This is the second post in a series that follows an Expert Workshop in Digitisation, Skills and Migration hosted by the Lowy Institute earlier this month in collaboration with the Department of Immigration and Border Protection.
The 'Fourth Industrial Revolution', as described by World Economic Forum Chairman Klaus Schwab, is characterised by a range of new technologies that are fusing the physical, digital and biological worlds. A lot of attention to date has focused on robotisation, driverless cars, cyber-weapons and biotechnology, and other developments: in this context, the effects of automation and its impact on jobs have been widely discussed. Less appreciated, however, is how digitalisation is affecting the future of work.
The digitalisation of documents, photos, personal data, social networks and just about everything else has paved the way for learning machines to translate this data and perform tasks that were once the realm of humans. This transition is in turn driving the transformation of everything from retailing procedures and corporate organisation to how we plan our cities and cure our sick.
Digitalisation has also enabled significant changes in employment. Skilled occupations are now much more accessible on a global scale, as well as more temporary and compartmentalised in nature. Workers can participate in the digital economy at any time from any place.
So why bring migration into the conversation? Migration is an important component of Australia's economic future, having been long used to fills gaps both low-skilled and high-skilled roles. Digitalisation will impact both. While migration has long been thought of as the physical movement of humans from one place to another, we are now witnessing a form of virtual labour migration. Work is crossing national boundaries through online capital, labour, and information flows.
Unfortunately, the significance of this online labour is poorly understood, not least because conventional labour market statistics are ill-suited to measuring work that is transacted via online platforms. It's often understood as 'trade', 'subcontracting', or 'outsourcing'; not as 'labour migration', a term reserved for physical migration. An entire transformation is taking place almost unobserved by policy-makers and statisticians.
One of the first (and few) economic indicators that we do have for the online gig economy is the Online Labour Index, developed by researchers at Oxford University, which tracks online labour projects. Over the past year the Index has experienced rapid and volatile growth, as shown below. The biggest sources of online vacancies (as of September 2016) were 'in' the United States (52% of the global total), followed by the United Kingdom at 6.3%, India at 5.9%, Australia at 5.7% and Canada at 5%. What is striking is that this growth occurred in the context of stagnant conventional labour markets. What is also striking is that the highest demand was for skilled work in areas such as software development, technology, and creative and multimedia tasks. It isn't just automation changing the future of work, but digitalisation and virtual labour migration as well. Many of the assumptions that underpin our current system need rethinking.
Perhaps most importantly, our assumptions about migration are being challenged. What were once perceived as controllable national borders are much more porous than we'd like to admit. This is proven daily by the sheer volume of data, capital and information that flows across our national boundaries unimpeded. And as the aging population of developed countries creates a new competition for the (youthful) best and brightest, we can't assume that a ready supply of highly skilled labour will always be eagerly awaiting offshore. Likewise, not all migrants may seek citizenship as their end goal. There is a younger generation of professionals entering the workforce who see themselves as mobile and global, with a transnational identity. They want to be able to move between countries, not just take a one-way trip to a new passport.
The trend towards increased mobility (both virtual and physical) must be a key consideration for policy makers. If work visits are shorter and more frequent, then the process to gain a visa shouldn't take longer than the stay itself. If future workers are going to be self-employed or hold a portfolio of jobs, then having a visa that is tied to a single employer, or cumbersome to transfer as employment conditions change, also creates an unwelcome barrier to labour mobility. Even the paperwork to document the many jobs that a worker has held in the past may need revisiting. And if self-employed entrepreneurs are a key part of the new economy, how do they fare in policy considerations? Governments rely heavily on signals from employers to inform them what skills are in demand. The risk is that programs informed only by traditional employer intelligence may be missing trends in alternative modes of work. And in a world where start-ups companies are increasingly important, how can the red tape that currently stops small (and regional) businesses from sponsoring skilled workers be amended?
Evidence regarding skills gaps, who is employed by whom, and where value is being generated is crucial to inform effective policy across categories of employment, education and migration and beyond. As stated above, there is still no true measure of the value of the 'internet' and technology-enabled services. It is the unique nature of digital goods that make them so hard track. Who is working to create the means to monitor and keep track of new trends? Are we thinking big enough in terms of what data we collect in a digital age?
There are mixed views on the degree to which the fourth industrial revolution will truly transform our lives. But this isn't about predicting the future. It is about testing today's assumptions in order to be ready for tomorrow. Given the complexity and inherent uncertainty about the future, it doesn't make sense to just pick a single strategy and wait to see if it works. Government needs to become more comfortable with pursuing a portfolio of solutions that allow for ongoing experimentation, learning, and adaptation. Admitting uncertainty and taking on a portfolio of experiments doesn't mean not having any strategic direction. It means creating a system that can learn for itself, based on real time feedback. Disruptions will likely unfold over decades rather than months but we have choices to make, with many possible solutions, and a lot of rapid learning to do.