Automation Skills - DeakinCo€¦ · Automation Skills: Preliminary Research Paper P a g e | 5...

Automation Skills

Preliminary Research Paper

10 August 2017

Automation Skills: Preliminary Research Paper P a g e | 2

Table of Contents Executive Summary ................................................................................................................................ 3

Introduction.............................................................................................................................................. 5

Project purpose ............................................................................................................................... 5

Background ..................................................................................................................................... 5

1. What is automation? ....................................................................................................................... 7

Automation from a human capabilities perspective......................................................................... 8

Automation beyond human limitations ............................................................................................ 9

2. How will automation affect Australian industry? ............................................................................ 10

Global technology disruption and Megatrends .............................................................................. 12

3. How will automation affect the Australian workforce?................................................................... 13

4. What skills will the Australian workforce need? ............................................................................ 16

5. What are the implications for training products? ........................................................................... 19

Findings from training package analysis ....................................................................................... 19

Insights from ANZCO occupational data ....................................................................................... 22

Possible action for competency development ............................................................................... 23

Issues for further consideration ............................................................................................................. 25

Glossary ................................................................................................................................................ 26

References ............................................................................................................................................ 28

Appendices ........................................................................................................................................... 32

Table of Figures Table 1: Current automation technologies compared to human performance across 18 capabilities .... 8

Table 2: How human capabilities may be replicated using types of automation technologies ............... 9

Figure 1: Australian industries and opportunities to grow and transform using automation ................. 11

Figure 2: Megatrends reshaping our future ........................................................................................... 12

Figure 3: Workforce impact – automation and computerisation ........................................................... 14

Figure 4: Global impact of automation and computerisation on jobs by 2020 ...................................... 14

Figure 5: Distribution of job categories against probability of computerisation ..................................... 16

Figure 6: Future of work for today’s 15-year-old ................................................................................... 17

Figure 7: Three skills dimensions for future work ................................................................................. 18

Table 3: Typologies of future skills (non-technical soft skills) ............................................................... 18

Table 4: List of SSOs and IRCs ............................................................................................................ 20

Acknowledgments Desk research and the initial scan of training packages for this project have been conducted by

Marcus Bowles and Fran Corrigan in collaboration with DeakinCo. Funding for the project is provided

by the Commonwealth Government through the Department of Education and Training.


Executive Summary Historically, the productivity and progress of human society has depended on our most effective and

versatile resource: our own human abilities. While new technologies have vastly changed what can be

achieved and how, they have not escaped dependence on human labour, creativity and intelligence.

However, we are now reaching a point where technologies are going even further and are now

matching or surpassing many human abilities at a level not seen before. The nature of these

technologies suggests we are entering a global period of economy-wide automation and resulting

labour market transformation.

Automation can involve a range of technologies, such as computerisation, artificial intelligence (AI),

data analytics, robotics and nanotechnology. However, automation is not just about technologies, or

technological disruption, or even the replacement of human workers in certain jobs. Rather, it is a

transformation of the nature of work.

The current public narrative surrounding automation is that it drives economic growth and improves

human productivity, but at the cost of jobs. This narrative does not adequately describe what

automation is, nor the wider environment in which it is occurring. The reality is while automation will

be ubiquitous across industries, businesses and occupations, deployment will neither be consistent in

extent nor speed. Machines may replace routine physical and cognitive tasks, but it is where

machines and humans form powerful combinations that future business and employment

opportunities will reside.

A focus on lost jobs unnecessarily deepens public anxiety and does not encourage constructive

thinking about the future workforce skills we need to flourish in a world of work that is enabled by

automation.

The focus of this project is on ensuring we have training packages in place that support the

development of skilled workers needed to support automation-enabled change and growth; and that

the training system can prepare people for the jobs of the (very near) future.

This paper brings together desk research on the way that automation is transforming Australian

industry and workforce requirements, and an initial scan of VET training products contained within

training packages to identify key discussion points for consideration by the Automation Skills Project

Reference Group. In summary, these discussion points can be divided into themes as outlined below:

Defining automation

• For the purposes of this project, ‘automation’ can be defined as the use of

technologies to improve processes and outcomes that substantially reduce reliance

on human involvement.

• Automation involves the use of a wide range of technologies, systems and processes.

• What can be automated is evolving as technological development moves beyond

physical functions to encompass cognitive functions.

Impact of automation on industry

• Routine and high-volume work will be most readily automated, and the increasing

sophistication of automated solutions means that these criteria will be more important

than the level of difficulty or complexity of the task.

• All industries are impacted by automation to varying extents and at varying speeds.

• Mature and new industries will be equally reliant on automation to harness operational

efficiencies, reduce costs, enhance speed, improve sustainability and reliability, and

increase productivity.

• Job displacement will be uneven and difficult to predict across occupations, industries

and locations.

• Even more difficult to predict is the new range of jobs and roles that will be created by

automation activities.


• The way that emerging technologies will shape automation in future for each industry

and occupation cannot be accurately predicted.

Future workforce skill requirements

• Soft skills and transferable skills will be valued as jobs transform and workers need to

transfer skills horizontally across occupational and industry boundaries.

• Formal and informal learning in a lifelong, continuous process will enable people to

navigate technological disruption to their work and career pathways.

• While all work will be affected in some way by automation, most competency

standards will still cover a wide range of work functions that will still be needed for

decades to come, as mature technologies will continue to survive in large parts of our

economy including with small business and regional workplaces.

Impact of automation on the VET sector

An initial scan of training packages found that:

• No competency standards directly address the skills required to design and

implement automation

• Training packages that are extremely exposed to the impact of automation include:

transport and logistics, construction, property services, information technology,

manufacturing, and defence. However, many occupations contained in other training

packages are also expected to be highly affected by automation.

• At least 280 units of competency contain an activity or component that involves

automation

• The majority of units of competency describe one or more work processes that could

conceivably be replaced by some type of automation


Introduction

Project purpose The Australian Industry Skills Committee (AISC) has identified emerging themes that are affecting

future workforce skill requirements across Australian industry. Automation is one such emerging

theme that will have a profound effect on future work.

Skills Impact have been commissioned to identify skills needs that are shared by multiple industry

sectors in relation to automation, and to develop a Case for Change recommending training package

developments and modifications to address the identified cross-industry skill requirements.

This paper brings together desk research on the way that automation is, and in the near future will be,

transforming Australian industry and workforce requirements, and an initial scan of VET training

products. Throughout the paper key discussion points have been identified for consideration by the

Automation Skills Project Reference Group.

The next phase of this project includes extensive consultation with stakeholders and further

examination of current training packages to inform the development of recommendations for the

development and modification of training package units of competency, skill sets and qualifications.

Appendix 1 contains a draft consultation plan and survey questions.

Background This report occurs against a backdrop of often dire predictions as to the job losses automation will

trigger in Australia and across the globe. When the well-respected Committee for Economic

Development of Australia (CEDA) reported in 2015 that 40 percent of Australia’s workforce, or more

than five million people, could be replaced by automation within the next 10–20 years (CEDA, 2015),

the topic attracted attention. Unfortunately, both the context for such statistics and the underpinning

research on the wider impact of automation (Frey, Osborne, & Holmes, 2016; Frey & Osborne, 2013;

World Economic Forum [WEF], 2016; CEDA, 2015) have failed to attract similar levels of attention.

For educators and policymakers alike, what has been left is a call to action. As stated by Adi Gaskell:

What each of these reports have in common is their advocated response to the

threat of automation. All highlight the growing importance of education, and the

ability of people to adapt quickly to changes in the labor market. (Gaskell, 2016)

What is missing from this call to action is more precision as to the nature of the threat to specific

vocations in Australia and potential skilling responses. Due to growing innovation in automation

technologies and applications, the challenges in defining automation outcomes and establishing its

relationship with other technological disruptions that will equally affect future work, are extreme.

Identification of how automation relates to computerisation, robotics, AI and a myriad of other

technological development in fields such as machine learning, sensors, cloud computing, cognitive

computing, virtual reality (VR) and augmented reality (AR), the Internet of Things (IoT) and big data

requires significant effort.

The main challenges confronting any nation seeking to establish how education and training systems

can respond to automation include:

Predictive analysis – can we accurately predict how certain technologies will match or

surpass many human abilities?

Responsiveness – can education and training systems respond to both wide scale

industry and discrete job-specific skilling needs? Given global production, distribution and

communication systems, the diffusion and adoption of automation technologies is

accelerating.

New funding models – given the findings of various reports, there is potential for

substantial economy-wide impacts as workers affected by automation face changes to

their employment. Can governments invest time and resources in vocational education


and skills training in a pre-emptive manner so that regions can attract new industries and

workers can stay in work or transition to other employment opportunities?

Flexible delivery – if the analytical reports on the extent of occupational impacts of

automation prove accurate, the scale of training demand is likely to test the capacity of the

training system. Further, the capabilities of the training system are also likely to be tested

because the system needs to further extend its offer to a range of ages, abilities and

stages of professional life.

