Humans Need Not Apply: Artificial Intelligence, Robotics, Machine Learning, and the Future of Work

Humans Need Not Apply: Artificial Intelligence, Robotics, Machine Learning, and the Future of Work

Mike Berrell
Copyright: © 2021 |Pages: 26
DOI: 10.4018/978-1-7998-4159-3.ch003
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Advanced technologies including artificial intelligence, robotics, and machine learning (smart machines) impact understandings about the nature of work. For professionals, semi-professionals, and ancillary workers supplying healthcare and legal services, for example, smart machines change the social relations of work and subvert notions of status and hierarchy that come with occupational groups such as doctors or lawyers. As smart machines continue to disrupt employment, job advertisement might soon carry the warning that humans need not apply. Under the prospect of a new world of work, people require additional knowledge, skills, and attitudes to cope with a future where smart machines radically alter the nature of work in settings where some people work anywhere and anytime while others work nowhere. In any future, people require skills and attitudes to cope with uncertainty. Ideas about multiple intelligences, emotional intelligence, critical thinking, creativity, and problem-solving will help employees cope with any of the futures of work predicted in the literature.
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The idea of anywhere working is seductive. Ostensibly represented to workers as a choice among the competing options of working availability, anywhere working delivers a range of positive social and economic benefits to employers, employees, and the wider society. These outcomes include regional economic growth, a better work-life balance, improved working conditions, a reduction in pollution with fewer workers regularly commuting to work in petrol consuming vehicles and new opportunities for employers to retain workers and bolster a distributed workforce (cf. Haddon & Lewis, 1994; Messenger, et al., 2017).

In 1998, Davenport and Pearlson flagged the death of the traditional idea of the office, suggesting that technology will make these workplaces redundant. Ideas about different work options including telework, virtual work, and anywhere working tracked the rapid advances in 'information, digital and mobile technologies in business and personal communication' [ICT]. New work options extolled the virtues of these new technologies, advanced notions of flexible work arrangements [FWAs] and improved the well-being of employees. However, what scenarios emerge for anywhere working when ICT delivers unforeseen outcomes?

From ancient Egypt to the present, science and technology have been major game-changers. History mirrors technology's power to alter or even depose the most entrenched social, political, and economic discourses. Thinkers from different worldviews accepted this fundamental proposition. Aristotle knew this, so did diverse thinkers like Fredrich Nietzsche, Rene Descartes, Karl Marx, and John Maynard Keynes. However, knowing the potential of technology to overturn established ways of doing and thinking is no guarantee that any pundit's view over the horizon will arrive in the manner they envisaged.

Game-changing technologies usually develop over time. For example, the historian Eric Hobsbawm suggested the technological seeds of the Industrial Revolution planted in Britain during the 1780s took decades to propagate. It took a further 50 years for the social, economic, and political changes wrought by this revolution in material production to resonate in the societies of the time fully. When technology develops swiftly, and its uptake is immediate, a different story appears. In the US in 2001, only a handful of people knew of Apple's plan for the iPhone. With its release in 2007, sales topped 1.36 million units. Two years on, Apple sold about 40 million units. In 2019, sales reached 217 million; by then, Apple had dispatched 1.5 billion iPhones across the globe. Apple's revolutionary iPhone technology and the rate of uptake of the device reinvigorated Apple's business fortunes overnight.

These relationships between the development of technology, its application and rate of uptake are fundamental to imagining the future of work in any of its forms. However, whether the rate of change in the social relations of work created by ICT is gradual or rapid, it is contingent on the technology's utility for society. In this light, charting the future of work, workplaces and anywhere working with any degree of certainty is challenging enough. Nevertheless, in 2019, Forbes Magazine presented a blueprint for the future of work, and ITC supplied the foundations of this vision.

The thrust of the case for the future underscored structural changes that would radically reshape ideas of work developed during the first industrial age, the post-industrial age and in today's high-tech digital world (Marr, 2019). Bernard Marr proposed that the coming “4th Industrial Revolution” would compel employers to develop new mindsets about employees and workspaces, especially concerning the skills and knowledge necessary to be productive in the next stage of capitalism, an age in which automation is likely to be the most entrenched feature of work and workspaces. Marr also raised matters germane to education; specifically, the need to provide employees of the 4th Industrial Age with “emotional intelligence, critical thinking, creativity and problem-solving skills” to cope with the new social relations of work in a highly automated workplace.

Key Terms in this Chapter

Machine Learning: Is a branch of AI, which encompasses the study of algorithms and statistical models used by computers to execute specific tasks without using explicit commands.

Robotics: Refers to the field of computer science and engineering concerned with creating machines that react to sensory inputs – also a branch of AI.

Images of the Profession: This refers to one's professional self-concept - their professional image is based on attributes, beliefs, values, motives, and experiences gained through professional practice.

Multiple Intelligences: This describes the variety of ways people learn and acquire information. Proponents of the idea believe that single measures of intelligence, such as the Intelligent Quotient (IQ), are too narrow to account for the variety of ways people learn.

Social Relations of Work: In social science, social relations refer to any relationship between two or more individuals. Social relations derived from individual agency form the basis of a social structure.

4th Industrial Revolution: This idea suggests that today's stage of technological innovation is characterized by the continual and increasing integration and synthesis of technologies and technological ideas in ways that alter current understandings about the relationships between the physical world, digital technologies and human biology.

Artificial Intelligence (AI): This is a surrogate term for the theories of and developments in computer systems capable of performing tasks that require human intelligence.

Affective Domain of Cognition: In Bloom's Taxonomy of Learning Domains , the affective domain is concerned with an individual's development in attitudes, emotion, and feelings.

Smart Machines: Smart machines are devices that can teach themselves how to do things – today, permutations of AI, robotics, and machine learning with their implanted algorithms, coalesce as an age of smart machines.

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