: Unless we find as many tasks to give humans as we find to take away from them, all the social and psychological ills of joblessness will grow, from economic recession to youth unemployment to individual crises of identity. That’s especially true now that automation is coming to knowledge work, in the form of artificial intelligence.”
Rather than discuss a coming fourth industrial revolution, Davenport and Kirby talk about a third age of automation. According to them, during the first age of automation “machines took away the dirty and the dangerous”; during the second age of automation “machines took away the dull”; but, in the coming third age of automation “machines will take away decisions.” Those are sweeping, but interesting, generalizations. Obviously, not all of the dirty, dangerous, and dull jobs have been eliminated by machines. In the third age of automation, the same will hold true for decisions. Cognitive computing systems can already handle many, if not most, of the routine decisions a business needs to make leaving decision makers free to deal with anomalous and/or important decisions. This arrangement encapsulates my vision of the future (i.e., one in which man and machine collaborate rather than one in which man is replaced by machine). Apparently Davenport and Kirby also envision such a future. They explain:
“What if we were to reframe the situation? What if, rather than asking the traditional question — What tasks currently performed by humans will soon be done more cheaply and rapidly by machines? — we ask a new one: What new feats might people achieve if they had better thinking machines to assist them? Instead of seeing work as a zero-sum game with machines taking an ever greater share, we might see growing possibilities for employment. We could reframe the threat of automation as an opportunity for augmentation.”
Augmentation is not a strange notion. Humankind has been using machines to augment its skills since the first tool was put to use. Davenport and Kirby continue:
“David Autor, an economist at MIT who closely tracks the effects of automation on labor markets, recently complained that ‘journalists and expert commentators overstate the extent of machine substitution for human labor and ignore the strong complementarities that increase productivity, raise earnings, and augment demand for skilled labor.’ He pointed to the immense challenge of applying machines to any tasks that call for flexibility, judgment, or common sense, and then pushed his point further. ‘Tasks that cannot be substituted by computerization are generally complemented by it,’ he wrote. ‘This point is as fundamental as it is overlooked.’ A search for the complementarities to which Autor was referring is at the heart of what we call an augmentation strategy.”
Like any strategy, an augmentation strategy is only useful if people implement it; and, implementation remains a concern. Shortsighted business leaders are looking for the quick fix and increased profits. Automation often fits that bill. “Aiming for increased automation promises cost savings,” write Davenport and Kirby, “but limits us to thinking within the parameters of work that is being accomplished today. Augmentation, in contrast, means starting with what humans do today and figuring out how that work could be deepened rather than diminished by a greater use of machines.” Noted Harvard business professor Clay Christensen (@) stated much the same thing in a tweet, “Today’s culture of quarterly earnings hysteria is totally contrary to the long-term approach we need.” Davenport and Kirby go on to argue that human/machine collaboration should allow humans “to take on tasks that are superior — more sophisticated, more fulfilling, better suited to our strengths — to anything we have given up.” Convincing business executives to implement an augmentation strategy should be an imperative. If we don’t convince them, then many of the dark scenarios painted by in the press are likely to come about. “For augmentation to work,” Davenport and Kirby explain, “employers must be convinced that the combination of humans and computers is better than either working alone.” They are optimistic that will occur. “That realization will dawn,” they write, “as it becomes increasingly clear that enterprise success depends much more on constant innovation than on cost efficiency.”
Although I am most concerned about ensuring jobs sustainability in the future, researchers at the Human Computation Institute and Cornell University are studying human/machine collaboration on a broader scale. George Leopold reports that, in a recent article published in the journal Science, the researchers explore the advantages of combining the “the raw horsepower of high-performance computing with the subtle cognitive skills of humans.” He writes, “The combination of machine intelligence and human computation — defined as the ‘science of crowd-powered systems’ — would allow humans and machines to ‘accomplish tasks that neither can do alone.’ … The researchers said they want to build on those early examples of human-machine interaction to tackle intractable, or ‘wicked,’ global problems like climate change and pandemics that have so far defied traditional problem-solving methods.”
Whether we augment the abilities of single individuals or humankind as whole, the Davenport/Kirby augmentation strategy is promising. They conclude, “The strategy that will work in the long term, for employers and the employed, is to view smart machines as our partners and collaborators in knowledge work. By emphasizing augmentation, we can remove the threat of automation and turn the race with the machine into a relay rather than a dash. Those who are able to smoothly transfer the baton to and from a computer will be the winners.”
 Danny Palmer, “Five million jobs at risk from AI and robotics, warns World Economic Forum,” Computing, January 2016.
 Jack Karsten and Darrell M. West, “How robots, artificial intelligence, and machine learning will affect employment and public policy,” The Brookings Institution, 26 October 2015.
 Thomas H. Davenport and Julia Kirby, “Beyond Automation,” Harvard Business Review, June 2015.
 George Leopold, “Melding Human, Machine Computing to Solve Big Problems,” Datanami, 6 January 2016.