Personalised but national – research suggests that while some jobs will and are

disappearing entirely, most roles are being changed or displaced to varying degrees by

automation. Skills training will need not only to be national—targeting many industries

where common activities and tasks will be automated—but also to directly enhance how

individuals respond to automation and develop transferable, employable human

capabilities that are more likely to resistant to being replicated by machines in the

foreseeable future.

This paper uses five questions to clarify thinking on the issues noted above:

1. What is automation?

2. How will automation affect Australian industry?

3. How will automation affect the Australian workforce?

4. What skills will the Australian workforce need to establish and grow the automation-

enabled industries and to support automation enabled processes?

5. What are the implications for training products?


1. What is automation? The field of automation now extends well beyond its origins in manufacturing to encompass a growing

range of technologies, industries and applications. This means that there are numerous definitions of

automation, and they vary in scope according to the technologies, applications and priorities of their

time.

For the purposes of this project, the following definition is proposed:

Automation is the use of technologies to improve processes and outcomes with

substantially reduced reliance on human involvement.

The primary focus of automation is the discovery, design, testing and application of technologies that

can match or surpass human abilities and so remove human involvement within the automated

process and to do things that cannot be done without automation.

Key themes in this definition include:

Technology – automation involves the deployment of an extensive range of technologies.

This range is likely to grow as innovations, convergence and breakthroughs continue to

occur. This means that it is not useful to define automation in terms of particular

technologies, nor can any study of automation predict how different technologies will

converge or combine to impact future skill needs (e.g. machine learning and

computerisation, robotics and AI).

Routine tasks – automation involves using technology to perform a routine or

transactional process. That process relates to a bounded and defined unit of work, or task.

Such tasks may occur in any job role, across any occupation or industry.

Automatic, without human involvement – the defining feature of automation is that it

removes the need for human involvement within the automated process itself. Instead,

human involvement is shifted outside the automated process, potentially to roles in the

design, use and maintenance of the automated system or to other activities. Automation

skills largely emphasise the discovery, analysis, testing and evaluation of technologies for

automation or involve situations in which humans work alongside automated processes.

Automated systems can learn – technologies can now learn, adapt and improve their

own functioning. This means automated systems are not necessarily static. As with voice-

automated call centres, machine learning in educational marking and assessment

systems, and AI used in driverless vehicles, human interaction with automated processes

and technologies will also be flexible and contextual.

Not just physical activities – technologies can now automate a range of human-centred

activities:

• social and emotional – output, reasoning and sensing

• natural language – understanding and generation

• cognition – patterns, reasoning, creativity, etc.

• sensory – perception, special assessment and judgement

• physical – motor skills, navigation and mobility (including logistics, manufacturing and

robotics)

• process – robotic process automation (RPA) is automating physical, informational and

transactions systems such as processing, production and service systems (Manyika

et al., 2017).

Four dimensions to automation can usefully be deployed to differentiate the fields of research into

automation:

1. redesign of processes – making use of automation technologies to enhance

production, supply chain, logistics and service processes

2. deployment and maintenance of automated systems and technologies

3. automation as a stimulant for innovation and new products or business models


4. ongoing efforts to redefine and redeploy human skills using automation

technologies.

Automation can be further refined by understanding different typologies. Traditionally, automation has

been seen as having three main typologies:

fixed – the deployment of technology or machines designed to automate a fixed sequence

of activities, a process or a series of related tasks (e.g. assembly, painting or weaving)

programmed – technology designed and deployed to change operations to accommodate

different sequences of activities, process activities or tasks (e.g. batch production)

flexible – technology programmed not only to respond to fixed variations but also to learn

and adapt to the situation (e.g. service bots).

Technological development has radically altered what tasks can be automated. Even a fixed

automation approach can now move from a focus on replacing human physical functions to

encompass cognitive functions. As a result, the use of automation to enhance productivity and

improve process efficiency and capability has extended to encompass all industries.

Automation can be explored from three viewpoints:

1. Disruptive technologies and automation enablers

2. Automation from a human capabilities perspective

3. Automation beyond human limitations.

Automation from a human capabilities perspective It is useful to have a conceptual scheme for understanding the nature and role of different automation

technologies. Given that the defining feature of automation is that it removes the need for human

involvement within an automated process, one way to explore automation technologies is in terms of

the human capabilities being automated. This is the approach used in MGI’s work (Manyika et al.,

2017), which defines 18 human performance capabilities for which automation technologies already

exist. While MGI uses this framework to conduct a detailed analysis of automation’s effect on different

occupations, the framework is also useful for exploring and explaining automation technologies. The

framework is shown below. The coloured rating system indicates relative performance of currently

available automated technologies compared to human capabilities.

Table 1: Current automation technologies compared to human performance across 18 capabilities

Below median Median Top quartile

Automation capability

Capability level

1

Description (ability to …)

Sensory perception

Sensory perception Autonomously infer and integrate complex external perception using sensors

Cognitive capabilities

Recognising known patterns/categories (supervised learning)

Recognise simple/complex known patterns and categories other than sensory perception

Generating novel patterns/categories

Create and recognize new patterns/categories (e.g., hypothesized categories)

Logical reasoning/ problem solving

Solve problems in an organized way using contextual information and increasingly complex input variables other than optimising and planning

Optimising and planning

Optimise and plan for objective outcomes across various constraints

Creativity Create diverse and novel ideas, or novel combinations of ideas

Information retrieval Search and retrieve information from a large scale of sources (breadth, depth, and degree of integration)

Coordination with multiple agents

Interact with others, including humans, to coordinate group activity


Output articulation/ presentation

Deliver outputs / visualisations across a variety of mediums other than natural language

Natural language processing

Natural language generation

Deliver messages in natural language, including nuanced human interaction and some quasi language (e.g., gestures)

Natural language understanding

Comprehend language, including nuanced human interaction

Social and emotional capabilities

Social and emotional sensing

Identify social and emotional state

Social and emotional reasoning

Accurately draw conclusions about social and emotional state, and determine appropriate response/action

Social and emotional output

Produce emotionally appropriate output (e.g., speech, body language)

Physical capabilities

Fine motor skills / dexterity

Manipulate objects with dexterity and sensitivity

Gross motor skills Move objects with multidimensional motor skills

Navigation Autonomously navigate in various environments

Mobility Move within and across various environments and terrain

1 Assumes technical capabilities demonstrated in commercial products, R&D, and academic settings; compared against human performance.

Source: Manyika et al. (2017, p. 35).

The following table relates these human capabilities to the types of automation technologies that

could play a role in replicating each category of human capability.

Table 2: How human capabilities may be replicated using types of automation technologies

Automation capability Automation technologies Enabling and supporting technologies

Sensory perception AI Neural networks Robotics

Computing; internet; cloud services; big data; nanotech and biotech; sensors, systems and materials

Cognitive capabilities AI Neural networks

Computing; internet; cloud services; big data

Natural language processing AI Neural networks

Computing; internet; cloud services; big data

Social and emotional capabilities

AI Neural networks Robotics

Computing; internet; cloud services; nanotech and biotech; sensors, systems and materials; mobile, smart and wearable devices

Physical capabilities Robotics AI

Computing; internet; cloud services; mobile, smart and wearable devices

Automation beyond human limitations The MGI classification above provides a useful way to understand the status of automation

technologies and what they can do in a human context (Manyika et al., 2017, p. 35). However, it

leaves a gap in understanding the broader possibilities of technology-only automation, given that it is

unconstrained by human needs and limitations. This extra perspective helps to convey a broader

sense of the value and potential of automation for Australian industry, leading to an improved

awareness of the potential implications for Australia’s workers and society.

Automated systems can potentially:

operate 24/7, 365 days a year

deliver a consistent level of performance (not affected by tiredness or distractions)


be highly scalable, particularly for computer-based automation and AI on cloud-computing

platforms; in this context, some authors talk of being able to ‘copy and paste’ AI-based

automated ‘workers’

operate at different scales to human workers – for example, by performing movement and

actions at physical scales that are particularly large or small compared to the human body

– and work at different time scales (faster, slower, scheduled)

work in extreme environments, without the work health and safety issues faced by human

workers.

Key points

For the purposes of this project, ‘automation’ can be defined as the use of technologies to

improve processes and outcomes that substantially reduce reliance on human

involvement.

Automation involves the use of a wide range of technologies, systems and processes.

What can be automated is evolving as technological development moves beyond physical

functions to encompass cognitive functions.

2. How will automation affect Australian industry? The potential of automation is not limited to new industries. There are significant opportunities to use

automation technologies and systems to improve mature industries. These mature industries often

involve large regional employers and represent high-potential markets for entrepreneurs, digital

businesses and start-up businesses looking to compete using automation.

