The World Economic Forum’s 8 Futures of Work: Lifelong Learning is the New Black

Hot off the press, The World Economic Forum’s White Paper Eight Futures of Work: Scenarios and Their Implications is the first in a series by the WEF’s System Initiative on Shaping the Future of Education, Gender and Work. You can download a copy a here. The Paper paints a future that is dystopian, utopian and everything in between.

Why should you care? Think about this:

McKinsey’s latest report on the impact of automation and work predicts between 75-375m workers will need to change jobs or adapt in their occupations by 2030.

Frey Osborne’s latest research (an extension of their seminal earlier work) predicts 47% of work in the US, 57% in some OECD countries and 77% in China is at risk of automation.

Futurist Martin Ford (the world’s early warning signal on the changes ahead) maintains 75% of occupations we know today will disappear by the end of the century.

And here in Australia, The Foundation for Young Australians forecasts that young people will hold 17 jobs across 5 careers in their lifetime.

The WEF doesn’t endorse any one particular statistic and neither do we at the 4IR.org but what is clear is that change is ahead on a scale we have never seen before and adaption is the only path to thrive. This is what drives our determination to deliver the training that is needed for the Future of Work.

The Paper envisions eight possible scenarios for the future of work in 2030 proffered in a uni-directional fashion so don’t despair – it’s dark moving towards the light and the progressive nature of the narrative does a lot to explain what comes next. The authors are at pains to point out that the scenarios are not predictions rather designed as a basis for discussion. They are possible but not certain. The reality, they point out, is more likely a combination of one or all scenarios ‘playing out simultaneously in different geographies, industries, age cohorts and social-economic groups.’ Their focus is the most volatile variables – those that are the most impactful or uncertain.

Notable Themes

The Paper covers a lot of ground but here are the notable themes we found within and across scenarios:

  • Curricula must be agile and adaptive
  • Employers must invest in their human capital to remain relevant through perpetual learning opportunities
  • Governments should resist restricting labour mobility in order to protect their investment – in other words resist workforce autarkies (more on this below)
  • Human/technology collaboration won’t be cyborg but it won’t be far off
  • Lifelong learners will be the new black

Three Major Trends

The Paper focuses on three trends to develop their eight futures of work scenarios:

Technological Change– recent technological advancements including robotics, artificial intelligence and big data analytics have already significantly impacted job markets – resulting in displaced occupations and changed skills sets and tasks (out with the old and in with the new). The relative stability or volatility of future labour markets will depend largely on the speed of uptake of these technologies. The Paper considers two outcomes for this trend: either steady (similar to past and recent times) or fast in which change rapidly accelerates.

Learning Evolution– the extent to which current and future labour forces acquire the right skills to carry out new tasks and occupy roles driven by Technological Change is highlighted as being both highly uncertain and highly impactful. Factors considered include the ability of education institutions to adopt updated and agile curricular, access across socio-economic groups, retraining opportunities for the existing labour force and a mindset shift for students – a new mental model that embraces lifelong learning. The Paper considers two outcomes for this trend: either maintenance or the status quo (slow) or a rapid learning evolution for students and the current workforce (fast).

Talent Mobility – workers’ movement between and within countries ‘may be affected by availability of economic opportunity, travel regulations, or crises and conflict’ and could have a significant impact on labour markets in different geographies. The Paper considers two outcomes for this trend: labour concentrations largely continue where they are (low) or labour is highly mobile within and between national borders (high).

What the Key Means

Next to each Scenario the WEF has provided a key illustrating the degree of intensity of the three trends that creates the conditions manifesting the Scenario. In the example below Workforce Autarkies arise when Technological Change is Steady, Learning Evolution is Slow and Talent Mobility is Low.

Technological Change

Steady  Accelerated
Learning Evolution Slow Fast
Talent Mobility

Low

High

The 8 Futures of Work

1. Workforce Autarkies

I had to look up the definition of the word ‘autarky’ – it means economic independence or self sufficiency. It could be a good thing but in this Scenario not so much.

Scenario One considers a future where the combination of technological advancements replacing low skilled workers in non cognitive, repeatable and complicated but not complex tasks and a slow paced learning evolution results in a diminishing number of opportunities to participate in the workforce.

Enter governments and local municipalities to protect local workers (and jobs) by restricting international talent mobility. One of the long term negative impacts of this is a local labour force without the knowledge transfer so essential in innovation and economic competitiveness and a resultant reduction in local industry growth and dynamism.

