Does automation result in job loss?
“Consider, for example, the effect of the automated teller machine (ATM) on bank tellers. The number of fulltime-equivalent bank tellers has grown since ATMs were widely deployed during the late 1990s and early 2000s (see Figure 1). Why didn’t employment fall? Because the ATM allowed banks to operate branch offices at lower cost; this prompted them to open many more branches (their demand was elastic), offsetting the erstwhile loss in teller jobs (Bessen 2016).” —WEForum: James Bessen
James Besson goes on to show that where there is elastic demand, so that automation meets increased demand, employment usually increases in an industry. But it is not all good news. Some work keeps going away: standardized & routine jobs.
“The evidence suggests that while computers are not causing net job losses now, low wage occupations are losing jobs, likely contributing to economic inequality. These workers need new skills in order to transition to new, well-paying jobs. Developing a workforce with the skills to use new technologies is the real challenge posed by computer automation.” —James Bessen
This is the challenge I have described several times. We don’t need to create more jobs, but rather better ways of co-creating value between humans. When a large number of jobs are created in a region, quite often these jobs are ripe for automation in a few years.
Co-create Value by Learning Together
If we are moving into a post-job economy, then we need to restructure how work gets done and how it is compensated. We cannot stay tied to the concept of the job as the primary way to work. For example, enabling people to easily change work roles, without the straight jacket of HR’s competency models, is one way to get rid of the standardized job, which has no place in a creative economy. All organizations and workers have to face the fact that the loss of routine jobs will continue.
“We show that over the past 40 years, structural change within the labor market has revealed itself during downturns and recoveries. The arrival of robotics, computing, and information technology has allowed for a large-scale automation of routine tasks. This has meant that the elimination of middle-wage jobs during recessions has not been accompanied by the return of such jobs afterward. This is true of both blue-collar jobs, like those in production occupations, and white-collar jobs in office and administrative support occupations. Thus, the disappearance of job opportunities in routine occupations is leading to jobless recoveries.” –Third Way: Jobless recoveries
Value creation in the emerging creative network economy is having ideas, connecting ideas, and trying new things out based on these ideas. Not only do these activities take time, they are highly social, as success often depends on who we work with. But being creative isn’t something people can just turn on and off, as any artist knows. To encourage creativity we need to change how we structure work. When ‘Labour’ of the industrial market economy is made obsolete by automation, the traits of compliance, diligence, and even intelligence become less valuable. In a creative network economy, ‘Talent’ requires creativity, curiosity, and empathy.
Supporting Talent for customized work requires a culture of continuous learning. Today, if people are not able to speak, read, or write, then work cannot get done. It would be impossible to run any modern organization without communication skills. We are moving into an era where it will be impossible to run a company where everyone is not constantly learning. This does not mean everyone will be on standardized training courses though. Curiosity, creativity, and empathy are not developed through training. These are social skills which can be practiced and reinforced in creative workplaces between engaged co-workers. Most importantly, a creative network economy workplace will require constant independent and interdependent learning by doing. This is social. In the very near future, those who cannot learn with others will miss out on creative work opportunities.
The good news is that everyone can learn. The bad news is that many have forgotten how and will fall between the cracks. James Bessen states above that, “Developing a workforce with the skills to use new technologies is the real challenge”, but I disagree. While we need to understand new technologies and use them optimally, we really need to develop something much more important. Our focus for education, training, and work must be on helping us be better humans, not better machines. Creativity, curiosity, and empathy become powerful human tools when we continuously learn with each other. No machine can match that. As Niels Pflaeging recently stated, “Machines can solve complicated problems. They cannot solve complex, surprising problems”. Valued work is no longer standardized. Therefore a standardized approach for education and training to support creative work is obsolete.