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WILL MY JOB BE TAKEN BY A ROBOT?
David Brougham, Jarrod Haar and Yumiko Olliver-Gray
THERE IS GROWING PUBLIC CONCERN THAT ARTIFICIAL INTELLIGENCE, algorithms and robots will replace human labour, resulting in unemployment at an unprecedented level. This technological anxiety has resulted in an ongoing debate about the impact automation will have on work. The discussion interrelates with numerous disciplines and socio-economic challenges, from education and social welfare to the economy. This chapter focuses on: what types of work can be automated; whether automation will result in widespread unemployment; what the ideological, philosophical and social concerns are; and where future jobs may lie. Given that people can at least prepare for the future, and maybe even shape it to some degree, we aim to help readers assess their own prospects in relation to automation. We also discuss some of the wider potential issues and future options for New Zealand.
The automation of work
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.1 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. For example, the Baxter and Sawyer robots from Rethink Robotics are inexpensive, multipurpose devices that can be easily programmed to attend to a range of tasks with their mechanical arms, in stark contrast to previously difficult and expensive setups for automation that you could see in an automated factory, lights-out facility or a robotic clean-room. General-purpose robotics like Baxter can be implemented within existing workplace structures, without the need for completely rebuilding a workspace. Robots from Boston Dynamics give clues as to the speed at which robotics are currently capable of moving, even though at this point they have more of a military application.2
Robots like this 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 smart phones 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.
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.3
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 per cent and above) include telemarketers, data-entry 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.4
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.
Technological redundancy through automation can also be outsourced to the consumer. A clear example is the development of self-checkouts; here, a sophisticated robot with fine motor skills to scan the products or take an order is not required: a touch-screen computer is simply turned outward towards the consumer. Other examples include online forms replacing call-centre workers, and banking apps taking the place of high-street branches and tellers. When a consumer completes a task an employee once did, it is known as ‘shadow work’. The power of smart phones is already disrupting and changing the very nature of work and how we consume goods and services.
Disruption of an entire industry can also lead to a highly changeable time for employees. Consider, for instance, improvements in the production (and taste) of meatless meats, lab-grown meats and synthetic milk. Our agribusiness sector exports 95 per cent of its products to over 100 countries and feeds up to 40 million people.5 Even if you don’t (or won’t) eat lab-grown meat, there are other consumers who will — and many of these consumers will be located in our export markets. It is also possible that these products will cost less and be more environmentally friendly, constituting a more ethical choice. This type of disruption may eliminate some of the labour between farm gate and dinner plate. We will also see more automation in fruit picking and packing, along with more automated tractors and farm equipment, such as sensors in the soil and drones to deliver pesticides.6
Research suggests that 47 per cent of occupations within the United States could be at risk of automation, from an assessment of 702 occupations,7while another report estimates the OECD average to be as high as 57 per cent.8 And a report by the Chartered Accountants Australia and New Zealand suggests that 46 per cent of jobs within New Zealand could undergo automation over the next two decades.9 It was also found that in 2016, 40 per cent of New Zealand businesses were looking at automating processes.10
We have tested the public’s perception of automation and work. Our research found that a large majority (91.4 per cent) of employees did not see automation as a threat to their current job, career or organisation.11 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.12 It was also found that younger employees were more likely to cite automation as a threat to job security.13
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’.14 Positions facing a low risk of automation (probability of less than 3 per cent) include recreational therapists, emergency management directors, occupational therapists, physicians and surgeons, registered nurses, veterinarians and mechanical engineers.15 In a 2014 poll, researchers found that fewer than half (48 per cent) 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.