Skilling strategies can ‘seed’ the speed and capability of these more mature industries to grow,

transform, and enhance not only their competitiveness but also their ability to retain or grow

employment. This can occur by:

automating to enhance operational efficiency, reduce costs and improve supply chains and

market access

shifting products, services and processes to target new customer segments

enhancing production technologies and processes

accessing lateral markets (adjacent market opportunities, old competencies and new

markets)

accessing incentives or regulatory reforms that encourage technology deployment tied to

enhanced global competitiveness

augmenting or enhancing job efficiency, making it more cost-effective not to outsource

certain activities to locations where labour costs are lower

improving logistics to reduce ‘to market’ time and costs.

Figure 2 indicates Australian industries that have been disrupted by digital technologies. The orange

arrows indicate industries that, according to Deloitte (2012), have relatively low levels of total digital

potential because they have already implemented many of the digital innovations available to them.

As a result, future disruption of these industries is predicted to be low. However, these industries and

others such as agriculture, forestry and fishing, and accommodation and food services (hospitality

and tourism), have significantly enhanced their competitiveness through process automation

initiatives such as RPA. This shows that the degree of transformation an industry has already

experienced is not necessarily a predictor for the potential of automation in that industry.


Figure 1: Australian industries and opportunities to grow and transform using automation

Source: Deloitte (2012, p. 8), Arrows have been added.

It is unwise to assume that the digital disruption or potential to automate an industry is static. Industry

transformation can take time and will be affected by new automation technologies and approaches.

Applying new technologies to an existing industry or business may not create a global, sustainable

competitive advantage, but it may buffer job loss and socio-economic impacts on a region or industry

for a sufficiently long period to allow the workforce and economy to transition to new opportunities.

Some principles guiding the use of automation as part of an industry development strategy include:

Emerging and new industries may offer growth, but industry and skills development

strategies need to accommodate the lag before sustainable employment is created in the

emerging industries.

Economic contribution may shrink over time, but removal of mature industries from the

economic mix can negatively affect a region’s economic performance and therefore it’s

national GDP. Mature industries are typically the heart of a region (familiar examples

include the regional impact from closing paper mills, steel smelters, car manufacturing

plants and mines).

Structural transformations take time.

The core competence of a mature industry’s workforce is often misaligned with future

needs, and the required reskilling and alignment takes both time and commitment.

Another industry development factor that is important to note is the ability of automation to challenge

outsourcing and bring certain jobs back to Australia. Activities such as call centres, textiles and

component manufacturing can be automated or their processes improved. This could not only

decrease cost but also raise productivity given Australia’s advanced infrastructure and skilled

workforce comparative to populous countries where these industries have been outsourcing activities

(King, 2015). The skills required to conduct a job that involves interaction with a machine or an

automated process involve higher levels of cognition and complexity than are necessarily available in

a low-skilled, under-educated workforce with the sole competitive advantage of cost (International

Federation of Robotics [IFR], 2016b; Forbes Leadership Forum, 2015).


Predicting the speed of automation and the extent of its adoption and impact in any industry is

difficult. Using McKinsey Global Institute (MGI) research (Manyika et al., 2017), five factors can be

isolated that affect the speed and extent of automation:

1. technical feasibility – the invention and integration of automation innovations within a

specific context

2. cost – the hardware and software costs of developing and deploying solutions

3. labour market – the supply of skills and demand-side costs to source human capital; reskill

the existing workforce; or manage those who will not be retained due to automation of

specific job roles or activities

4. economic – the impact on productivity, higher throughput, and increase in quality and

labour cost savings

5. social and regulatory - even as automation creates business benefits, its adoption may

have negative effects due to regulations, policy decisions or community or social costs that

either slow adoption or impact the bottom line.

Global technology disruption and Megatrends Automation is more than a standalone, isolated phenomenon. It is the confluence of many

megatrends and technological disruptions that make the speed and extent of automation in the

modern era more profound (Baur & Wee, 2015). Various megatrends continue to impact economies

and drive Industry 4.0 transformation beyond its European manufacturing origins to encompass all

industries and nations. These same megatrends are also affecting automation and will continue to

drive its widespread and expanding use.

Megatrends are drivers of change that have worldwide impact and transform all aspects of social and

economic activity. Very few business or individuals in Australia can remain unaffected by these

trends. It follows that businesses and individuals in all regions of Australia need to anticipate and

respond to megatrends.

Figure 2: Megatrends reshaping our future

Source: Bowles and Harris (2015).

As with nations across the globe, each megatrend will have a significant impact on Australia (OECD,

2016a; Hajkowicz, Cook, & Littleboy, 2012; Bowles & Harris, 2015). Each trend covers the following

domains:

Demographics – the current world population is growing but it is also ageing, growing

faster in certain countries, and increasingly concentrated in urban locations.

Technology disruption – technological innovations involve the technologies – machines,

systems, tools, hardware and software, and devices – that are transforming how humans

live, work and exist in their environment. Technology disruption has a profound impact on

business efficiency, productivity, quality and asset utilisation. It also has the potential to

transform societies and how people live and work.

Changing workforce – the workforce of the future is changing. Technology and other

trends are changing the nature of work and the nature of the opportunities that are being

offered by employers predominately in new and emerging industries. New job designs will

bring more technologically astute, creative and consumer-oriented expertise into roles.

The form of engagement is creating opportunities for jobs that are not location-specific and


often are short term, part time or casual. Workers with certain skill sets, capabilities and

with access to connectivity can access jobs outside their region, using channels to market

that are not bound by regional and national borders. Employment is growing in areas that

involve short-term contracts where an individual’s skills are amalgamated, hybridised or

grafted onto a project, or a job that may be shared with other workers. Many workers are

constrained from participation in jobs of this nature due to existing social demographic and

economic factors.

Social and sustainable – greater societal awareness of climate change, resource

shortages and the need to be sustainable is driving a commitment to renewable fuel and

energy sources, increased production capacity and reducing pollution.

Intensified global competition – international trade patterns, multilateral free trade

agreements and national policies are integrating regional markets into one global

marketplace. Emerging market exports are forcing developed markets to specialise in

high-quality goods and service provision.

Key points

Routine and high-volume work will be most readily automated, and the increasing

sophistication of automated solutions means that these criteria will be more important than

the level of difficulty or complexity of the task.

All industries are impacted by automation to varying extents and at varying speeds.

Job displacement will be uneven and difficult to predict across occupations, industries and

locations.

Old and new industries will be equally reliant on automation to harness operational



3. How will automation affect the Australian workforce?

Technologies that exist today and those under active development have important

implications for the workforce. They create opportunities for new products,

services, organisational processes, and business models as well as opportunities

for automating existing tasks, even whole occupations. Many cognitive and

physical tasks will be replaced by machines. At the same time, we expect new job

opportunities to emerge as increasingly capable combinations of humans and

machines attack problems that previously have been intractable. (Committee on

Information Technology, Automation, and the U.S. Workforce, 2015, p. 159)

Public discourse about the impact of automation on jobs has focused on the negative consequences

of job loss and disappearance of occupations. This section addresses this matter and will summarise

the negative case, moderate these insights and offer a view on the jobs most likely to have activities

and tasks automated.

…approximately two out of five NSW jobs have a high risk (above 70%) of being

computerised over the next decade or two. (Angus, 2015, p. 31)

Organisations seeking to be more agile and responsive to rapidly changing markets and technological

advances are harnessing disruptive technologies and business models that profoundly alter existing

business processes and how work is designed. Finding workers who can not only work productively

but also move rapidly to be productive in redefined work and organisational structures will become

more of a serious challenge for modern societies.


Figure 3: Workforce impact – automation and computerisation

Source: Working Futures (2017) using data sourced from Berriman and Hawksworth (2017); Frey and Osborne (2013).

When the Office of the Chief Economist (Edmonds & Bradley, 2015) and then CEDA (2015)

suggested over five million jobs – totalling almost 40 percent of existing Australian jobs – would have

a moderate to high likelihood of being replaced by automation in the next decade, awareness was

generated on the potential for extreme negative effects because of the rapid growth of automation

and its enabling technologies. In early 2016, a quick web search indicated more than 200 follow-up

news stories, reports and publications from reputable sources regarding the research (Bowles &

Lanyon, 2016a). Reports influencing industry, employment and educational responses have

continued to narrate the accelerating pace of change and the profound impact automation would have

on jobs, careers and future employment. In Australia, as in nations facing similar challenges, the

concern over how to deal with the consequences of automation has tended to focus on efforts to

enhance the business benefits derived from automation while mitigating the negative impact on

employment and society in general.

The impact of automation and computerisation on jobs was reported globally to audiences equally

anxious to those in Australia.

Figure 4: Global impact of automation and computerisation on jobs by 2020

* Cambodia, Indonesia, the Philippines, Thailand and Vietnam.

Source: Working Futures (2017) using data from Frey et al. (2016); Berriman and Hawksworth (2017); Chang, Rynhart, & Huynh (2016).


