Weekend Review: A positive future can only be a possibility if we determine who benefits from automation and how.
This edited extract from a chapter in The Big Questions: What is New Zealand’s Future? is reprinted by permission of the publisher, Penguin NZ.
When thinking about automation, many people imagine a high-tech robot taking over every aspect of their job. The reality, however, is that robotics makes up a very small part of the automation picture.
Job automation also includes algorithms, smartphone apps, artificial intelligence, computer software, driverless technology, drones, the Internet of Things, quantum computing, and more. Most of it is possible thanks to exponential leaps in computing power.
Today, new disruptions to traditional modes of production, apparent through advances in 3D printing, nanotechnology, biotechnology and the rapid combination of existing technology, amount to a fourth industrial revolution.
Technology has always changed society, and this new wave of automation has begun — and will continue — to disrupt many occupations and industries.
Automation of a person’s job may be considered a raw competition between technology and human labour. For example, a driverless car or truck could make the driver of a taxi or truck redundant in some settings.
However, automation can also compete with human labour indirectly by being slower but more cost-effective and consistent.
A general-purpose robot could work 24 hours a day, seven days a week without a break. A robot cannot injure itself, eliminating health and safety concerns. It requires no sick leave, annual leave, KiwiSaver contributions, ACC levies or other overheads. Its running cost is far less than the minimum wage.
General-purpose robotics like this are in their early development, and while they are agonisingly slow in their current form compared to performing manual labour against a human, the break-even point is near.
Comparing our current smartphones with a Nokia from the mid-2000s highlights how far technology has come in a short timeframe. It is not difficult to imagine how automation will advance during the decades to come, and how the costs of these units will continue to fall while wages, and worker overheads, continue to rise.
Skilled versus unskilled jobs
In popular wisdom it is the unskilled jobs that are most likely to be automated. However, when the cost of labour is high, the incentive to automate that labour is also high. As a result, many of the skilled professions and service-focused roles could be targeted for automation; these include technical writers, human resources assistants, medical and clinical laboratory technologists, insurance sales agents, retail salespersons, accountants and auditors.
Other industries affected include those with repetitive activities within jobs, such as the construction, retail and food service industries, as jobs that are increasingly specialised and fragmented are easier to automate. When the complexity of a job is reduced and the repetition within the work is increased, that job tends to become more scripted; that is to say, the human employee (say, a fast-food worker) has to follow a clear set of tasks to complete their job to specification.
Some of the roles that are at high risk of replacement (at a probability of 90% and above) include telemarketers, dataentry workers, insurance underwriters, driver/sales workers, farm labour contractors, meat/poultry/fish cutters and trimmers, automotive body repairers and HR assistants, to name a few.
Technology is more likely to change employment when part of a job is automated, which could create a net loss in the total employees needed. For example, automated accounting and data entry can mean some employees find the work requirements in their jobs decrease once the repetitive task of entering, ordering and checking data is taken over by automation. This may result, for example, in fewer accountants or administrators. Yet automating repetitive tasks may open workers’ daily timetables to more creative and customer-focused roles, potentially leading to a change in the employee’s role, rather than a loss of employment.
Public perceptions
We have tested the public’s perception of automation and work. Our research found that a large majority (91.4%) of employees did not see automation as a threat to their current job, career or organisation. But we also found that employees were unable to assess the true risk of automation to their job. For example, a checkout operator or driver did not see automation as a threat to their job, despite this threat being high.
By comparison, those in lower-risk occupations were more aware of, and more concerned about, automation in their line of work. An employee’s self-rated assessment of their job complexity and job repetition were good indicators of the risk of automation to their job, rather than asking them whether their job could be automated. It was also found that younger employees were more likely to cite automation as a threat to job security.
While it is easy to form a negative picture of the future in some industries, it is important to note that mass unemployment as a result of automation should not be seen as a foregone conclusion. The most difficult jobs to automate are those in the areas of science, technology, engineering and mathematics (STEM) — or those, according to commentator Olivia Berlin, “that call for creativity or the yet-to-be replicated ‘human touch.’”
She quotes the World Economic Forum, which suggested that “persuasion, emotional intelligence and teaching others will be in higher demand across industries … [in addition to] character, dependability and perseverance.”
Positions facing a low risk of automation (probability of less than 3%) include recreational therapists, emergency management directors, occupational therapists, physicians and surgeons, registered nurses, veterinarians and mechanical engineers.
In a 2014 poll, researchers found that fewer than half (48%) of nearly 2000 experts believed that robotics and AI would negatively affect the human workforce by 2025. The majority, albeit a slender one, predicted a positive future for us.
Research suggests that perceptions about the probability of specific jobs being replaced are unfounded. This is because automation tends to be task-based (activities done within a job), rather than occupation-based. So-called high-risk occupations, such as accounting and auditing, also involve tasks that cannot be automated, such as problem-solving and influencing.
There is a tendency to overlook tasks within a job and focus on an occupation as a whole, with the result likely to be an overestimation. When tasks within a job are taken into account, the risk of automation to jobs in the US falls from 38% to 9% when all other variables are equal.