Automation and (un)employment
Fears of automation leading to mass unemployment are not new. Back in 1811, during the (first) industrial revolution in England, the Luddites smashed new machinery in the textile mills out of fear that it would put them out of work. But the counter-argument that automation creates jobs is also supported by looking at industry change caused by technological advancement in, for example, agriculture and manufacturing; while employment in these areas has declined, the service industry and an economy based on interaction has expanded.16
Previous industrial revolutions moved people from farming and other primary-sector jobs into manufacturing and other secondary-sector jobs. Many developed countries have seen their service sectors grow significantly over the past decades. These revolutions have created more and different jobs. A recent report by Deloitte in the United Kingdom suggested that over the past 140 years, more jobs have been created as a result of technology, with technology being touted as ‘a great job-creating machine’. The report found that, in the course of 15 years, 800,000 low-skilled jobs were eliminated as a result of automation technologies; in the same period, 3.5 million new jobs were created, paying an average of £10,000 (NZ$20,000) more per year than those that were lost.17
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 United States falls from 38 per cent to 9 per cent when all other variables are equal.18
Other arguments against automation causing job loss include the practical elements of automation design, creation and implementation. For example, robots are usually designed to carry out specific tasks; their reasoning abilities are limited, and they are unable to respond to unusual situations. Experts are predicting that automation may take a lot longer to reach human-like abilities, and so we may have more time than previously thought to prepare for this level of automation.19 As noted earlier, too, automation often creates jobs. Unemployment has not grown significantly in the United States in recent years, and job tenure has actually increased since 2000.20 We cannot simply assume that there are finite jobs in any industry, or that for every task that is replaced by a robot, an occupation becomes less viable.21
This new onset of automation might just be a time of difficult transition, rather than the start of mass unemployment,22 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.23 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’.24 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’.25 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 towards an attitude of integration, whereby we work with, rather than against, automation.26 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,27 and which focuses discussions on ‘redeployment’ rather than unemployment, emphasising the flexibility and added value for humans that integration across tasks can provide.28
Ideological, philosophical and social concerns
Elon Musk, Bill Gates and Stephen Hawking have asserted that automation may drive inequality and displace large amounts of people in the workforce in the coming decades. Musk predicts that ‘there will be fewer and fewer jobs that a robot cannot do better’.29 More recently however, Musk has said that some factories have in fact over-automated, resulting in slowed production, suggesting that human workforces have been under-rated.30 Some discussions grapple with more abstract notions, questioning the value of work, the meaningfulness of employment versus free time, and the underlying philosophies or ideologies that underpin our current engagement with automation. We need, for instance, to focus on distributive justice — how automated labour is distributed through society — and on the role that a job plays in determining people’s sense of identity, purpose and value. If people no longer work, what will they do with their lives?31 Many gain a great deal of satisfaction from identifying with a profession — for example, ‘I’m an accountant’ or ‘I am a teacher’ — and automation may result in occupations being more transient, with a knock-on effect on identity and self-worth.
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.
We might also question the purpose of automation: is it to replace humans, to enhance production, or to augment our way of life? What about the legal and social implications that automation may create? For example, if automation causes harm to people, who is responsible? Accidents from driverless cars will become more prominent. We may also see more social inequality as some jobs will be more immune to automation. We will most likely need to develop new policies and economic models, and discuss effects on basic human rights and inequality. Some have mooted a universal basic income as a means of addressing income disparity caused by job losses due to automation. Grounds for this were highlighted in a recent Oxfam report, which found that 82 per cent of all wealth created in 2017 went to the top 1 per cent of the population and none of it to the lower 50 per cent.32
Other considerations include gender and ethnic inequalities. The automation industry consists mainly of male engineers, computer scientists, etc. If further progress in automation and robotics were to result in a gender bias towards males, could it lead to women, more than men, being replaced by automation?33 This kind of imbalance could have a huge impact on the nature of employment and on society as a whole.
Technology also has the ability to polarise labour, and may result in the reduction of middle-class jobs, meaning we have far more low- and high-skilled jobs.34 People need stability in their work, as it provides security and gives them housing, food and other necessities. The potential rise of automation may lead to ‘less to do, less to hope for’ in terms of career aspirations and social mobility through hard work and opportunity. A disruption to a significant number of jobs in quick succession (such as driving, retail, food service work, etc.) may result in unemployment above a tolerable rate for our social systems to operate effectively, not least because there would be a shrinking number of taxpaying workers.
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, but there will be significant disruptions in the sector.
An ageing population requires an increase in medical and care employment. While some medical jobs could be automated, it is likely that they would be enhanced, rather than replaced, by technology. Hands-on jobs such as nursing are considered safe from automation because of the care and empathy needed in these roles,35 as well as the wide range of skills they call for. This need for care, empathy and the human touch was expressed in a TED Talk, by MIT professor and psychologist Sherry Turkle,36 who explored the sad predicament of elderly people in rest homes being attended to by talking software programs. It is essential to maintain occupations that involve face-to-face care and compassion if we are to keep the human connection, particularly given the increasing time people spend online with, for instance, social media. That said, the growth in an ageing population means increased demands for aged care; and thus providers might see technology as a cheap necessity to keep up with growing demands. Overall, we will need to question how appropriate it is to automate some jobs in the future. In addition, as our baby boomer population retires in the coming decades, automation might become necessary to drive productivity.