While the negative view on automation as a global disruption causing massive job loss may galvanise

attention, this perspective is deceptive. The research shows potential areas of impact, not negative or

positive consequences.

Automation is not, of itself, the sole cause for loss of jobs and dissolution of occupations. Automation

is part of the wider transformation of existing business models and how work is being designed and

transformed.

Nor will automation efforts readily replace jobs where there is a high level of perception and

judgement occurring in an unstructured environment (e.g. surgeons); use of creative intelligence (e.g.

digital marketing and design thinking); or application of cultural or social intelligence relating to

empathy with another human and engaging in a two-way communication with sensitivity (e.g. aged

care and counselling) (Frey & Osborne, 2013; Edmonds & Bradley, 2015).

The research that examines the impact of automation and computerisation on occupations certainly

suggests an impact that needs to be counterbalanced with research that examines the impact of

automation at the task or activity level (sub-occupational level). The later research suggests by 2025

automation may impact activities and tasks in upwards of 60 percent of jobs in countries such as

Australia, but only 9 percent of jobs, on average across 21 OECD countries are automatable (Arntz,

et al, 2016; Productivity Commission 2016, p. 4).

The reality is that it is highly unlikely that automation will displace 5 million workers in Australia by

2025. This is not to downplay the impact and the fact jobs will be lost. Certain activities and specific

tasks common to many jobs that are located in different industries and regions will be automated

(Chui, Manyika, & Miremadi, 2015; Cognizant, 2015). This may result in efficiencies that displace

workers. However, automation will also create new activities and tasks allocated to many jobs that will

require more workers and skills. This suggests that fear over automation not only replacing jobs but

also not creating enough new jobs is not substantiated by research (Autor, 2015; Productivity

Commission 2016; Arntz, et al, 2016; WEF, 2016, p. 19). As succinctly stated by McKinsey Global

Institute (Manyika et al., 2017):

While less than 5 percent of all occupations can be automated entirely using

demonstrated technologies, about 60 percent of all occupations have at least 30

percent of constituent activities that could be automated. More occupations will

change than will be automated away. (p. iii)

Even should automation replace 10 percent of occupations in Australia this level of transformation is

not unusual. In the 2016 and 2011 census more than 10 percent of respondents listed jobs that didn’t

exist in the previous census four years earlier (Working Futures, 2016; Arlington, 2016). The

fundamental difference is the extent and speed with which automation is affecting all parts of the

economy.

While the impact of automation will occur across the labour market, the level of automation and its

consequences will be uneven. CEDA (2015) made this point in their research (see Figure 9).

The most important change to the narrative of how automation and computerisation will impact jobs

has been to extend the traditional debate beyond job losses in routine, low-skilled jobs with a focus on

manual labour to include jobs that are routine, low skill and white collar but increasingly often highly

skilled and well paid whether they are manual or not. Automation is no longer replacing jobs just in the

production trades, in low-skilled jobs or in our rural communities; it is moving into professional

occupations and CBD office blocks. The perceived scope of the impact has also widened. In routine

jobs, we have moved beyond farming and manufacturing machine operators to large-scale impact on

workers in transport, mining, banking, retail service and clerical roles.

Nor are jobs that were about physical work the sole topic for discussion. Machine learning, cognitive

computing and many other developments in data analytics are all seeing automation affecting jobs

that were considered invulnerable to automation due to their high cognitive elements or complexity.

Fields that involve specialist skills and cognitive processes surrounding advice, administrative

procedures, assessment and decision-making are being successfully automated. This can result in


much higher reliability and less variation than the existing human processes (DeakinDigital, 2014).

Professional fields such as academia, financial planning, insurance advice, investment banking,

surveying, data analysis, law, information technology (IT), specialist government clerical work and

even call centre operation all represent areas where automation will have a profound impact in the

coming five years. The consequences for future work and employment in these vocations have not

been subject to detailed research outside major corporations.

Figure 5: Distribution of job categories against probability of computerisation

Source: (CEDA, 2015, p. 60)

Key points

Job displacement will be uneven and difficult to predict across occupations, industries and

locations.

The way that emerging technologies will shape automation in future for each industry and

occupation cannot be accurately predicted.

4. What skills will the Australian workforce need?

The accelerating pace of technological, demographic and socio-economic

disruption is transforming industries and business models, changing the skills that

employers need and shortening the shelf-life of employees’ existing skill sets in

the process. […] Even those jobs that are less directly affected by technological

change and have a largely stable employment … may require very different skill

sets just a few years from now as the ecosystems within which they operate

change. (WEF, 2016, p. 19)

The transformation we are confronting today has more in common with the world of work before the

industrial revolution than the industrial age. The rise of the industrial age drove one of the largest and

most profound global demographic shifts as workers moved from rural farming communities into

urban industrial jobs. This profound demographic shift continues today.

In 1910, around 26 percent of Australia’s workforce was employed in agriculture production; by 1960,

this had fallen to 10 percent; and by 2010, it was less than 3 percent of total employment (Rayner,


Tan, & Ward, 2010; Australian Bureau of Statistics [ABS], 2001). While the share of the total economy

reduced as new industries emerged, the gross value of agricultural output increased from $10 billion

in 1963 to $25 billion in 2003, reaching $54 billion in 2015 (Productivity Commission, 2005; ABS,

2016).

Automation is not the key cause of problems in the future work landscape, it is the uncertainty created

by the speed at which transformation is occurring and the seemingly uncontrolled impact on

employment across all industries and regions.

Much of the uncertainty relates to how young people will find jobs in the future. With systemic

unemployment or underemployment of young people (15–24-year-olds) and automation of routine

jobs – particularly in farm, service, food service industries and now increasingly in the white-collar

sector – the fear is that young people will have difficulty gaining entry into the workforce. As jobs for

life disappear and people are expected to transition between 15 and 25 jobs in their future careers,

commentators are questioning whether is the education system is preparing young people to be

employable (Owen, 2016; Morton, 2015).

Figure 6: Future of work for today’s 15-year-old

Source: Foundation for Young Australians (FYA 2015, p. 7).

FYA reported that more than one in three 15-19-year-olds (39 percent) are not studying and one in

four 20-24-year-olds (26 percent) are in part-time work (FYA, 2015). In some regions, over 21 percent

of 15-24-year-olds who had some form of work were underemployed, meaning that part-time or

casual work was not satisfying their requirements for hours of work, career needs, income and ability

to live independently (Bowles, 2014).

Unless we identify the skills required for future work, it will only become more difficult for young

people to identify entry points into a career and find meaningful, engaging work. Many researchers

have considered the skills that the education system should target to enable young people and

existing workers meet the requirements for future work.

The skills required for the future worker will change. Employers need higher-skilled talent that can

rapidly adapt and change as the nature of work and jobs evolves.

As activities and tasks are automated and new activities and jobs emerge, the nature of work will

change. More work will be contracted and organised into complete projects rather than within full-time

employment structures.

The WEF (2016) suggested that non-technical skills that were essential for future employability

spanned three dimensions: character qualities, foundational literacies and competencies.


Figure 7: Three skills dimensions for future work

Source: Deloitte Access Economics (2017).

The rising importance of soft skills also de-emphasises qualifications and education solutions that

only focus on a single package of skills for a discipline or vocation. It raises the employability of

individuals who can use their soft skills to better deploy technical skills in a range of contexts and

employment relationships.

Table 3: Typologies of future skills (non-technical soft skills)

Skill Employability skills

Australian Curriculum

DeakinCo. WEF future

skills 2020

Economist Intelligence

Unit

Self-management X X X

Communication X X X

Teamwork (including collaboration)

X X X

Problem-solving X X X X

Critical thinking X X X X

Digital/technology literacy

X X X X

Emotional judgement X X X X

Global citizenship X X

Ethics X X

Innovation X

Creativity X X X X

Continuous learning X

Enterprise skills X X

Source: Bowles and Lanyon (2016a); WEF (2016); Economist Intelligence Unit (2015); Department of Education and Training (2016); Australian Curriculum, Assessment and Reporting Authority (2016).

As automation advances, so national approaches to competency-based training need to adapt more

rapidly and remain relevant to the future workplace. While enrolling in a vocational qualification may

have prepared a person for entry into work, it will be a combination of formal and informal learning in


a lifelong, continuous process that will enable people to navigate technological disruption to their work

and career pathways.

As automated jobs continue to grow faster than those that are not automated (Frey & Osborne, 2013)

and industries that are able to compete in the globalised economy grow, so the education system will

need to change how it delivers the skill sets required by new and existing workers to operate in their

given context.

It is no easy task for a nation to equip a workforce to respond to technology

change. Nor is it simple to regulate, fund and recognise learning and development

that will increasingly occur in the workplace or through discrete experiences that

target contextual needs (The Economist, 2017).

Key points

Soft skills and transferable skills will be increase valued as a range of jobs transform and

workers need to transfer skills horizontally across occupational and industry boundaries.