Difficult transition
This new onset of automation might just be a time of difficult transition, rather than the start of mass unemployment, as people adjust to new ways of working and access new knowledge and skills for different tasks and roles. The speed of change will dictate the terms of change.
For example, this transition may be felt in one industry and disrupt a significant number of workers at a rapid pace; from a mass roll-out of driverless technology, for example. It is important to recognise that the transition often impacts those who do not have the skills and opportunities to move into different lines of work. As a society, we must be prepared for this eventuality. In other industries, such as the rise of internet business and smartphone apps, the effects of change can be more gradual.
Consider the types of jobs that did not exist 10 years ago. These include: Uber driver (previously, a casual taxi-driver), social media manager (previously, a marketing manager), app developer (previously, a software developer), big data analyst (previously, a statistician or analyst), content creator (previously there was no free worldwide platform or outlet like YouTube to draw an income from), driverless car engineer (previously, a vehicle designer/engineer/mechanic), millennial generational expert (previously, a social scientist specialising in age and culture), and solar installer (previously, a labourer).
Many jobs are simply changing because of technology, or are harnessing technology to be something different. Different skills will be in demand at different times.
It is likely that some work will change, as technology might play a greater role in some jobs, but the future of robots showing up in the workplace and escorting all redundant humans off the premises is unlikely.
One of the positive impacts of automation on employment is that it can add value to human work, shifting employees from routine, mundane tasks to what Forbes magazine calls “value-added work, like critical thinking.”
As businessman and columnist Matthew Kirchner puts it, the jobs created through automation “will be more interesting, less monotonous, safer [and] more rewarding and the purchasing power of wages earned in these new jobs will go even further.”
Automation will thus create more efficiency; and because it has the potential to free up human resources at unprecedented levels, people might be able to focus on developing other aspects of their roles, possibly enabling them to do them more effectively and creatively.
There is an argument, too, for a move toward an attitude of integration, whereby we work with, rather than against, automation. The challenge for both automation designers and relevant industries is not to get machines to replicate the way humans work, but to consider an approach that recognises the benefits automation provides, and which focuses discussions on “redeployment” rather than unemployment, emphasising the flexibility and added value for humans that integration across tasks can provide.
Where will the work be?
Job growth in certain areas will be driven by a few key international factors outside of the automation debate. The world population is growing, and New Zealand’s population, like that of many developed countries, is ageing.
These trends require the production of more food, shelter and infrastructure to meet world demand. Even with the advent of synthetic milk and meat we will need more jobs in science and technology to increase traditional farm yields.
This may not necessarily mean more farmers, but we can expect more agribusiness jobs in technology areas. There may still be a demand for traditional produce,
The extent to which automation will affect employment is highly debatable.
However, given technology’s track record, we owe it to ourselves and our futures to explore the field and plan accordingly. The flow-on effects of automation in the workplace could be widespread, and we need to discuss how to manage this at individual, social and political levels and across disciplines.
Implications for employees
New Zealand businesses will need to automate processes and jobs to some degree in order to create efficiencies, boost productivity and keep pace with onshore and international competitors. But they must also consider the implications for employees, particularly in industries where automation may potentially threaten aspects of a worker’s role or disrupt the entire industry.
Individually, too, the more we understand technology’s potential to affect our job, the better we can select appropriate skills and plan careers accordingly.
However, this awareness may result in possible skill shortages in some industries. For example, driverless technology may mean that professions like truck driving become less attractive, as the stability of driving as a long-term career may be questionable.
This results in fewer people training in this area, causing a skill shortage. Interestingly, this might enhance the opportunity for this new technology adoption, because of a self-fulfilling prophecy.
The focus should be on using automation to create a highly productive New Zealand economy, and on promoting the training and development of people who are replaced. New Zealand needs to develop the ability to train people for new lines of work that appear and new jobs that do not exist yet.
Training required
The training needs to be rapid in terms of both course completion and course development; it also needs to be inexpensive for the funders of that training (for example, industry, students and government) in comparison to what is currently available. Employers will need to consider and include upskilling programmes to retain employees if widespread automation takes place.
These ideas are not impossible: there are Massive Open Online Courses that are inexpensive, can be developed quickly and can be distributed to a wide audience. Thus, these challenges may have important future implications for education providers.
Understanding inequalities that exist and may potentially result from automation is a significant area for thought and discussion. This may include researching impacts on gender, age and ethnicity in tasks that have been, and are likely to be, impacted by automation.
How, what and who creates automation and biases (gender and ethnic) that may exist in the industry, and that then impact on employment and society, is an area for further discussion.
Optimism exists around how automation will shape and impact on work, with a clear move away from assumptions of mass unemployment due to automation. There is a possibility that job losses are overestimated.
We cannot know the future. But it is still important to consider a future where automation may compete with human labour in a wide range of occupations. We will always need something to do, something we value doing and something that offers us meaning. A positive future can only be a possibility if we determine who benefits from automation and how. Robots cannot do that for us.
Dr David Brougham is a senior lecturer at the Massey Business School, Dr Jarrod Haar is professor of human resources management at AUT and Yumiko Olliver-Gray has a doctorate in social anthropology from Massey University
This edited extract from a chapter in The Big Questions: What is New Zealand’s Future? is reprinted by permission of the publisher, Penguin NZ.
