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Preparing For An Uncertain Future Of Work

How do we prepare students for jobs that don't even exist yet?

By Jason Swanson

How do we train students for jobs that don’t yet exist? If you are an educator, a parent, or an employer, I am sure you have pondered this question.

To add potentially more stress to it, the future of work feels increasingly complex and uncertain. There is quite a bit of speculation as to what impact factors such as artificial intelligence (AI), automation, globalization, and taskification (the breaking up of large jobs into small tasks) might have on the future of work. For example:

  • Might we experience an abundance economy where artificial intelligence and automation drive consumer prices down and eliminate boring and dangerous work?
  • Might most people be forced into contingency employment, competing with one another to assemble a mosaic of paid work?
  • Might the vast majority of people find themselves out of work as the march of automation accelerates and human workers are replaced faster than new jobs can be created?
  • Might work be redefined as artificial intelligence and automation eliminate the majority of jobs, leading people to work on task and projects based on their passions rather than on the need to generate income?

In reality, the future will probably contain shades of all the above, along with other developments that we have not yet considered.

Trends Shaping the Future of Work

What we do know is that work is changing; what we don’t know is to what extent. For example, there is little agreement on the long-term effects of automation and artificial intelligence. A 2013 study by Carl Benedikt Frey and Michael Osborne of Oxford University suggests that 47 percent of current middle-class American jobs could be lost over the next two decades as computers take over cognitive tasks in areas such as management, finance, medicine, science, engineering and the arts. In contrast, James Bessen of Boston University argues that rather than destroying jobs, automation has historically redefined them, helping companies free up financial capacity and then expand or offer new services.

Even if we take drivers of change such AI and automation out of the mix, the world of work is still in flux. The average worker in the US now holds 11.7 jobs in his or her lifetime, an excellent reminder that most of us already experience a fair degree of churn. We can expect that number to rise as the way people organize work changes. One factor that will likely contribute to such an increase is the rise of the contingency-based workforce. McKinsey Global Institute estimates that 54 to 68 million people in the United States already work in the project-based economy (i.e., as contingency-based employees). This number is expected to increase thanks to factors such as the lower coordination costs provided by the Internet and the continued proliferation of digital platforms that help match candidates with organizations seeking to complete a task.

Best if Used by…

Whether AI and automation lead to new job creation or to high levels of job displacement, we can expect the way we define and complete work to change. Technological advances have a long history of altering how people complete work, making jobs safer and less routine. Looking ahead ten years, we can expect increasingly to partner with technology to complete work, even if what constitutes work comes to be radically redefined, with people pursuing things such as social good or passion-based projects rather than working to make a living or people opting in and out of work when they choose. We can also expect the structure of work to change as more and more people enter the contingency-based workforce, possibly working several different kinds of jobs or projects concurrently in a far cry from traditional notions of career. Lastly, we can expect that many people will be working in jobs that do not exist today.

These expected changes point toward a future of work where the shelf life of skills will be shortened dramatically. The changing structure of jobs might mean that one indiviudal could be doing very different things from one project to the next. Bigger picture, the tasks in which we engage and the nature of our contributions to work will likely change quickly as machine partners do more and more for and with us. We will be likely to need just-in-time training to keep up with work’s changing demands, with new skills enduring for far less time than they do today.

A Hardware Upgrade

So how do we prepare today’s students to be tomorrow’s workforce?

One answer might be by helping them cultivate deep self-knowledge and meta-cognitive skills. In other words, focus on upgrading a learner’s hardware (how to think, learn, and unlearn) rather than their software (skill acquisition and knowledge recall), promises to be the best way of ensuring that learners are ready for a future of work, no matter which future of work comes to fruition.

Due to the uncertain nature of future work, skills and practices such as deep self-knowledge, social awareness, emotional regulation, self-determination and proactive learning will become increasingly important. For instance, in a future of work where employment structures are increasingly contingent, a learner will need such skills to manage time if they are working on many different projects, to seek skills to complete those projects and to have the emotional intelligence to partner with both people and machines from across the globe. In a post-work world, such skills might be equally important, helping people create subsistence strategies, pursue community-impact initiatives, and start passion-based projects rooted in their values.

Cultivating core social-emotional skills and foundational cognitive and meta-cognitive practices also promises to assist individuals in creating bold aspirational visions for themselves and in navigating terrain that today can only look uncertain, even uncharted. Focusing on these skills can provide the foundation for both near-term career pathways and future career creation and success.

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