Formal and informal learning in a lifelong, semi-continuous process will enable people to


5. What are the implications for training products? For this section, a scan of current training packages was conducted to identify which units of

competency and training packages will be impacted by automation. Analysis of this information

confirms the substantial task that is required for the national VET system to respond to the extent and

speed of automation and its impact on industries and occupations across Australia.

To conduct the scan, researchers manually sorted, classified and formed topics and keywords.

Consistent with methods in similar studies, humans were used to review face validity to cross-validate

findings across 67 training packages. This analysis reviewed training packages at unit of competency

level for evidence of automation activity. For a unit to be identified as containing automation, it had to

contain some development or active human engagement with technology, or activities that could be

automated. For example, many units were disqualified, as the only interaction was observation or

following a set of instructions. Automation was viewed as active engagement, such as manipulation of

computer programs, process improvement using technology or the streamlining of an operation or

activity through deployment of technology.

The method of grouping and capturing the results mirrored the types of automation identified in this

research paper. Using ANZSCO (ABS, 2006), areas of potential automation were derived and

matched with the training packages identified as containing units of competency impacted by

automation. The data is presented in the form of a table (see Table 7 below), with the industry

represented in the left column, the unit of competency in the second column and the training

packages represented by the unit in the far-right column.

Findings from training package analysis It is important to note that no competency standards were found that directly or indirectly cover how

the discovery, review, testing or execution of automation is undertaken. This implies that no formal

vocational skills training, vocational education qualification or skill set exists to enable the workforce

and businesses to meet future challenges identified in this report.

As with jobs, the study of the impact of automation on units of competency and training packages has

found that neither the extent nor the speed will be constant across all industries.

Unsurprisingly, many areas within the training packages contained little or no coverage of automation

where research confirms it has already occurred (e.g. coverage of RPA and use of drones for imaging

and surveying, to name but two of many such examples).


Excluding defence and some older training package remaining in use, 280 units were identified as

containing an activity or component that involves automation.

Those packages with the greatest levels of automation were transport (46); construction (40); property

services (31 – based on the available older package, CPP07), information technology (28) and

manufacturing (17). While the police training package (21) and some part of the defence package (62)

appeared to involve activities that can or are being automated, this was not investigated further due to

the absence of public detail on some units. In some cases, where automation is already evident in

jobs within the sectors, no units impacted by automation could be reported (e.g. in such industry

categories as wholesale, fishing, recruitment and cleaning).

The absence of units impacted by automation does not mean that automation will not affect jobs in

this sector or industry. Rather, it means that existing units do not reflect job roles, activities,

contemporary processes or ways of working that can be automated.

Table 7 indicates the level of exposure training packages have to the impact of automation on units of

competency. This is an initial, indicative analysis based on the number of units identified as containing

automation components or human activities that are being automated at the time of this report

(CEDA, 2015; Frey et al., 2016; Manyika et al., 2017; DeakinCo., 2017).

The rating scale used is as follows.

Low

(<4 units)

Moderate (4–6 units)

High

(7–14 units)

Extreme

(>15 units)

For instance, a rating of Low indicates no immediate impact on existing units of competency. An

Extreme rating indicates immediate impact on a high number of units relative to other training

packages and high exposure of jobs in this sector to immediate automation trends.

The rating is not a convulsive indication of either the speed or the extent to which this impact will

occur. The analysis also excluded any units where the wording was ambiguous or researchers could

not agree on the inclusion of the unit.

Table 4: List of SSOs and IRCs

SSO IRCs Training packages Impact

SkillsIQ

Community Sector and Development IRC

CHC Community Services

Client Services IRC

Direct Client Care and Support IRC

Children’s and Youth Services IRC

Aboriginal and Torres Strait Islander Health Worker IRC

Ambulance and Paramedic IRC

Complementary and Alternative Health IRC

Dental IRC

Enrolled Nursing IRC

First Aid IRC

Joint IRC

Technicians Support Services IRC

HLT Health

Local Government IRC LGA04 Local Government

Public Sector IRC PSP12 Public Sector

Wholesale, Retail and Personal Services IRC

SFL Floristry

SHB Hairdressing and Beauty Services

SIB10 Beauty



SIF Funeral Services

SIH11 Hairdressing

SIR07 Retail Services

Sport and Recreation IRC SIS Sport, Fitness and Recreation

Tourism, Travel and Hospitality IRC SIT12 Tourism, Travel and Hospitality

Artibus Innovation

Construction IRC CPC Construction, Plumbing and Services

Property Services IRC CPP Property Services (CPP07)

Skills Impact

Rural and Related IRC

AGF07 Agri-Food

AHC Agriculture, Horticulture and Conservation and Land Management

ACM10 Animal Care and Management

Meat IRC AMP Australian Meat Processing

Food Beverage and Pharmaceutical IRC FDF10 Food Processing

SUG02 Sugar Milling

Forest Management and Harvesting IRC

Timber and Wood Processing IRC

Timber Building Solutions IRC

FWP Forest and Forest Products Training Package

Pulp and Paper Manufacturing IRC FPP10 Pulp and Paper Manufacturing Industry

Racing IRC RGR08 Racing

Seafood IRC SFI11 Seafood Industry

PwC’s Skills for Australia

Business Services IRC BSB Business Services

Culture and Related Industries IRC CUA Creative Arts and Culture

CUS09 Music

Financial Services IRC FNS Financial Services

Printing and Graphic Arts IRC ICP Printing and Graphic Arts

Information and Communications Technology IRC

ICT Information and Communications Technology

ICT10 Integrated Telecommunications

Education IRC FSK Foundation Skills

TAE Training and Education

Automotive Heavy Vehicle IRC

Automotive Light Vehicle IRC

Automotive Strategic IRC

AUM Automotive Manufacturing

Automotive Heavy Vehicle IRC

Automotive Light Vehicle IRC

Automotive Strategic IRC

AUR Automotive Retail, Service and Repair

Civil Construction/Infrastructure IRC

Coal IRC

Drilling IRC

Extractive IRC

Metalliferous Mining IRC

RII Resources and Infrastructure Industry

Australian Industry Standards

Aviation IRC AVI Aviation

Corrections IRC CSC Correctional Services

Public Safety IRC DEF Defence

POL Police



PUA12 Public Safety

Maritime IRC MAR Maritime

Water IRC NWP National Water

Rail IRC

Transport and Logistics IRC

TLI Transport and Logistics

TLI10 Transport and Logistics

Gas IRC UEG11 Gas Industry

Electrotechnology IRC UEE11 Electrotechnology

Electricity Supply Industry Generation IRC UEP12 Electricity Supply Industry—Generation Sector

Electricity Supply Industry Transmission Distribution and Rail IRC

UET12 Transmission, Distribution and Rail Sector

IBSA Manufacturing

Textile Clothing and Footwear IRC MST Textiles, Clothing and Footwear Training Package

Aerospace Education and Training IRC MEA Aeroskills

Furnishing IRC MSF Furnishing

Manufacturing and Engineering IRC MEM Manufacturing and Engineering

Manufacturing Skills Australia Strategic IRC

MSS11 Sustainability

Process Manufacturing, Recreational Vehicle and Laboratory IRC

MSL Laboratory Operations Training Package

MSM Manufacturing

PMA Chemical, Hydrocarbons and Refining

PMB Plastics, Rubber and Cablemaking

PMC Manufactured Mineral Products

Appendix 2 contains the list of units identified through the training package scan.

Insights from ANZCO occupational data As disruptive business models emerge to compete in a global market, the pace of automation will

increase, and economic imperatives will break down some of the more entrenched ways nations and

professional bodies classify occupational boundaries. Based on the analysis of occupational data

(Frey & Osborne, 2013; CEDA, 2015) and findings from this research, the following jobs will be most

exposed to loss and dissipation as their role is shared or diluted into new roles and occupations:

drivers (truck, taxi, courier, etc.)

bankers (in particular, routing administrators, clerks, financial advisors, market analysts

and investment brokers)

miners

agricultural labourers

call centre and data processing workers

health care primary providers

freight handlers (logistics, stevedores, waterfront and warehouse workers)

marine engineers

educators (assessors, vocational lecturers, administration and general tertiary education

staff)

retail sales and service workers (especially in computers, real estate, supermarkets, liquor,

etc.)

manufacturing workers.

Despite the overwhelming focus on the negative consequences, automation and workforce

transformation also create opportunities. They also consolidate opportunities in roles not being


automated. The following job roles would represent opportunities for workers – particularly those

exposed to the negative impact of automation on employment or employability – to transition to areas

of predicted high growth:

agribusiness farmers with IT and mechatronic skill sets

care workers (e.g. aged, home or personal services)

medical professionals (e.g. GPs, surgeons, diagnostic and pathology professionals, and

nurses)

information and communication technology professionals (e.g. cybersecurity specialists,

enterprise architects, telecommunications engineers, business intelligence/data analysts,

programmers and applications developers)

advanced science, engineering and technology professionals (e.g. biological scientists,

biochemists, geoscientists, design engineers, structural engineers, digital and special

surveyors, and sustainable energy engineers)

ships officers

specialist logisticians and supply chain managers

business development and financial managers

business services/consultants

construction trades and managers

electrical-mechanical trades

specialist machine operators and technicians (advanced manufacturing workers)

protective services and security managers

digital media and creative workers

project managers

data-driven marketers

specialist teachers and digital educators

online/virtual trainers, coaches and assessors.

