The “future of work” has become a hot topic in recent times, in large part due to rapid developments in digital technology. Exponential development and growth can be seen in processing capacity, data volumes and numbers of internet connected devices. Just as compounding interest has its greatest impact on savings in later years, so too, the impacts of developments in digital technology have been building slowly over time.

We are now riding a wave that is ready to break, bringing significant disruption to global labour markets. Previously the impacts of automation were only felt in low-skill and less well paid jobs but the capability of artificial intelligence and machine learning will soon encompass tasks being performed in well-paid and skilled jobs, across all sectors of the economy.

Where will change happen?

There is considerable variability in estimates of job losses (estimates range from 9 per cent to 47 per cent) but, at least in the medium term, it will be the jobs that are more routine or rule-based that are most vulnerable to automation.

In reality, many of us perform a mixture of routine and non-routine tasks in our jobs. Rather than losing our jobs, we are likely to devolve routine work to the machines and spend more of our time on other tasks.

As these adjustments occur, even workers within the same occupational group may experience different impacts. As an example, accounting graduates may find it more difficult to find work in the future because the transactional accounting roles that were traditionally performed by graduates are being automated.

However, experienced accountants will remain sought after for their ability to analyse and derive recommendations from complex financial data. For truck drivers working on busy roads, the potential for automation may be limited because of safety concerns and regulatory restrictions. Yet at remote mine sites, automated vehicles are already in use because they reduce human workers’ exposure to dangerous and dirty work environments.

The variability of these impacts are clearly illustrated in the figure below, which models automation impacts for each of the major occupations in the Australian workforce. In some occupations the impacts of automation are low and we may see wages increase as workers use the new technology to perform their work more efficiently or add value in new ways. However roles which require less creativity, involve less uncertainty or depend less on relationship building (e.g., salespeople in very transactional roles) will disappear as the human worker is replaced by a machine.

A chart

Modelling Impacts from Automation in Occupational Groups ©Reeson, Andrew; Mason, Claire; Sanderson, Todd; Bratanova, Alexandra; Hajkowicz, Stefan. The VET Era Equipping Australia’s Workforce for the Future Digital Economy. Canberra: CSIRO; 2016. CSIRO:EP163744

Trends in the workforce

Researchers at CSIRO’s Data61 have been examining trends in the labour force and their work provides some unexpected insight into the way in which demand for skills is changing over time. By linking Australian Labour Force Statistics (produced by the Australian Bureau of Statistics) with skills data captured by the United States Department of Labor, Employment and Training they have been able to identify (based on the changing patterns of employment in the Australian economy) which skills and abilities are becoming more or less important in the workplace.

For clarity, the skills and abilities are clustered into three categories:

  1. Science, Technology, Engineering and Maths (STEM) skills
  2. Communications skills
  3. Technical skills.

Up until recently, there has been an assumption that increased reliance on technology will translate into greater demand for workers with traditional STEM skills (programmers, mathematicians and physicists). Instead what the data reveal is that it is occupations that require people skills (active listening skills, negotiation skills and a strong service orientation) which have been growing fastest. In a world of human and robot workers, the human outperforms the robot in the relationship domain. A machine can be taught to write code but it has not yet developed the capacity for empathy and understanding.

A chart

Demand for communication skills has been growing fastest.  ©Reproduced from: Reeson, Andrew; Mason, Claire; Sanderson, Todd. Growing Opportunities in the Fraser Coast: Informing regional workforce development. Brisbane: CSIRO; 2017. csiro:EP175939.

The growing importance of people skills in our labour market has also come about because most Australians now work in the services sector. As our population ages (and the incidence of mental disorders, chronic diseases and obesity continues to rise) and as we re-skill and upskill (in response to rapid technological developments) demand for workers in health care, aged care, education and training will continue to rise. The delivery of services requires people-centric skills and these skills are not likely to be automated soon.

Technological disruption and our future jobs

In previous waves of technological disruption, more new jobs have been created than have been taken away. For this next wave of disruption, new roles will similarly emerge.

Perhaps online chaperones will help us to manage our digital identity and security while health and lifestyle paraprofessionals may replace doctors and nurses as the first point of contact with aged care recipients.

It will not be necessary to become a software engineer or a data scientist in order to find work in the future. However, in Australia’s high cost labour market, the capability to deliver our work more efficiently through using the latest digital technology is vital. We don’t need to be able to program machines but we do need to work with them. For this reason, the ability to learn and adapt to working with the latest technology will be a prerequisite for employment.

Future proofing our workforce is about empowering people to use technology in their jobs, so that the routine tasks are taken care of and the human worker can focus on adding value in ways that the machine cannot – by helping a customer find a solution to an ill-defined problem, by personalising an automated service or product or more fundamentally, by ensuring that customers still feel understood, supported and valued in our more automated world.