Global policy leaders are starting to identify the competencies that learners will need for the new emerging economy - so what does this mean for learning? How can we prepare for the social and political disruption that is likely to emerge as a result of workplace disruption due to automation? How can we develop a set of competencies and knowledge in learners that will enable them to adapt to what's coming and prosper?
At The Future Learning Project we ask critical questions and explore the global factors that are shaping the future of learning. This week, we look at job losses due to automation, and how learning can help people be prepared. Our focus is:
1. The factors that indicate why education systems need to change, despite these systems being structurally resistant to innovation and new ideas.
2. Why learning needs to be disrupted - our social, political and economic wellbeing may very well depend on it.
3. Why the gap between knowledge and skills learned in schools and knowledge and skills needed in the real world grows ever wider.
4. Why low-skilled workers most at risk of disruption can be the most resistant to retraining or up-skilling opportunities.
To start, The World Economic Forum and McKinsey have shared insights from Davos on the future of learning and work and the Fourth Industrial Revolution. Tri-sector collaboration (government, business and civil society) was a focus of policy makers' discussions about how we can be prepared for sweeping changes and opportunities in the workplace. The conversation quickly turned to education:
"Policy leaders immediately began discussing how education systems could be retooled to train the millions of data scientists, machine operators, IoT architects, and engineers that will be required in the future."
The context of this conversation was manufacturing, which faces significant disruption from automation and opportunity for innovation in Economy 4.0. It will be interesting to see what form this 'retooling' of education systems takes, and how this will be contextualised and realised within different learning systems. It will also be interesting to see what happens to the arts within all of this.
Education systems are famously resistant to change. Indeed as we've seen from research into personalised learning in America recently, opposition to innovation appears to be hard-wired into the design of the system itself. The systems and structures to innovate through a culture of risk-taking, prototyping, iteration and dissemination are not built into traditional school structures. In addition, bureaucracies governed by rules, specialisation and hierarchy are also not designed to support innovation.
The idea of 'retooling' a system may sound attractive, but education systems are not manufacturing, and our concerns are to think they can be similarly transformed underestimates the national effort and significant investments in political will, money and time that will likely be necessary.
Our next article this week comes from Brookings Brief, looking at the likely political and economic fallout from large scale automation and job disruption. The article references several pieces of research that indicate that increasing automation and computerisation of work is likely, with up to 50% of US jobs automated within 20 years, and 30% likely to be disrupted by the year 2030.
The pain will be felt by lower-skilled workers, as these are the roles most likely to be automated, and if workforce disruption is as significant as predicted, social and political turmoil is a very real possibility for decades to come. More low-skilled workers will compete for fewer positions, wages will continue to stagnate or fall, and the inequality gap will grow, raising the risk of serious social disruption. Even if work disruption is not as large as feared, social challenges will still be significant, and there will likely be implications for how governments respond, with some fearing a trend towards authoritarianism.
Let's get in front of this by having a discussion about the coming disruption of work as a matter of urgency. We need to figure out what learning in our schools needs to look like to meet this challenge, and then understand what needs to be done to make it happen. Let's also talk about the new positions and work tasks that will emerge as human work is augmented by machines - workers can be up-skilled and retrained. Whose responsibility is this?
Continuing in this theme, our next article from The Guardian newspaper shares growing alarm about the coming reality of automation in the British job market, and why political systems and society are almost completely unprepared for what's about to happen. Whole regions of Britain are at risk of sweeping job losses due to automation, because clusters of at-risk industries such as retail, manufacturing, mining and agriculture lie within certain geographical areas.
The article argues that radical plans are necessary, but automation of jobs unfortunately does not appear to be on the current government's policy agenda. If preparations were to be made, learning in schools would be at the forefront, with an attempt made to "maximise the numbers (of people) skilled enough to work at higher tiers". In an education system that teaches children to code in a manner that is 19th century in its delivery, a radical transformation will be needed, at huge political and economic cost.
Education globally needs to be disrupted. Learning must develop a set of competencies and knowledge that will prepare students for life-long learning and enable them to adapt to what's coming and prosper from new opportunities. The danger is that the more things stay the same in our schools and education systems, the gap between what students are learning and what they actually need to learn grows ever larger. Traditional school-based learning may lose its relevance to an even greater degree.
To conclude we have an interesting research summary piece about the risks of job automation in OECD countries. Of particular note is that training participation rates in jobs at higher risk of automation is significantly lower than those in other jobs. This is similar to research we have seen of coal miners in America turning down retraining and awaiting the reopening of their mines, despite new opportunities being available. Education gets a mention towards the end, with reference to how learning systems will need to adapt to the changes being brought about by automation and technology adoption. Details are light, but there are references to cognitive and social intelligence, and learning skills needed to function effectively in a digital context.
What is the reason for the reluctance to retrain? Is it because the jobs at the highest risk of automation are low-skilled? Is it because these workers are not accustomed to a mindset of continuous learning?
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