Possible action for competency development The components of how we undertake automation can be defined. Analysis of existing training

packages suggests that it is likely competency development will need to progress on three fronts:

1. Develop a set of automation competency standards to span the following phases in

automation:

a) research and discovery

b) business benefits analysis

c) design and testing

d) evaluation

e) deployment.

2. Review specific units of competency that need to be updated by training package owners.

3. Review where competency standards do not exist to cover the automation of processes,

activities or tasks related to a known vocation.

Nevertheless, how automation will affect a job or activities in a specific industry or occupation cannot

be predicted, nor can it be subject to anticipatory competency development. For example, when we

know drones will be used to conduct aerial surveying of structures we can start to determine the skills

and knowledge required to undertake the job roles. However, the technology is being deployed so

rapidly and developing so fast that we need to devise ways of developing units that can cover

emerging skills, or have enough flexibility to describe the present and be used for the future.

Key points

No competency standards directly address the skills required to design and implement

automation

Training packages that are extremely exposed to the impact of automation include:





At least 280 units of competency contain an activity or component that involves automation

The majority of units of competency describe one or more work processes that could

conceivably be replaced by some type of automation.


Issues for further consideration Key points raised throughout this paper for consideration by the Automation Skills Project Reference

Group have been divided into themes as outlined below:

Defining automation

• For the purposes of this project, ‘automation’ can be defined as the use of

technologies to improve processes and outcomes that substantially reduce reliance

on human involvement.

• Automation involves the use of a wide range of technologies, systems and processes.

• What can be automated is evolving as technological development moves beyond

physical functions to encompass cognitive functions.

Impact of automation on industry

• Routine and high-volume work will be most readily automated, and the increasing

sophistication of automated solutions means that these criteria will be more important

than the level of difficulty or complexity of the task.

• All industries are impacted by automation to varying extents and at varying speeds.

• Mature and new industries will be equally reliant on automation to harness operational



• Job displacement will be uneven and difficult to predict across occupations, industries

and locations.

• Even more difficult to predict is the new range of jobs and roles that will be created by

automation activities.

• The way that emerging technologies will shape automation in future for each industry

and occupation cannot be accurately predicted.

Future workforce skill requirements

• Soft skills and transferable skills will be valued as jobs transform and workers need to

transfer skills horizontally across occupational and industry boundaries.

• Formal and informal learning in a lifelong, continuous process will enable people to


• While all work will be affected in some way by automation, most competency

standards will still cover a wide range of work functions that will still be needed for

decades to come, as mature technologies will continue to survive in large parts of our

economy including with small business and regional workplaces.

Impact of automation on the VET sector

An initial scan of training packages found that:

• No competency standards directly address the skills required to design and

implement automation

• Training packages that are extremely exposed to the impact of automation include:




• At least 280 units of competency contain an activity or component that involves

automation

• The majority of units of competency describe one or more work processes that could

conceivably be replaced by some type of automation


Glossary The following is a glossary of key automation technologies and techniques sourced from the

McKinsey Global Institute.

Technologies and techniques Description/examples

Artificial intelligence

Field of computer science specializing in developing systems that exhibit “intelligence.” Often abbreviated as AI, the term was coined by John McCarthy at the Dartmouth Conference in 1956, the first conference devoted to this topic

Machine learning

Subfield of artificial intelligence developing systems that “learn,” i.e., practitioners “train” these systems rather than “programming” them

Supervised learning

Machine learning techniques that train a system to respond appropriately to stimuli by providing a training set of sample input and desired output pairs. Supervised learning has been used for email spam detection by training systems on a large number of emails, each of which has been manually labelled as either being spam or not

Transfer learning

Subfield of machine learning developing systems that store knowledge gained while solving one problem and applying it to a different but related problem. Often used when the training set for one problem is small, but the training data for a related problem is plentiful, e.g., repurposing a deep learning system trained on a large nonmedical image data set to recognize tumours in radiology scans

Reinforcement learning

Subfield of machine learning developing systems that are trained by receiving virtual “rewards” or “punishments” for behaviours rather than supervised learning on correct input-output pairs. In February 2015, DeepMind described a reinforcement learning system that learned how to play a variety of Atari computer games. In March 2016, DeepMind’s AlphaGo system defeated the world champion in the game of Go

Cognitive computing

Synonym for artificial intelligence

Neural networks

Artificial neural network

AI systems based on simulating connected “neural units,” loosely modelling the way that neurons interact in the brain. Computational models inspired by neural connections have been studied since the 1940s

Deep learning Use of neural networks that have many layers (“deep”) of a large number (millions) of artificial neurons. Prior to deep learning, artificial neural networks often only had three layers and dozens of neurons; deep learning networks often have seven to ten or more layers. The term was first used in 2000

Convolutional neural network

Artificial neural networks in which the connections between neural layers are inspired by the organization of the animal visual cortex, the portion of the brain that processes images, well suited for perceptual tasks. In 2012, the only entry using a convolutional neural network achieved an 84% correct score in the ImageNet visual recognition contest, vs. a winning score of 75% the year prior. Since then, convolutional neural networks have won all subsequent ImageNet contests, exceeding human performance in 2015, above 90%

Recurrent neural network

Artificial neural networks whose connections between neurons include loops, well-suited for processing sequences of inputs. In November 2016, Oxford University researchers reported that a system based on recurrent neural networks (and convolutional neural networks) had achieved 95% accuracy in reading lips, outperforming experienced human lip readers, who tested at 52% accuracy.

Robotics Soft robotics Non-rigid robots constructed with soft and deformable materials that can manipulate items of varying size, shape and weight with a single device. Soft Robotics Inc. grippers can adaptively pick up soft foods (e.g., baked goods, tomatoes) without damaging them.

Swarm robotics

Coordinated multi-robot systems, often involving large numbers of mostly physical robots

Tactile/touch robotics

Robotic body parts (often biologically inspired hands) with capability to sense, touch, exhibit dexterity, and perform variety of tasks

Serpentine robots

Serpentine looking robots with many internal degrees of freedom to thread through tightly packed spaces

Humanoid robots

Robots physical similar to human beings (often bi-pedal) that integrate variety of AI and robotics technologies and are capable of performing variety of human tasks (including movement across terrains, object recognition, speech, emotion sensing, etc.). Aldebaran Robotics and Softbank’s


Technologies and techniques Description/examples

humanoid Pepper robot is being used to provide customer service in more than 140 Softbank Mobile stores in Japan

Automation product categories

Autonomous cars and trucks

Wheeled vehicles capable of operating without a human driver. In July 2016, Tesla reported that its cars had driven over 130 million miles while on “Autopilot.” In December 2016, Rio Tinto had a fleet of 73 driverless trucks hauling iron ore 24 hours/day in mines in Western Australia

Unmanned aerial vehicles

Flying vehicles capable of operating without a human pilot. The unarmed General Atomics Predator XP UAV, with roughly half the wingspan of a Boeing 737, can fly autonomously for up to 35 hours from take-off to landing

Chatbots AI systems designed to simulate conversation with human users, particularly those integrated into messaging apps. In December 2015, the General Services Administration of the US Government described how it uses a chatbot named Mrs. Landingham (a character from the television show The West Wing) to help onboard new employees

Robotic process automation

Class of software “robots” that replicates the actions of a human being interacting with the user interfaces of other software systems. Enables the automation of many “backoffice” (e.g., finance, human resources) workflows without requiring expensive IT integration. For example, many workflows simply require data to be transferred from one system to another

Source: Manyika et al. (2017, p. 24).