The desire to automate more processes so businesses can be competitive will continue, ensuring those with skills in computer science and automation will be in demand. Growth will also occur in clean energy and construction, compliance, and health and safety. Given the recently enhanced health and safety law within New Zealand, a greater push to remove employees from dangerous work through automation is likely, along with reducing highly repetitive work that results in human strain over time. One would hope that the dirty, dull, difficult or dangerous jobs and tasks for humans will be limited with this new wave of automation. It’s hard for us to imagine the variety and nature of jobs that automation will create in the future; yet considering today’s jobs in comparison to those prior to the first industrial revolution, it is apparent that we humans are innovative in finding ways to create employment, imagine new work, spend our time and consume products, services and experiences.
Considering today’s jobs in comparison to those prior to the first industrial revolution, it is apparent that we humans are innovative in finding ways to create employment, imagine new work, spend our time and consume products, services and experiences.
Recommendations and conclusions
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.
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.
In the famous words of Dennis Gabor, inventor and Nobel laureate, ‘The future cannot be predicted, but futures can be invented.’37 Inventing the future with regard to automation is open to us all: public, professionals, media and government. Discussing the topic of automation ‘taking over’ human jobs can help prompt questions about wider social influences and impacts. Future research could explore the influence of popular culture (within movies and TV shows) and the media on employee perceptions of automation in the workplace, and understanding the nature of technophobia may help us address people’s fears. Exploring tasks within occupations that are more likely to be automated, rather than determining what occupations may become redundant, may help foster a positive attitude towards automation within the workplace. Research across industries as to what tasks have become automated, those that may become automated and what jobs may be enhanced by ‘freedom’ from routine/mundane tasks, could be useful, too.
An extension of this theme is developing an understanding of what the ‘value-add’ automation has for individuals in their work and social environments. This can also be linked to considering the nature of ‘skills’ for future employment. 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. 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 (e.g. 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.38 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.
1 K. Schwab (2017). The Fourth Industrial Revolution. London: Penguin Books.
3 C. Frey and M. Osborne (2013). The Future of Employment: How susceptible are jobs to computerisation? Retrieved from http://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf.
4 Ibid.
5 New Zealand Trade and Enterprise (2017). Our Sectors — Agribusiness. Retrieved from https://www.nzte.govt.nz/en/buy/our-sectors/agribusiness/.
6 KPMG (2016). Agribusiness Agenda 2016, Volume 2: Foresight to the future. Retrieved from https://assets.kpmg.com/content/dam/kpmg/nz/pdf/November/agri-2016-vol2-kpmg-nz.pdf.
7 Frey and Osborne (2013).
8 Citigroup (2016). Technology at Work v2.0: The future is not what it used to be. Retrieved from http://www.oxfordmartin.ox.ac.uk/downloads/reports/Citi_GPS_Technology_Work_2.pdf.
9 Chartered Accountants Australia and New Zealand (2015). Disruptive Technologies, Risks, Opportunities — Can New Zealand make the most of them? Retrieved from https://nzier.org.nz/static/media/filer_public/6d/6e/6d6ecf8b-032c-4551-b0a7-8cd0f39e2004/disruptive_technologies_for_caanz.pdf.
10 C. Smylie (2016). Kiwi businesses preparing for robot automation, research shows. Retrieved from https://www.nbr.co.nz/article/kiwi-businesses-preparing-robot-automation-research-shows-cs-p-195591.
11 D. M. Brougham and J. H. Haar (2016). Repetition and Complexity: An insight into how employees perceive their jobs in the age of STARA. Paper presented at the HRINZ Research Forum 2016, Auckland, New Zealand. University of Auckland.
12 D. Brougham and J. Haar (2017). Employee assessment of their technological redundancy. Labour & Industry, vol. 27, no. 3, pp. 213–231, doi:http://dx.doi.org/10.1080/10301763.2017.1369718.
13 D. Brougham and J. Haar (2017). Smart Technology, Artificial Intelligence, Robotics, and Algorithms (STARA): Employees’ perceptions of our future workplace. Journal of Management & Organization, 1–19. doi:10.1017/jmo.2016.55.
