The world of work is changing fast, and the robots are knocking at the door. Human and machine collaboration is now emerging as the biggest revolution to hit our workforce in over 250 years. Machines are racing to this collaboration-state at a rapid pace, with advances in natural language processing, autonomous driving and neural networks occurring on an almost daily basis.
But what about their soon-to-be human colleagues? Well, according to the World Economic Forum, by 2020 more than a third of the core occupational skill sets needed in the workplace will include skills that are not currently considered crucial and fundamentally are not been taught in our educational institutions. This could place humans, and organizations, at a distinct disadvantage in the near future. And the disadvantage is not one where the omnipresent robots steal our jobs either. Rather it’s that both parties (machines and humans) need one another in order to increase productivity. Machines will, and already are, providing the science of the job the computational and analytical tasks that they can perform at scale, speed and accuracy ahead of humans. Whilst humans will provide the art of the job, the empathetic, social and creative inputs that add true value to work.
But does that mean that our children need to primarily focus on “soft” skills to future proof themselves? Well no, the answer is by no means as binary as that. To drastically over simplify the issue, human workers will need to deliver on three core elements in industry 4.0. These are:
- Building: this is the grunt work of industry 4.0, the coding and DevOps of our automated colleagues and systems.
- Creativity: the creativity aspect that’s needed in a digital-first world cannot be overemphasised. The vision and UX expertise in building automated systems has already proven to be a key differentiator between digital superstars, Amazon for example, and those who haven’t quite made the grade.
- Leadership: This is one element that is nearly always overlooked when we speak about future skills development, but arguably it’s the most critical. Leaders will need a complex array of behavioural characteristics and skillsets to effectively lead in an enhanced workplace. Preparing this future crop of leaders is vital.
But how are we to arm our workforces for effective collaboration with machines? Ultimately, human learning will now need to pivot on how we interact and work with machines. And only through relating to machines as affective co-agents in our lives can we begin to understand what learning with machines might mean for all of us. We can unlock many learning experiences about machines we live and work with today. But without thoughtful planning and execution from educational institutions and business leaders, collaboration between humans and machines may not be the likeliest future outcome.
Ultimately educational institutions and enterprises need to jointly and individually reengineer how they educate for successful collaboration between man and machine. These organizations and institutions need to understand and qualify future disruptions by examining how and where they’re coalescing and how work and lifelong learning has to change around them. An upcoming investigation by the CFoW will highlight the changing nature of learning and examine how educational institutions and corporations must embrace new learning models in order to effectively develop tomorrow’s talent.