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Appendix 1: Draft consultation plan and survey questions Consultation process

Appendix 2: Units of competency identified through training package scan

Training Package Unit Code Unit Title Release

Manufacturing

MSM/MSA07 Manufacturing Training Package

MEM16008A Interact with computing technology 1

MEMPE001A Use engineering workshop machines 1

MEM30031A Operate computer-aided design (CAD) system to produce basic drawing elements 1

MSFFM3009 Produce manual and computer-aided production drawings 1

PMBPROD375 Vulcanise products using an autoclave 1

PMBPROD265 Operate portable vulcanising equipment 1

MEM30033A Use computer-aided design (CAD) to create and display 3-D models 1

MEM23122A Evaluate computer integrated manufacturing systems 1

MEM05 Metal and Engineering Training Package

MEM23126A Evaluate industrial robotic applications 1

MEA271A Lay out avionic flight management systems 2


MEM23122A Evaluate computer integrated manufacturing systems 1

MSF Furnishing Training Package CUFDIG507A Design digital simulations 1


PPM Pulp and Paper Manufacturing

FWPCOT6205 Prepare an enterprise carbon management report 1

FWPCOT6209 Manage forest and wood products industry research 1

MST Textile, Clothing and Footwear


Mining

RII Resources and Infrastructure Services

CPPSIS5032A Capture new spatial data 1



CPPSIS5036A Integrate spatial datasets 1

RIICWD530D Prepare detailed design of surface drainage 2

RIIMEX602D Establish and maintain surface mining ground control and slope stability systems 2

RIIMEX603D Establish and maintain underground mining ground control and stable mining systems 2

RIIMEX604D Establish and maintain surface product haulage and transport systems 2

RIISTD201D Read and interpret maps 3

RIISTD302D Process data and maintain accurate records 2

RIIUND501D Implement the ventilation management plan 2

RIIUND601D Establish and maintain the ventilation management system 2

RIIUND603D Manage, operate and maintain the mine ventilation system 2

Accommodation and Food Services

FDF10 Food Processing FDFGR4001A Control power and automation for milling processes 1

FDFOP2060A Operate an automated cutting process

FDFFST4003A Apply digital technology in food processing 2

AMP Australian Meat Processing Training Package

AMPMGT502 Manage new product or process development 1

AMPMGT504 Develop, manage and maintain quality systems 1

FDFOP2060A Operate an automated cutting process

SUG02 Sugar Milling Training Package

SUGZPC2A Operate a process control interface 1

Tourism, Travel and Hospitality SITXICT401 Build and launch a small business website 1

BSBEBU501 Investigate and design e-business solutions 1

BSBFIA302 Process payroll 1

SITHGAM005 Analyse and report on gaming machine data 1

SITHGAM014 Manage gaming activities 1

SITHGAM015 Attend casino gaming machines 1

SITHKOP008 Select catering systems 1



SITTPPD007 Research and analyse tourism data 1

SITTTSL002 Access and interpret product information 1

SITTTSL010 Use a computerised reservations or operations system 1

SITXEBS002 Develop, implement and monitor the use of social media in a business 1

SITXINV005 Establish stock and purchasing and control systems 1

SITXMPR005 Participate in cooperative online marketing initiatives 1

SITXMPR007 Develop and implement marketing strategies 1

Construction

CPC08 Construction, Plumbing and Services

CPCPCM4013A Produce 2-D architectural drawings using CAD software 1

CPCPCM5010A Design complex sanitary plumbing and drainage systems 1

CPCPCM5011A Design complex cold water systems 1

CPCPCM5012A Design complex stormwater and roof drainage systems 1

CPCPPS5030A Design pump systems 1

CPCPPS5032A Design siphonic stormwater drainage systems 1

CPCPPS5033A Design vacuum sewerage systems 1

CPP07 Property Services CPPBDN4004 Set up BIM-capable software and files for building design drafting projects 1

CPPBDN4009 Analyse building design drawings and review findings 1

CPPSIS3011 Produce basic maps 1

CPPSIS4022 Store and retrieve spatial data 1

CPPSIS4024 Source and assess spatial data 1

CPPSIS4025 Collect spatial data using GNSS 1

CPPSIS4026 Digitally enhance and process image data 1

CPPSIS4034 Maintain spatial data 1

CPPSIS4035 Apply GIS software to solve spatial data problems 1

CPPSIS4037 Produce computer-aided drawings 1

CPPSIS4039 Design and produce maps 1



CPPSIS5032 Capture new spatial data 1

CPPSIS5035 Obtain and validate spatial data 1

CPPSIS5036 Integrate spatial datasets 1

CPPSIS5037 Maintain spatial data systems 1

CPPSIS5038 Develop spatial databases 1

CPPSIS5039 Plan and implement spatial projects 1

PPSIS5040 Interpret and collate spatial data 1

CPPSIS5043 Design spatial data storage systems 1

CPPSIS5047 Conduct GNSS surveys 1

CPPSIS5048 Conduct engineering surveys 1

CPPSIS5053 Perform advanced surveying computations 1

CPPSIS5054 Perform geodetic surveying computations 1

CPPSIS5060 Develop spreadsheets for spatial data 1

CPPSIS5064 Coordinate GIS data manipulation and analysis 1

CPPSIS5065 Design basic engineering structures 1

CPPSIS6022 Produce mine drawings 1

CPPSIS6036 Monitor engineering structures 1

CPPSIS6037 Conduct advanced remote sensing analysis 1

CPPSIS6040 Develop 2-D and 3-D terrain visualisations 1

CPPSIS6041 Compile mine survey plans 1

RII Resources and Infrastructure Industry Training Package

RIIMPG301D Control and monitor automated plant/machinery 2

RIICRC321D Use automated paving guidance systems 2

Electrical, Gas, Water and Waste Services

UEP12 Electricity Supply Industry - Generation Sector

UEENEEI150A Develop, enter and verify discrete control programs for programmable controllers 2

CPC08 Construction, Plumbing and Services

CPCPCM4013A Produce 2-D architectural drawings using CAD software (Release 1) 1



CPCPCM5010A Design complex sanitary plumbing and drainage systems (Release 1) 1

CPCPCM5011A Design complex cold water systems (Release 1) 1

CPCPCM5012A Design complex stormwater and roof drainage systems (Release 1) 1

CPCPPS5030A Design pump systems (Release 1)

CPCPPS5032A Design siphonic stormwater drainage systems (Release 1) 1

CPCPPS5033A Design vacuum sewerage systems (Release 1) 1

UEE11 Electrotechnology Training Package

UEENEEE077B Write specifications for automated systems projects 2

UEENEEI123A Design electronic control systems 3

UEENEEI130A Set up electronically controlled robotically operated complex systems 3

UEENEEI113A Setup and configure Human-Machine Interface (HMI) and industrial networks 3

UEENEEI136A Manage automated control systems projects 2

UEENEEI137A Plan automated and control systems projects 2

UEENEEI157A Configure and maintain industrial control system networks 2

UEENEEI153A Design and configure Human-Machine Interface (HMI) networks 2

UEENEEI151A Develop, enter and verify word and analogue control programs for programmable logic controllers 2

UEENEEI128A Set up and configure controls on complex fluid systems 3

UEENEEI129A Set up electronically controlled mechanically operated complex systems 3

UEENEEI152A Develop, enter and verify programs in Supervisory Control and Data Acquisition systems 2

UEENEEI154A Design and use advanced programming tools PC networks and HMI Interfacing 2

UEENEEI155A Develop structured programs to control external devices 2

UEENEEI156A Develop and test code for microcontroller devices 2

UEENEEI155A Develop structured programs to control external devices) 2

UEENEEI150A Develop, enter and verify discrete control programs for programmable controllers 2

NWP National Water Training Package

NWPIRR033 Coordinate and monitor the operation of irrigation delivery systems 1

NWPIRR032 Monitor and control rural water distribution operations 1



NWPNET004 Monitor and operate network systems 1

NWPNET005 Optimise network systems 1

NWPSOU053 Coordinate and monitor groundwater system usage 1

NWPSOU054 Monitor and operate pump stations 1

NWPTRT044 Operate and control desalination processes 1

NWPTRT045 Assess and improve desalination processes 1

UEG11 Gas Industry UEGNSG117B Plan and implement the data acquisition and metering requirements of a gas system 1

UEGNSG121B Prepare safe design specifications of a gas system 1

UEGNSG131A Compile a gas industry technical report 1

Rental, Hiring and Real Estate Services

CPP07 Property Services Training Package

CPPSPS4012A Design, install and service automated systems for swimming pools and spas 1

BSBITS401 Maintain business technology 2

CPPDSM3015B Use and maintain property and client information databases 1

Agriculture, Forestry and Fishing

FWP Forest and Wood Products Training Package


AHC Agriculture, Horticulture and Conservation and Land Management

AHCAGB402 Analyse and interpret production data 1

AHCAGB506 Manage application technology 1

AHCAGB50 Select and implement a Geographic Information System (GIS) for sustainable agricultural systems 1

AHCAGB501 Develop climate risk management strategies 1

AHCAGB507 Select and use agricultural technology 1

AHCAGB509 Select and implement a Geographic Information System (GIS) for sustainable agricultural systems 1

AHCAGB510 Implement the introduction of biotechnology into the production system 1

