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This article takes a look at just a few of the different elements that make up Industry 4.0: automation, the use of artificial intelligence and examples of how these are applied in practice. We look at implications for workers, what learning needs to look like so that people can thrive, and why the present focus of most education systems is both insufficient and ineffective.
‘Too much time discussing whether robots can take your job; not enough time discussing what happens next.’
Our first article looks at implications for jobs in the age of automation: lower worker skill means lower wages, along with less job security and fewer benefits. Two classes of intervention and support for workers are identified:
1. A ‘quasi-Luddite’ approach, in which automation is either slowed or reversed through measures such as taxing products produced by robots or automation.
2. Developing ‘coping strategies’, in this case a) a universal basic income (UBI) and b) retraining and up-skilling of workers.
Each is recognised as being insufficient – given emerging trends, derailing automation is unlikely to work, and we don’t know enough about how UBI and worker retraining is going to work. That’s exactly what the article concludes – there needs to be a lot more research into exactly how we intend to manage this transition, and identify which interventions are likely to succeed.
But first, let’s start the conversation – in our case, and about what automation means for learning in all its forms.
The nature of work in almost every occupation and work-related tasks is expected to be affected by automation by the year 2030. This does not mean that all jobs will disappear, merely that many will be augmented by automation or new jobs will be created. With augmentation and the creation of new jogs thanks to rapid technological advancement come the need for new skills and competencies, and McKinsey has identified the following as being essential:
1. Demand for advanced technological skills such as programming will grow rapidly.
2. Social, emotional, and higher cognitive skills, such as creativity, critical thinking, and complex information processing, will also see growing demand.
3. Basic digital skills demand has been increasing and that trend will continue and accelerate.
One of the ten challenges identified in this article is ‘Evolving education systems and learning for a changed workplace’. Learning systems such as schools and higher education providers need to focus on developing skills and competencies such as higher order thinking and life-long learning habits.
“There is work for everyone today and there will be work for everyone tomorrow, even in a future with automation. Yet that work will be different, requiring new skills, and a far greater adaptability of the workforce than we have seen. Training and retraining both mid-career workers and new generations for the coming challenges will be an imperative.”
Are our students and education systems prepared for these coming changes? What conversations do we need to have within our schools and learning communities?
From McKinsey Global Institute, research examining the effects of exponential technologies and disruptive innovation on the workforce of tomorrow. Four key questions addressed within the research are:
1. How will demand for workforce skills change with automation?
2. What are shifting skill requirements in five industry sectors (manufacturing, banking, retail, energy and healthcare)?
3. How will organisations adapt?
4. How will we build the workforce of the future?
The research notes a likely decline in routine manual and cognitive work performed, with an increased demand for workers with social-emotional and technological skills – this aligns with research we have seen from the World Economic Forum (WEC). Each sector faces significant structural changes, for example more complex data and customer management within banking, growth of care for the elderly in healthcare, and automation of manufacturing. As more retail moves online, supply chain and inventory management is becoming more automated, and future opportunities lie in customer services and technology deployment and maintenance.
Organisationally, companies will need to instil a culture of life-long learning, and adopt a team-based, agile approach to work. As we have also seen in earlier posts, the number of contractors will also rise. In building their workforces, companies will likely need to focus on staff: retraining and/or redeploying them, hiring them, contracting out work, and letting people with redundant skills go.
So what are the implications for learning? From a higher education perspective, few respondents and companies in the research identify higher education providers as being potential partners in developing the workforce of tomorrow. Schools are not mentioned, but learning is, and according to this research ‘skills’ are the focus and the challenge.
Understanding the importance of life-long learning and developing skills and competencies such as collaboration and an ability to function sensitively and effectively in any context develops over a period of time, and needs to be practised. Today’s 10 year olds will be entering the workforce in 2030, and we need to think seriously about the skills and competencies workers need, and how learners will develop them throughout their schooling.
We may see more of this in coming years – workers striking due to fears of their jobs being replaced by automation. Although it’s still early days, food workers’ unions are concerned about the growing use of food service robots, some capable of making 400 custom burgers to order hourly. Unions do not appear to be against the idea of technology and innovations that create and improve jobs, just as long as there are net gains for workers.
It’s a good idea for unions to start negotiations before automation becomes commonplace, as they are more likely to be negotiating from a position of strength. They are aware of issues surrounding the rise of exponential technologies and disruptive innovation, preparing as a result, and will hopefully achieve good outcomes for their people.
What about teachers and schools? Are they aware of what’s happening and adjusting their practices? Are families and students informed about how work is likely to change?
The World Economic Forum shares a report from the McKinsey Global Institute about the changing nature of work and the 3 key skill sets for the workers of 2030. Again, as we have seen in previous posts and research, jobs requiring routine physical and cognitive skills will decline as they are automated, and the demand for higher-order thinking, social and emotional skills and technical know-how will increase.
Today’s 10 year olds will be 18 and about to enter the workforce in 2030 – will the education they receive develop the competencies needed to thrive in the new era of work? If not, how do we get things to change? Where does the impetus need to come from?
The first optimistic look at automation and loss of jobs to AI via Futurism argues that while job loss is inevitable, it needn’t necessarily be a bad thing. Jolene Creighton envisages a world in which AI is woven into our very existence, and the role of education has changed from learning skills in order to work to a life-long learning according to ever-changing job requirements.
So who’s responsible? Will companies absorb the cost of learning? Governments? Workers? Will they form learning partnerships? Will industries with skill shortages be subsidised? Will good jobs exist? Will wages be high enough?
Are our schools having these conversations with students? Are case studies of changes within local industries being conducted by students? Are they interviewing business owners, leaders and politicians?
The work to address the issue of education and learning within the context of automation and disruption of work has barely begun. We need to rapidly transform how we learn and develop human potential, and the work must start now.
Our second optimistic article is also via Futurism, shared from the World Government Summit in Dubai. While many worry about the disruptive negative effects of AI and automation on people’s jobs, Sebastian Thurn argues that we may instead become superhuman workers, with AI enhancing our abilities. AI will be left to tackle the routine cognitive tasks, while humans focus on their unique ability to create and invent.
The timeline for realising this transition is mixed, but most are agreed that by the year 2030 AI will be well advanced and have had a major impact on many industries. Today’s ten year olds will be 19 years old in 2030 – just entering the workforce and university.
Do our education systems reflect how transformationally different the world of work is likely to be? Will traditional jobs even exist? What skills will they need? How can we help them be better prepared?
The research conducted and insights gained during the writing of this article have inspired the Indigo Schools Framework, the details of which can found in the Primer on our Resources Page. Send us an email at email@example.com or complete the form below if you’d like to learn more about how the Indigo Schools Framework can be successfully applied within your school. Also be sure to follow us on Facebook and Linkedin for our latest updates.