Technological Change

Steady  Accelerated
Learning Evolution Slow Fast
Talent Mobility

Low

High

2. Mass Movement

This scenario follows a similar narrative to the Workforce Autarkies but deviates with workforce mobility. Here they see a massive movement of displaced workers searching for work and high-skilled talent searching for the latest and most lucrative opportunities. One outcome is a higher level of competitiveness among workers at all skill levels leading to strains on social cohesion.

Technological Change

Steady  Accelerated
Learning Evolution Slow Fast
Talent Mobility

Low

High

3. Robot Replacement

The scenario goes something like this: the skills of workers don’t track with advancements in the machines they work with hence the creation of more machines to replace workers with redundant skills. The result is fewer people contributing to the world’s production and distribution. Widening talent gaps continue to dampen economic growth as businesses lose confidence in human talent. ‘As income accrues to a limited few the economy of the past has disintegrated and conflict is on the rise’.  Governments are forced to respond with new, untested policy interventions such as ‘nationalisation of technology-owning monopolies’ (hello Google, Tesla).

Technological Change

Steady  Accelerated
Learning Evolution Slow Fast
Talent Mobility

Low 

High

4. Polarized World

No surprise we landed here. Loss of opportunity, advancements in technology striking not just the low skilled but moving up the labour chain. Large swathes of the workforce become unemployable. Opportunities and control are vested in fewer, and fewer people. There are ‘deepening and growing inequalities.’

This leads to a mass movement of people in search of employment; some to high-income, high-skilled enclaves that form ‘super-economies’. Whilst low skilled workers left behind are increasingly disenfranchised and earning meagre livings servicing the privileged few. In parallel, traditional national economies disintegrate.

Technological Change

Steady  Accelerated
Learning Evolution Slow Fast
Talent Mobility

Low

High

5. Empowered Entrepreneurs

And just in time the clouds part and the future looks bright again. Increasing concerns about the impact of rapid technological change herald reforms in education (the Paper is curiously silent on what this might look like). Companies invest heavily in training systems and reskilling and a new ethos arrives: lifelong learning. The result is a large supply of skilled, agile, curious workers. The result: more innovation, advancements across multiple industries and sectors.  In parallel, conditions are ripe for workers to create opportunities for themselves and this in turn attracts inflows of investment capital. To protect their investment governments restrict labour mobility enhancing the attractiveness of online platforms to access global markets. Many entrepreneurs shift their focus to local markets.

Technological Change

Steady  Accelerated
Learning Evolution Slow Fast
Talent Mobility

Low

High

6. Skilled Flows

The Skilled Flows scenario sees the combination of education evolution, employer investment in their human resources and a life-long learning ethos result in more workers than ever before ‘bringing a wide range of skills, and enhanced creativity, dynamism and productivity’ to the market. Online platforms for accessing global markets remain a marginal proposition resulting in a high mobility of workers across geographies. Labour markets with better local access to technology drive higher value creation with fewer resources creating a widening chasm between countries and ‘technical haves and have nots’.

Technological Change

Steady  Accelerated
Learning Evolution Slow Fast
Talent Mobility

Low

High 

7. Productive Locals

This scenario is similar to Skilled Flows but highlights that the resultant impact of systems that produce highly skilled, productive workers is an increasing demand for people to complement machines, manage the transition to new models of business and specialise in new roles and jobs. Technology is ‘applied broadly, alongside human creativity and productivity’. Economies make efforts to resist high levels of migration in an effort to retain the human capital in which they have invested heavily. High engagement in online platforms has resulted in some economies thriving. Skills shortages bite and lower levels of mobility result in dampened exchange of ideas. Livelihoods and technologies are heavily dependent on local economies.

Technological Change

Steady  Accelerated
Learning Evolution Slow Fast
Talent Mobility

Low

High

8. Agile Adapters

Conditions in this scenario parallel Productive Locals but depart where mobility is not restricted and online engagement is high. The result is a global, agile workforce. ‘Harmonized workforce, global policies and internationally standardized credentials, certifications and degrees’ lead to high levels of dynamism and growth. The downside? Not everyone can keep up and many people feel marginalised and dislocated from society.

Technological Change

Steady  Accelerated
Learning Evolution Slow Fast
Talent Mobility

Low

High

If you are an educator, worker, employer, student, elected representative or government official the manner in which the seismic change ahead is navigated will depend very much on decisive action. This Paper goes some way to providing a place to start the conversation.

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