14 O. Berlin (2017). Automation Nation: Will advances in technology put people out of work or give them new purpose? State Legislatures vol. 9, p. 8.
15 Frey and Osborne (2013).
16 H. Tayeb (2017). Robots Are Friends, Not Foes. Retrieved from http://ezproxy.massey.ac.nz/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=nfh&AN=2W62919427181&site=eds-live&scope=site.
17 Deloitte (2015). From Brawn to Brains: The impact of technology on jobs in the UK. Retrieved from https://www2.deloitte.com/uk/en/pages/growth/articles/from-brawn-to-brains--the-impact-of-technology-on-jobs-in-the-u.html.
18 M. Arntz, T. Gregory & U. Zierahn (2017). Revisiting the Risk of Automation. Economics Letters, no. 159 (July), pp. 157–160.
19 T. Walsh (2017). Expert and Non-Expert Opinion about Technological Unemployment. Retrieved from https://arxiv.org/ftp/arxiv/papers/1706/1706.06906.pdf.
20 J. Surowiecki (2017). Robopocalypse Not: Everyone thinks that automation will take away our jobs. The evidence disagrees. Wired, vol. 25, no. 9, p. 60.
21 M. Kirchner (2017). The Robots Are Coming — Will Your Job Be Next? With advancing automation, reconsider what robots have to offer. Products Finishing, vol. 81, no. 10, p. 52.
22 The Economist (2016). Automation and Anxiety. Retrieved from http://www.economist.com/news/special-report/21700758-will-smarter-machines-cause-mass-unemployment-automation-and-anxiety.
23 R. Hallett and R. Hutt (2016). 10 jobs that didn’t exist 10 years ago. World Economic Forum. Retrieved from https://www.weforum.org/agenda/2016/06/10-jobs-that-didn-t-exist-10-years-ago.
24 K. P. Erb (2017). Is Your New Tax Professional Secretly A Robot? Forbes. Retrieved from https://www.forbes.com/sites/kellyphillipserb/2017/07/20/is-your-new-tax-professional-secretly-a-robot/#4395fac535bf.
25 Kirchner (2017).
26 J. Danaher (2017). Will Life Be Worth Living in a World Without Work? Technological unemployment and the meaning of life. Science & Engineering Ethics, vol. 23, no. 1, pp. 41–64. doi:10.1007/s11948-016-9770-5.
27 Susskind, as cited by A. Gale (2017). Will Robots Make Us Redundant?, Management Today, May, pp. 40–44.
28 A. Gale (2017). Will Robots Make Us Redundant? ibid.
29 C. Weller (2017). Elon Musk Doubles Down on Universal Basic Income: ‘It’s going to be necessary.’ Retrieved from http://nordic.businessinsider.com/elon-musk-universal-basic-income-2017-2?r=US&IR=T.
30 S. Gibbs (2018). Elon Musk Drafts in Humans After Robots Slow Down Tesla Model 3 Production. The Guardian. Retrieved from https://www.theguardian.com/technology/2018/apr/16/elon-musk-humans-robots-slow-down-tesla-model-3-production.
31 Danaher (2017).
32 Oxfam (2018). Reward Work, Not Wealth. Retrieved from https://www.oxfam.org.nz/sites/default/files/reports/Reward%20Work%20Not%20Wealth%20-%20Oxfam%202018%20-%20Summary.pdf.
33 Hayasaki, E. (2017). Women vs. The Machine. Foreign Policy, vol. 222, pp. 38–47.
34 D. Acemoglu and D. Autor (2011). Skills, Tasks and Technologies: Implications for employment and earnings. Handbook of Labor Economics, vol. 4, pp. 1043–1171.
35 L. Scheltens (2017). The Robot-proof Job Men Aren’t Taking. Vox. Retrieved from https://www.vox.com/videos/2017/11/27/16692056/nursing-automation-men-jobs.
36 S. Turkle (2012). Connected, But Alone? TED.com. Retrieved from https://www.ted.com/talks/sherry_turkle_alone_together/transcript.
37 D. Gabor (1964). Inventing the Future, as cited by Y. O. de Lima and J. M. de Souza (2017). The Future of Work: Insights for CSCW. Paper presented at the 2017 IEEE 21st International Conference on Computer Supported Cooperative Work in Design (CSCWD), 26–28 April.
38 Berlin (2017).