Automation, the replacement of human work with human-made technology, has been happening ever since we invented tools. Just as farmhands were replaced by machines 100 years ago, so too will knowledge workers be replaced by networked computers in the next few decades. Last century, those farmhands had the option of moving to the city and working in factories, but what are the alternatives for today’s knowledge workers? It is not likely to be a new job, as the job itself is being made obsolete, underlined by 57 million freelancers in the USA today, accounting for about 1/4 of working-age adults. This is expected to grow to 86 million by 2027 so that freelancers will be the majority of the American workforce.
Automation seems to be accelerating and has been a frequently discussed topic here. But does automation really result in job loss? It appears that where there is elastic demand, so that automation meets increased demand, employment usually increases in an industry. For example, employment at banks increased with the introduction of automatic tellers. 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
McKinsey Global Institute looked at a wide array of US jobs based on 2014 labour data to determine what percentage of work could be automated in various jobs using current technology.
Paralegals 69% – Lawyers 23%
Food Service Managers 32% – Chief Executives 25%
Computer User Support Specialists 65% – Actuaries 15%
Pharmacists 47% – Psychiatrists 7%
Rehabilitation Counselors 31% – Health Educators 0%
Library Technicians 59% – PreSchool Teachers 7%
Training & Development Managers 38% – Legislators 4%
How can we preempt automation? The challenge is to identify what work can be automated and focus people on being more creative, both in dealing with complex problems and in identifying new opportunities. Human creativity is a limitless resource. But too often, it is wasted in our organizational structures. Those who work for themselves embrace automation.
“The family farm is an example of automation being used to free people to do what they do best. As one farmer said, it’s difficult to hire people who want to milk cows everyday at 4:00 am.
While automation is one of the reasons there’s been so many job losses in manufacturing — taking over repetitive tasks, experts in the field says it’s time to re-think the point of jobs themselves.
Despite automation, the Shantz family says cows still need personal attention. And although some farmers are skeptical of robots are taking over jobs, experts in the field say that with technology forging ahead it’s time to re-think the point of jobs themselves.” —The Current, CBC
What is the point of a job? Farmers are in a position to see their entire work system and make it better. The future is for people to work on the system, not in the system as replaceable parts. We can get there if those people in charge start identifying ways to make all work more human and focus on talent development — creativity, curiosity, and empathy — to name a few. In a post-job economy, management is preempting automation. In countries like Sweden, with a strong support system for unemployed workers, people look forward to automation. “The jobs disappear, and then we train people for new jobs. We won’t protect jobs. But we will protect workers” —NYT 2017-12-27. In Sweden there are national systems in place to preempt automation.
Getting Ahead of Automation
Automation of routine and standardized work is forcing people to do more non-routine manual and cognitive work. If the work can be mapped and analyzed, it will be automated. As non-routine work becomes the norm, work environments will have to become open, transparent, and diverse because trust is essential to ensure that knowledge flows. With little routine work to do, organizations have to learn as fast as their environments. In addition, constant experimentation must be the norm.
Those in leadership and management positions today must find ways to nurture creativity and critical thinking. Management can set the initial example of transparency. In addition, self-management is required at all levels. When there is no one to defer work to, everyone sets an example through their actions. In this environment everyone is learning and everyone is teaching by example. From such a foundation, today’s organizations can prepare for a new world of work. Machines will continue to replace work and jobs but people can develop new work roles that are creative and social, beyond the reach of automation.
One small change that could have a major impact would be to look at everyone’s work from the perspective of standardized versus customized work. Every person in the company, with the help of some data and peer feedback, should be able to determine what percentage of their time is spent on standardized work. If the percentage is over a certain threshold, say 50%, then it becomes a management task to change that person’s job and add more customized work. The company should be constantly looking at ways to automate any standardized work in order to stay ahead of technology, the market, and the competition. Automation is pretty well inevitable but it does not have to decimate the workforce, as the Swedish example above shows.
Looking at the overall company balance between standardized and customized work should be an indicator of its potential to succeed. By visualizing the Labour/Talent split, people in the company can take action and make plans before the inevitable shift. This of course means that jobs and roles have to become more flexible and open to change. But this is a post-job economy we are moving toward. We cannot stay tied to the concept of the job as the primary way to work.
Building ways to constantly change roles will be one way to get rid of the standardized job, which has no place in a creative economy. This one small change could have a major impact on any organization. It just requires a slightly new way of looking at work, collecting good data, engaging workers in the process, and being transparent about it all. Most of all, it requires companies and managers who really care about talent development.
Learning at Work
The human work that emerges from mass automation is increasingly complex. This is a challenge for training and education systems run by a central authority (the academy). Standardized curricula are only effective when developing instruction to deal with complicated phenomena, where all the components are understandable and can be analyzed and mapped. Best practices and good practices can align easily with a curriculum. But in complex environments, emergent practices need to be developed while simultaneously engaging the problem. Social learning is the process by which groups of people cooperate to learn with and from each other. As discourse replaces the academy, social learning in knowledge networks augments and even replaces training and education.
If you are involved in workplace learning or education, consider these changes in how we communicate, organize, and work.
- Are you still focused on developing new content, as opposed to helping make connections between people and ideas?
- How are you helping people get better at creating new practices, and not just replicate old ones?
- How are you building trust so that people freely share their knowledge?
We know that machines will continue to improve. Barring the collapse of civilization, digital networks are here to stay. In the network era, work is learning and learning is the work. The job of learning professionals is to make humanity the killer app for our organizations. Work is progressing away from routine jobs and toward unique and creative work. This has to be supported through widespread opportunities for continuous learning and ways to share implicit knowledge.
More resources on automation.