AHCARB405 Perform geospatial data collection 1

AHCARB603 Interpret diagnostic test results 1



AHCASW306 Use technology in Aboriginal sites work 1

AHCBUS405 Participate in an e-business supply chain 1

AHCIRG503 Design irrigation, drainage and water treatment systems 1

AHCLPW405 Monitor biodiversity 1

AHCNRM507 Manipulate and analyse data within geographic information systems 1

Arts and Recreation Services

CUA Creative Arts CUAACD503 Select and refine a specialised drawing technique 1

CUAACD506 Refine 2-D design ideas and processes 1

CUAACD502 Create observational drawings 1

CUAACD512 Work with photomedia in creative practice 1

CUADIG401 Author interactive media 1

CUADIG402 Design user interfaces 1

CUADIG403 Create user interfaces 1

CUADIG405 Produce innovative digital images 1

CUADIG502 Design digital applications 1

CUADIG508 Refine digital art techniques 1

CUADIG509 Investigate technologies for the creation of digital art 1

ICPRP484C Set up and operate automated workflow 1

CUFDIG507A Design digital simulations 1

CUADIG506 Design interaction 1

ICTICT306 Migrate to new technology 1

CUAANM303 Create 3D digital models 1

CUAANM302 Create 3D digital animations 1


CUS09 - Music CUSMCP501A Compose music using electronic media 2

CUSMPF409A Perform music using digital media 2



Health Care and Social Assistance

HLT Health HLTADM001 Administer and coordinate Telehealth services 2

HLTADM002 Manage Telehealth technology 3

HLTAHA025 Contribute to client flow and client information management in medical imaging 1

HLTAHW063 Implement office systems 2

BSBHRM502 Manage human resource management information systems 1

BSBINM501 Manage an information or knowledge management system 1

BSBRKG502 Manage and monitor business or records systems 1

HLTADM004 Manage health billing and accounting system 1

BSBWOR204 Use business technology 1

BSBRKG403 Set up a business or records system for a small business 1

BSBINM401 Implement workplace information system 1

CHCINF403D Coordinate information systems 1

CHC Community Services BSBITS401 Maintain business technology 2

Public Administration and Safety

DEF Defense Training Package DEFFOR003 Gather and analyse electronic information 1

PUA12 Public Sector Training PUACOM004B Manage organisational communication strategies 2

PSPSEC006 Implement security risk treatments 1

PUAPOL028B Manage investigation information processes 4

PUAECO004A Operate computer aided dispatch system 2

PUAFIR409B Develop air attack strategies 2

PSPBDR009 Analyse surveillance products 1

PSPSCI004 Undertake scientific/technological research 1

PSPSEC004 Undertake information technology security audits 1

PSPGSD012 Provide specialist technical service delivery 1

PSPREG016 Conduct data analysis 1



PSPSEC016 Define information systems framework 1

Professional, Scientific and Technical Services

BSB07 Business Services BSBSMB412A Introduce cloud computing into business operations 1

BSB Business Service Training Package

BSBMGT802 Lead design and review of enterprise systems 1

MSL & MSL09 Laboratory Operations/Lab Ops Training Package

MSL905003A Create or modify automated calibration procedures 1

PMA Chemical, Hydrocarbons and Refining

PMASUP341 Monitor and maintain instrument and control systems 1

PMC Manufactured Mineral Products

PMC556031 Design structural/mechanical components 1

Transport, Postal and Warehousing

MEA11 Aeroskills Training Package

MEA271A Lay out avionic flight management systems 2

MEA718 Evaluate rotorcraft flight control systems 1

MEA717 Evaluate avionic digital systems 1

UET12 Transmission, Distribution and Rail Sector Training Package

UEENEEI156A Develop and test code for microcontroller devices 2

UEENEEI155A Develop structured programs to control external devices) 2

MAR13 Maritime Training Package

MARL5007A Demonstrate basic knowledge of marine control systems and automation 1

AUM Automotive manufacturing AUMABA002 Operate load shifting equipment (Release 1) 1

AUMAKM002 Produce computer-aided drawings (Release 1) 1

AUMATK011 Use technical data relating to plant, tools, equipment and systems (Release 1) 1

AUMATR002 Install and maintain motor vehicle instrumentation sensors and transmitters (Release 1) 1

AUMATW001 Test vehicle welds ultrasonically (Release 1) 1

AUMGTR001 Install and replace vehicle electrical units and assemblies (Release 1) 1

AVI Aviation Training Package AVIW5013 Operate air traffic control equipment and workstations (Release 2) 2

TLI Transport and Logistics Training Package

TLISS00141 Ultrasonic Points and Crossings Testing Skill Set (Release 1) 1



TLIA5058 Manage facility and inventory requirements (Release 1) 1

TLIL5019 Implement and monitor transport logistics (Release 1) 1

TLIL5055 Manage a supply chain (Release 2) 2

UET12 Transmission, Distribution & Rail Sector

BSBINM501A Manage an information or knowledge management system (Release 1) 1

UEENEED104A Use engineering applications software on personal computers (Release 1) 1

UEENEED117A Install and configure network systems for internetworking (Release 1) 1

UEENEEE126A Provide solutions to basic engineering computational problems (Release 2) 2

UEENEEI156A Develop and test code for microcontroller devices (Release 2) 2

UETTDRDS35A Design overhead distribution power systems (Release 1) 1

UETTDRDS36A Design underground distribution power systems (Release 1) 1

UETTDRDS37A Design power system distribution substations (Release 1) 1

UETTDRDS38A Design power system public lighting systems (Release 1) 1

UETTDRDS43A Develop high voltage and low voltage distribution protection systems (Release 1) 1

UETTDRDS44A Design power system substations modifications (Release 1) 1

UETTDRDS46A Develop planned power systems outage strategies (Release 1) 1

UETTDRDS49A Establish and manage power system geographical information systems data (Release 1) 1

UETTDRDS50A Design customer power system substations (Release 1) 1

UETTDRDS51A Manage power system transmission and sub-transmission design process (Release 1) 1

UETTDRDS52A Design power system transmission, sub-transmission and zone substation buildings (Release 1) 1

UETTDRDS53A Design power system transmission and sub-transmission substation primary plant (Release 1) 1

UETTDRDS54A Design power system transmission and sub-transmission protection and control (Release 1) 1

UETTDRDS55A Design power system transmission and sub-transmission substation earthing (Release 1) 1

UETTDRDS56A Design power system transmission, sub-transmission and zone substation civil and structural components 1

UETTDRDS57A Design power system overhead transmission systems (Release 1) 1

UETTDRDS58A Design underground transmission systems (Release 1) 1

UETTDRSO36A Develop low voltage distribution switching programs (Release 1) 1



UETTDRSO37A Develop high voltage distribution and subtransmission switching programs (Release 1) 1

UETTDRSO38A Develop and evaluate power systems transmission switching programs (Release 1) 1

UETTDRSO51A Manage network systems power flows (Release 1) 1

UETTDRTS29A Develop power systems secondary isolation instructional documents (Release 1) 1

AUR Automotive Retail, Service and Repair Training Package


Education and Training

BSB Business Services Training Package

BSBLIB404 Use integrated library management systems 1

Information Media and Telecommunications

ICT10 Integrated Telecommunications Training Package

ICTITU7106B Manage automated ICT system applications using unix 1

ICTCBL4099A Remotely locate and identify cable network faults 1

ICT Information and Communications Technology

ICTICT815 Manage automated ICT system applications using enterprise wide operating system 1

ICTDMT402 Produce interactive animation 1

ICTGAM401 Produce an interactive game 1

ICTGAM402 Identify and apply principles of games design and game playing 1

ICTGAM404 Apply artificial intelligence in game development 1

ICTGAM410 Develop 3-D components for interactive games 1

ICTGAM412 Design interactive media 1

ICTPRG405 Automate processes 1

ICTWEB425 Apply structured query language to extract and manipulate data 1

ICTNWK411 Deploy software to networked computers 1

ICTPRG409 Develop mobile applications 1

ICTWEB417 Integrate social web technologies 1

ICTICT307 Customise packaged software applications for clients 1

ICTNWK306 Evaluate characteristics of cloud computing solutions and services 1



ICTNWK419 Identify and use current virtualisation technologies 1

ICTPRG604 Create cloud computing services 1

ICTICT814 Develop cloud computing strategies for a business 1

ICTICT423 Select cloud storage strategies 1

ICTGAM509 Design interactive 3-D applications for scientific and mathematical modelling 1

CUFDIG507A Design digital simulations 1

ICTICT306 Migrate to new technology 1

CUAANM303 Create 3D digital models 1



ICP10 Printing and Graphics Arts ICPRP484C Set up and operate automated workflow 1


Financial and Insurance Services

BSB07 Business Services BSBSMB412A Introduce cloud computing into business operations 1

FNS Financial Service BSBMGT802 Lead design and review of enterprise systems 1

BSBMGT801 Direct the development of a knowledge management strategy for a business 1

BSBADM506 Manage business document design and development 1

BSBMKG525 Design effective web search responses 1

BSBMKG527 Plan social media engagement 1

BSBMKG530 Create distributed multiplatform digital advertisements 1

BSBDES403 Develop and extend design skills and practice 1

BSBEBU502 Implement e-business solutions 1

BSBMKG421 Optimise digital media impact 1


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