KnowledgeWorks’ newest strategic foresight paper, “The Future of Learning: Redefining Readiness from the Inside Out,” explores how changes to the future of work will cause readiness for further learning, life and work, to be redefined and what the implications of such a redefinition might mean for the K-12 and post-secondary education sectors.
One of the major drivers of change shaping the future of work is the rise of smart machines. We define smart machines as artificial intelligence, machine learning, robotics and other forms of automation. These technologies are increasingly capable of performing tasks that humans carry out today, including cognitive and manual routine tasks that are well-defined, routine or rules-based. Such tasks are central to many accounting, transportation, construction, repair, monitoring and production-based jobs. Smart machines are also gaining the ability to perform cognitive and manual non-routine tasks, or tasks that are less well defined and that require situational adaptability, persuasion, problem solving and creativity. Such tasks form key parts of many managerial, creative, medical, caring and science-based jobs.
While we know that smart machines are reshaping work, we don’t yet know to what extent they will impact human jobs. Many projections depict high displacement, post-work futures where the vast majority of human workers have been replaced by smart machines. Other scenarios depict worlds where work and tasks have been reconfigured thanks to smart machines, but the concept of working is still the same as it is currently.
In contrast to this evidence of displacement, there are also numerous examples of how smart machines are helping human workers complete tasks. Baxter, a cobot designed to work alongside people on production lines and factory floors, is a great example. Baxter can learn and re-learn tasks with relative ease and affordability. The robot does the tasks that are repetitive and sometimes dangerous for people (for example, loading and unloading, packing and material handling), leaving its human counterparts to complete tasks that require human judgement, greater degrees of dexterity and less repetition. In another example of smart machines’ reconfiguring work, the medical industry is augmenting human intelligence and decision making by using machine learning to help diagnose illnesses.
It remains uncertain whether the rise of smart machines will cause widespread displacement of human workers or whether job creation and reconfiguration will outpace job loss. Historically, technological advances such as the rise of smart machines have typically led to the creation new jobs, reconfiguring current work and making many jobs safer, easier and more interesting. Looking ahead, smart machines’ capacity to carry out both cognitive and manual and both routine and non-routine tasks could cause their impact to be greater. We need to prepare for either possibility, or for a mix of the two.
As smart machines continue to reshape work, educators will need to consider new strategies for cultivating learners’ readiness and will also need to reconsider how readiness is defined. These challenges will be made more acute by the fact that smart machine technologies are maturing at an accelerating rate, making jobs and tasks get reconfigured, created and made obsolete at faster and faster rates.
With the future of work unfolding all around us, how do you see smart machines impacting the future of work, and what will their rise mean for readiness?