Appendix1

Our modelling assumpstions

As part of the 2017 US study, Cisco and Oxford Economics assembled a team of technology experts to engage in an interactive workshop and develop a detailed hypothesis about the likely progress of technology over the coming decade. Participants were tasked to form a collective judgement on the future capabilities of a range of technologies, including artificial intelligence, advanced robotics and IoT, and how they would change the nature of work. They were asked “To what extent will businesses become more productive at performing certain tasks, such that fewer workers will be required to produce the same output?”

They considered the extent of technological progress, as well as the rate of business investment, and other institutional, political and infrastructural challenges that defined the context in USA. This helped us formulate a set of consistent task-based productivity assumptions across 41 workplace tasks that are a key input to our labour market modelling framework.

Below is a summary of the results from the interactive workshop applied to the Australian labour market, aggregating the 41 workplace tasks into 10 task clusters.

Limitations of the study for sector-specific insights The principal modelling challenge for this study is to explore long-term implications of technological change on Australia’s labour market. We developed generic, task-based assumptions about how technology will change enterprises’ capabilities over the period, which can be mapped to the entire labour market via the task-profiles of different occupations, and the occupational mix of employment in different sectors. For this framework to hold, one must assume that, over a 10 year period, if technology is capable of performing a certain task in one sector, e.g. observing the quantities of things on a food production line using pattern recognition technology, then the same broad technological solution will be applicable to all sectors in which observing the quantities of things is required, e.g. a security guard at an entertainment venue. This framework enables us to take a cross-sectoral perspective on the potential impact of a single technology scenario over a 10 year period, based on the task-content of work in each sector. However, it does not allow for a more contextual understanding of the sector-specific barriers – or catalysts - that might differentiate that impact over time. This limitation should be considered when interpreting our sector-level outputs. The ultimate impact could be greater or smaller than the central case presented, depending on sector-specific factors affecting the rate of technology adoption.